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Report Krasny Project Scoping Study

Kopy Goldfields AB

AMC Project 218143 24 June 2019

Krasny Project Scoping Study Kopy Goldfields AB 218143

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Executive summary

Kopy Goldfields AB (Kopy) engaged AMC Consultants Pty Ltd (AMC) to undertake the Krasny

Project (Project) Scoping Study (the Study).

Kopy’s brief was to proceed with the Study based on a resource model prepared by others. The Study includes a review of the proposed approach to mine development options for the Krasny

Project, a preliminary review of the resource model and Mineral Resource estimate, and an

independent critical review of the existing Ore Reserve estimates for Krasny, including the

underlying assumptions and the modifying factors provided by Kopy and others.

The review activities have also considered the economic viability of the Vostochny exploration area, with a preliminary review of resource model and an outline economic assessment of the

potential economic viability of mining the mineralization identified as potentially economic.

The execution of the Study has been undertaken in separate discipline work packages and this

report reflects methodology, results and recommendation provided by each of the separate study

areas as follows.

Mineral resource model review

AMC has undertaken a high-level review of the Krasny resource model, together with the

supporting data provided, and has concluded that the model is suitable as a basis for mining

evaluation at the scoping level of study.

The following opportunities for improvement in the evaluation of Krasny mineral resources have

been identified by AMC to augment recommendations already set out in this review report.

Interpretation

The project previous study work describes the Krasny interpretation as consisting of four identified zones, made up of 12 individual solid wireframes. The different zones have similar

strikes and are mainly separated by poorly mineralized gaps or on the basis of different dips.

However, no underlying structural framework is described.

AMC has observed a possible relationship between some of the Krasny zones that may provide

such a framework for improved interpretations.

Figure I show an east-facing cross-section of the Micon interpretation shapes. The left-hand

panel has the interpretation outline superimposed over a window of drillhole grades, with values below 0.5 g/t Au filtered out, and with higher grades scaled for exaggeration. The right-hand

panel is the same section but with no window restriction on the visible samples. The right-hand panel image is strongly suggestive of an antiformal fold hinge, and a faulted offset of the lower

limb. AMC suggests that this structural framework be further investigated and, if substantiated,

it can be used to refine the interpretations.


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Figure I Krasny: Apparent fold-fault structural setting: view to east

AMC has further observed a potential plunge orientation not described in the previous study work, as illustrated in Figure II. If the plunge orientation can be confirmed, then this provides

an opportunity for potentially improving variogram quality, and also for a refinement of grade

estimation.


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Figure II Potential plunge orientation of gold grades

Estimation method

Further to AMC’s recommendation that a robust kriging estimation strategy should be introduced

to replace the inverse distance method applied at Krasny, AMC considers the Krasny spatial distribution of gold to be particularly suited to non-linear methods of estimation. Linear

techniques such as ordinary kriging, when applied to estimation panels (blocks) in the Krasny style of mineralization are at risk of over-smoothing the estimates relative to the gold distribution

evident from the drillhole assays. In these circumstances AMC recommends the appropriate use of non-linear techniques, such as multiple indicator kriging (MIK). By applying a localized version

of MIK (LMIK) the benefits of robust MIK estimates can be realized, but the estimates are presented as single gold grade values within selective mining unit-sized blocks, rather than as

grade distributions within panels, as generated by conventional MIK.

Mineral processing review

The Study investigated processing options for ore from the Project consisting of the Krasny

deposit and the Vostochny mineral occurrence.

The AMC review considered that the ore is characterized as a low-sulphide gold-quartz type. Samples that were tested were composed of quartz sandstones, siltstones and shales. An

oxidation zone extending down 20 m to 100 m from surface is present in the deposit. Samples

referred to as “primary”, “transitional”, and “oxide” were tested. Gold predominantly occurs in association with pyrite in primary ore and iron hydroxides in the oxide zone. Oxide ore is

considered to be free milling, with 91% cyanide-leachable, while primary ore is deemed

refractory with 85% able to be placed in solution by cyanide.

Preg-robbing carbon (organic carbon) was analysed in the samples that were tested. Reporting at 0.4% to 0.8% in oxide ore, 1.2% to 2.8% in primary ore, and 4% to 5% in flotation

concentrate were reported.


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Testing programs examined physical and mineralogical characteristics of samples of the ore, and

tested the following processing methods:

• Heap leaching.

• Gravity separation.

• De-sliming.

• Flotation.

• Cyanide leaching.

Previous project study activities recommended a gravity-flotation-CIL flowsheet which is

typically used to process gold ores of this type.

The following opportunities for improvement in the mineralogical assessment, mineral processing

evaluation and design of Krasny processing circuits have been identified by AMC as follows.

Sample selection

Sample selection for metallurgical testing, of the historical project study work, was based

primarily on degree of oxidation; as characterized by oxidation level. This percentage value was

calculated using iron assays, and it expressed the ration of iron fully oxidized to the Fe3+ state.

Three ore types were defined using oxidation level:

• Primary ore <25%.

• Transition ore 25% to 80%.

• Oxide ore >90%.

Samples of drill core were selected and composited to provide material for testing that

represented the three ore types.

While this approach yielded data on metallurgical performance for each ore type, AMC notes that

samples were not chosen and tested to examine locational variability throughout the orebody. This applies to comminution characteristics, gold recoverability, and presence of preg-robbing

carbon. AMC recommends performance of a full geometallurgical examination to model

metallurgical parameters during the next phase of study.

Test work conducted

Experience with a range of similar gold ores from the Irkutsk region and elsewhere in Russia led Irgiredmet to anticipate good metallurgical responses from SAG milling, gravity separation and

flotation of gravity tailings. Preliminary scoping tests were undertaken to investigate other approaches such as pressure oxidation, x-ray radiometric ore sorting and heap leaching,

however results were not positive, and the basic gravity-flotation combination was carried

forward.

Preg-robbing organic carbon in the ore was identified as a potential source of significant gold loss. Pre-floating of organic carbon and discarding of the concentrate is often used to remove

the gold-robbing fine particles prior to the CIL circuit. Irgiredmet did not recommend this approach on the basis of high gold losses experienced in early test results. Also, not

recommended was de-sliming of flotation concentrate by hydrocyclone classification which can

be economically viable if preg-robbing organic carbon is preferentially present in the ultrafine fraction, and the gold loss in the discarded ultrafines is less than the gold loss in the escaping

organic carbon when ultrafines are not removed. Both conclusions should be rechecked during

the next phase of study.

Use of organic carbon depression was evaluated and found to effectively reduce the organic carbon concentration in flotation concentrate (and hence in the CIL circuit). Detailed tests to

evaluate reagents and optimize dosage should be conducted.


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Irgiredmet forecast an overall Au recovery of 85.5%, from a feed grade of 1.54 g/t Au, with the

following intermediate recoveries:

• Gravity concentrate 60.19%.

• Gravity middlings 8.21%.

• Flotation concentrate 21.67%.

• Gold recovery by CIL 94.94%.

Previous studies used the three ore types (primary, transition, oxide) in their financial model of

the Krasny project, estimating overall gold recovery as follows:

• Primary 88.5%.

⎯ No direct basis for use of the TP-4 test result which was obtained from a blend of the

three ore types.

⎯ However, primary ore tests produced recoveries ranging from 84.8% to 92.8%, so

the use of this estimation is not unreasonable.

• Transition 87.8%.

⎯ Based on the pilot-scale test conducted in 2017 using a bulk composite (TP-4) with

a head grade of 1.6 g/t Au measured (1.9 g/t Au calculated) and oxidation level of

61%. Au recovery of 88.5% was estimated.

⎯ Transition ore tested during the mapping series (TK-2 and TK-5) produced good

recoveries similar to those achieved with primary ore.

⎯ This estimate is adequate for this stage of the project.

• Oxide 77.5%.

⎯ Based primarily on 2016 testing of the recommended flowsheet using the TP-3 oxide

sample.

⎯ Testing of oxide ore during the mapping series (TK-1 to TK-6) produced variable

results (64.2% to 80.7%).

Use of a modelled estimation of gold recovery based on degree of oxidation would improve the

reliability of gold recovery estimation. As discussed previously, a geometallurgical study could

provide data to develop such a relationship.

The previous project financial model, 2018, shows an average head grade for the project of

1.089 g/t Au and a gold recovery of 83.9%. The recoveries used are consistent with the testwork completed on the three ore types. AMC recommends more work to be done to quantify locational

variability, and to establish a reliable relationship between degree of oxidation and gold recovery.

Flowsheet design

AMC is generally aligned with the flowsheet design developed in the previous study work and

align with the recommended changes incorporated.

The comminution circuit appears to be designed on the basis of tests using a single Primary ore sample (Sample No.1). Primary ore was stated to be generally harder and more abrasive than

Oxide ore, so testing of only Primary material was deemed sufficient. The following physical and

ore hardness parameters were determined:

• Protodiakonov Strength Class IV (hard)

• Specific gravity 2.58 g/cm3 to 2.67 g/cm3.

• Bond crushing work index (CWi) 10.16 kWh/t to 11.9 kWh/t.

• Bond ball mill work index (BWi) 11.46 kWh/t to 15.54 kWh/t (medium-hard to hard).

• Bond abrasion index (Ai) 0.14 to 0.19.

As observed by Irgiredmet and Micon, Krasny ore can be characterized as medium-hard to hard and quite abrasive. A sample of Vostochny Transition ore was also tested, returning a BWi of

13.18 kWh/t which is consistent with Krasny material.


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AMC recommends that the following additional testing be conducted:

• Testing specific to the use of SAG milling which is a central part of the flowsheet.

• Testing of oxide and transition material to confirm plant operating ranges when treating

different materials.

• Testing to quantify locational variability of ore across the life of the project.

The simplified gravity-flotation circuit recommended by Micon has several significant

advantages:

• High efficiency centrifugal separators give the best opportunity to maximize gold collection

early in processing which increases recovery.

• Feed is not over-ground prior to gravity separation, limiting the opportunities for over-

grinding and loss of gold to the unrecoverable, ultra-fine fraction.

• The simplified flotation circuit requires less capital and is easier to run and maintain which

leads to increased recovery.

AMC recommends confirmation with testwork that the regrinding is not required in the flotation

circuit.

Hydrogeology

AMC undertook a review of the project hydrology reports, to assess dewatering requirements

and potential for surface and ground water and the likely impact upon the Project slope stability

and mining operations.

The investigations and conclusions presented in previous 2018 study work (Micon Mineral Resource and Ore Reserves Estimates report, 2018), are a reasonable preliminary estimate of

total potential inflow to the pit.

The preliminary nature of the assessment must be emphasized, and the results cannot be carried

forward to a dewatering plan. While the mine comprises a stratigraphic sequence of meta-

sediments, groundwater inflow will occur at discrete locations in association with structural

features.

The predicted volumes are such that management are likely to be difficult by sump pumping only. Advanced dewatering with strategically located boreholes screened across potential water

bearing structures have the potential to significantly reduce inflow volumes and pore pressures

near the pit face.

AMC recommend structural mapping to identify potentially water bearing structures that will

intersect the pit and provide targets for advance dewatering boreholes.

In addition, the paths of the Teplyi Creek and Wet streams must be diverted beyond the limits

of the Krasny pit prior to the commencement of mining to prevent surface water inflows.

Geotechnical

AMC undertook a geotechnical review, that included an assessment of the previous geotechnical

investigations and supporting data, and the appropriateness of the slope design

recommendations.

The project area is underlain by greenschist facies meta-sediments; namely meta-sandstone,

meta-siltstone and interlayered meta-sandstone and siltstone, which are classified as strong rocks with a low to well-developed foliation. Apart from some areas covered by alluvial deposits,

rock outcropping is wide spread. Weathering is shallow, where the competent rock occurs ≤5 m

below surface. Rocks are moderately fractured.


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In the project area, the rocks are folded into a west-north-west trending overturned anticline. The southern limb has a subvertical dip and the northern limb is open with en echelon folds. The

most important engineering geological factor impacting the pit slope design is the structural set up. The groundwater table has a southerly gradient towards the Bodaybo river, and the depth

to the water table is variable approximately 50 m to 100 m. Groundwater pressure has a main influence on slope stability on the north side, where depressurization will be required to achieve

recommended slope designs.

Based on the geological structure, AMC loosely defined four geotechnical domains and developed

geotechnical models. The available rock strength data limited geotechnical logging data from the

Vostochny deposit, inspection of core photographs from the Krasny area were used to develop basic geotechnical models. The geotechnical design parameters were derived using rock mass

classification methods.

The potential modes of instability of all pit walls were likely to be complex due to the strong

directional strength bias characteristic of the anisotropic (foliated) materials and the dip of foliation, and the dip direction relative to the proposed pit walls. Potential modes of instability

include:

• Circular failure, where failure occurs predominantly through the rock mass. In this case,

the rock mass strength takes precedence over structural influence on slope stability.

• Failure with partial control from structures, where the failure surface occurs partially

through the rock mass and partially along a structure.

Based on the results of the stability analyses, scoping level sloe design parameters were recommended, as presented in Table I and shown in Figure III. The recommended slope angles

are conformable with the slope recommendations given in Micon 2018 study.

Table I Recommended Krasny slope design parameters

Geotechnical

Domain

Batter Design Overall Slope

Bench

Height

(m)

Bench Face

Angle

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Bench Width

(m)

Geotechnical Berm Slope

Height

(m)

Slope

Angle

(°)

1 20 70 8.5 15 m 100 m vertical depth 360 50.7


3 20 60 10 20 m 100 m vertical depth 360 41.4



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Figure III Geotechnical domains and overall slope design recommendations

Krasny mining review

AMC undertook a review of the available mining reports to consider the deposit’s potential to be

developed into a viable economic mining operation. AMC have also performed a series of Project sensitivity analyses to investigate the potential opportunities to enhance the economic viability

of mining operation.

Comparison of Krasny open pit optimization results

Details of Revenue Factor 1 (RF1) pit optimization output shells generated by AMC and the

historical study work (Micon, 2018) for MII and MI cases are summarized in Table II. The RF1 pit shells generated by AMC and Micon are similar in size with a variance of 2% to 5% in total

material. The AMC pit shells achieved a similar depth and contained 3% to 6% less ore tonnage

compared to Micon RF1 pit shells.

Table II Comparison of AMC and Micon open pit optimization results

A west east cross section of the RF1 pit shells with an overlay of the resource model is shown in

Figure IV.

Case Source Au Cut-off Revenue

Factor

Total

Mining

Waste Ore Stripping

Ratio

Gold Gold Gold

g/t (Mt) (Mt) (Mt) (t:t) (kg) (oz) (g/t)

MII Micon 0.40 1 383.4 356.7 26.7 13.36 43,890 1,411 1.64

MII AMC 0.40 1 364.4 338.3 26.0 12.99 43,958 1,413 1.69

Variance -5.0 -5.1 -2.5 -2.8 0.2 0.2 2.9

MI Micon 0.40 1 38.6 31.9 6.7 4.76 7,659 246 1.14

MI AMC 0.40 1 37.8 31.5 6.3 5.00 7,565 243 1.20

Variance -2.0 -1.1 -5.9 5.0 -1.2 -1.2 5.2


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Figure IV West east cross section of RF1 pit shells

The comparative decrease in ore tonnages quoted between the 2018 Micon and AMC optimization

outputs is attributable to the small variance in cost input data utilized within the pit optimization cost and revenue parameters. AMC was able to reconcile the 2018 Micon reported Ore Reserve

inventory by removing the additional $0.70/t ore transport cost and excluding ore premium from

cut-off grade considerations.

It is worth noting that the project is characterized by large quantities of marginally economic grade ore, and relatively small fluctuations in the application of cut-off grade result in significant

increases in ore inventory.

Inspection of the Krasny grade-tonnage curve illustrates that around the cut-off grade of 0.4 g/t gold, which is the limit applied to the current Project Ore Reserve statement, there are sharp

changes in ore inventory associated with relatively small fluctuation of the cut-off grade. The cut-off grade of 0.4 g/t gold has been utilized in the optimizations, and for ease of comparison

to the previous iterations of work, AMC have continued to utilize this low cut-off. However, it is noted that the continued use of such a low representation of economic cut-off grade is likely to

artificially swell the ore inventory of the optimization outputs and may lead to negative impacts

on the project financial results.

AMC have utilized a cut-off grade of between 0.5g/t gold to 5.0g/t gold for the calculation of

underground inventories utilising the Mineable Shape Optimizer (MSO). The open pit Whittle pit optimizations utilized the 0.4g/t gold cut-off, in order to be comparable to the previous iterations

of work and align with the currently quoted 2018 Ore Reserve reporting by Micon. The combined open pit and underground production scenarios reported here by AMC, are based upon a higher

3.0 g/t gold cut-off grade for underground inventories, which more closely represents the current

Project economic breakeven.

AMC recommends estimating a cut-off grade that more closely represents the calculated cut-off from operating costs and gold recoveries. This is likely to be higher in future studies and is likely

to assist to de-risk the potential over-estimation of the ore inventory.

The Krasny grade-tonnage curve graph is shown below in Figure V.

Block model • Red Indicated• Green InferredPit shells• Pink Micon Indicated only• Purple AMC Indicated only• Green Micon Indicated and Inferred• Aqua AMC Indicated and Inferred


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Figure V Grade tonnage curve

Krasny open pit optimization sensitivity

The sensitivity of the project open pit optimization results to variations in the major input parameters was tested by changing the value of individual parameters while keeping all others

constant. Individual parameters changed include:

• Metal price.

• Processing cost.

• Mining cost.

• Processing rate.

• Pit slope angle.

• Metallurgical recovery.

Sensitivity analysis was completed for both Measured and Indicated (MI) and Measured, Indicated and Inferred (MII) resource category scenarios. The RF1 pit shells were selected for

parameter variance to explore the sensitivity of output shell size and corresponding financial metrics. The applied variation range for the input parameters were ±50% for metal price,

processing cost and mining cost. +50% to +400% for production rate, ±5° for pit slopes and

-10% to +2% for recovery.

Changes in the undiscounted cash flow variance for each parameter have been plotted, where a

steeper slope on any curve represents greater sensitivity to the parameter represented by that

curve.

The sensitivity analysis demonstrates that the undiscounted cash flow is most sensitive to changes in gold price. A 10% reduction in gold price results in a 27% decrease in undiscounted

cash flow. A 10% increase in processing cost results in a 8% decrease in cash flow.

The ore tonnage is sensitive to changes in gold price. A 10% reduction in gold price results in

an 5% decrease in ore tonnage. A 10% increase in processing cost results in a 4% decrease in

ore tonnage.

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AMC notes an average mining cost was applied in the open pit optimizations. The MII open pit optimizations achieve a greater depth compared to the MI case. Application of an incremental

mining cost will have a significant impact on the pit optimization due to the increased stripping ratio of the larger MII open pit shells. The sensitivity analysis shows a 30% increase in mining

cost results in an 25% decrease in cash flow. AMC recommend more detailed work be undertaken, during future study activities, to more accurately determine the variable open pit

mining cost in the deeper MII open pit optimizations.

The sensitivity analysis was reported on percentage change in undiscounted cash flow and ore

tonnes with results presented in Figure VI for undiscounted cash flow sensitivity.

Figure VI Krasny MII sensitivity - undiscounted cash flow

Krasny underground optimization

The underground potential was assessed and optimized using the MSO process in Datamine’s

5D Planner (5DP) software package. This process generates stope shapes at a range of variables including cut-off grades, floor to floor lift heights, stope widths and stope strike lengths. This

allows a relatively quick assessment of a deposit’s applicability for underground exploitation, the

types of mining methodology that may be applied (together with geological and geotechnical

inputs) and a preliminary assessment of potential mining inventory.

AMC conducted two types of MSO assessments. The first MSO assessment was to determine the suitability of the block model with the MSO process. This involved running MSO in multiple

scenarios with differing stope dimensions to ascertain any limiting or preferable variables. The results of this initial assessment showed that the block model was robust and that no limiting

variables were prevalent when used with the MSO process.

As the first assessment showed that MSO was able to generate an acceptable level of stoping

inventory at a range of stope dimensions, for the second MSO assessment AMC chose to use ‘standard’ stoping dimensions of 20 m strike length, a 20 m floor to floor lift height and a

minimum 1.5 m stope width as these stoping dimensions allow extraction by the most commonly

used underground mining equipment. The MSO process was ran using these stoping dimensions

at a range of cut-off grades from 0.5 g/t to 5 g/t.

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The MINPROP field was not utilized in the underground optimization component of this work. This is due to the fact that the underground MSO shapes have external dilution added to their

tonnages after the MSO process has been completed. For this level of study this is usually expressed as a percentage figure based on an estimate of the depth of failure for the hanging

walls, footwalls and sidewalls.

Krasny production scheduling

Preliminary production schedules were undertaken using the Milawa scheduler in Whittle. Milawa was used to determine the required material movement rate to deliver steady-state ore

production to the processing plant. The 2018 Mineral Resource and Ore Reserve report

considered a nominal plant throughput rate of 0.4 Mtpa, which AMC considers to be very low for the magnitude of the Krasny project. To present an easy comparison with the previous iterations

of study work, AMC has considered the same nominal plant throughput rate of 0.4 Mtpa, as well as presenting an additional analysis of 1.0 Mtpa, 2.0 Mtpa and 3.0 Mtpa throughputs, as a higher

production rate is likely to present more favourable economic outcomes.

Five scenarios were produced based on different configurations of processing plant capacity and

the inclusion or exclusion of Inferred ore in an open pit. A sixth scenario was produced with

consideration of underground mining. The six scenarios are defined as follows:

• Scenario 1 open pit (MI) – 0.4 Mtpa plant throughput.


• Scenario 3 open pit (MII) – 1.0 Mtpa plant throughput.

• Scenario 4 combined open pit and underground – 1.0 Mtpa plant throughput.



Krasny cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of each production scenario. The cumulative undiscounted cash flow is presented in Figure VII and

cumulative discounted cash flow is presented in Figure VIII. The financial model for each scenario

which includes mining and processing physicals is in Appendix B. A discount rate of 6% was used. Cash flows for the Micon scenario was derived from the Micon report. The pre-production

years, capital, property tax and profit tax have been removed for comparison purposes.

Figure VII Cumulative undiscounted cash flow excluding capital

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3.0 Mtpa MII Open Pit


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Figure VIII Cumulative discounted cash flow excluding capital

The outcomes of cash flow analysis show benefit in increasing the plant throughput rate from

0.4 Mtpa to 1.0 Mtpa. In the MI open pit scenario, the discounted value increased by 31%, exclusive of capital expenditure. By increasing the ore production rate, value is realized much

earlier in the mine life.

There is risk associated with mining the MII open pit as cash flow analysis shows a 13-year

period where the project is cash flow negative at a plant throughput rate of 1.0 Mtpa, which reduces to a seven-year period of negative cash flow at a plant throughput rate of 2.0 Mtpa. The

MI open pit captures a significant portion of the mineralization near surface and the remaining

portion of the orebody is at much greater depths. A significant amount of waste stripping is required upfront, to expose the mineralization in latter cutbacks, to maintain ore production

throughout the mine life.

Analysis shows the MI open pit to underground mining scenario has similar discounted value

compared to the 1.0 Mtpa MII open pit. The transition to underground does not require immediate capital investment, as in the MII open pit scenario, as a portal can be established

towards the bottom of the open pit. Value generated from mining the open pit can be used to

offset the cost of underground development.

For the current presentation of resource modelling, mineral processing and economics inputs;

AMC considers the combined Krasny open pit to underground mining scenario, at a production

rate of 1.0 Mtpa, to produce the highest value balanced against cash flow risk.

Recommendations for future work

AMC recommends future work should consider:

• Detailed ultimate pit and stage pit designs. Whittle pit shells provide guidance for developing an optimal ultimate pit. Consideration of access and practicality issues

associated with pit staging will often result in variances between design and pit shell. Additional waste is likely to be brought forward in a production schedule based on pit

designs as opposed to pit shells.

• Dilution and ore loss analysis. There are areas of the Krasny orebodies which contains

narrow vein mineralization where the application of dilution and ore loss factors in Whittle is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones

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that cannot be selectively mined to the level of accuracy suggested by these modifying factors. Conversely, application of global dilution and ore loss factors can penalize bulkier

zones of the orebody.

• High-grading and stockpiling study.

• Capital cost estimate for trade-off between operating scenarios.

• Waste dump design and mine site layout.

Exploration target – Vostochny

AMC completed a high-level evaluation of the Vostochny mineral occurrence, which is situated

north-east of the Krasny deposit.

Vostochny pit optimization

Pit shells were produced by the optimization process based on Measured, Indicated and Inferred

resources.

Vostochny production scheduling

Preliminary production schedules were undertaken using the Milawa scheduler in Whittle. Milawa

was used to determine the required material movement rate to deliver steady-state ore

production to the processing plant. AMC has considered a nominal plant throughput rate of

0.4 Mtpa, as well as presenting an additional analysis of 1.0 Mtpa throughput.

Vostochny cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of each

production scenario. The cumulative undiscounted cash flow is presented in Figure IX and

cumulative discounted cash flow is presented in Figure X.

The outcomes of cash flow analysis show a three-year period where the project is approximately cash flow neutral at a plant throughput rate of 1.0 Mtpa due to high material movement. There

is a difference of approximately US$32M in discounted cash flow between the 0.4 Mtpa and

1.0 Mtpa scenarios excluding capital expenditure.

AMC notes there is a high level of risk associated with both production scenarios due to the high

operating strip ratios.


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Figure IX Cumulative undiscounted cash flow excluding capital

Figure X Cumulative discounted cash flow excluding capital


AMC recommends future work should consider: • Detailed ultimate pit and stage pit designs. Whittle pit shells provide guidance for

developing an optimal ultimate pit. Consideration of access and practicality issues



• Dilution and ore loss analysis. There are areas of the Vostochny orebody, which contains narrow vein mineralization, where the application of dilution and ore loss factors in Whittle

is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones that cannot be selectively mined to the level of accuracy suggested by these modifying

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factors. Conversely, application of global dilution and ore loss factors can penalize bulkier





Combined Krasny and Vostochny production scenario

AMC has evaluated a combined production scenario of the Krasny deposit and Vostochny mineral occurrence. This scenario can be considered as an extension of the Krasny open pit and

underground scenario, with development of the Vostochny open pit beginning in 2030. Development of the Vostochny open pit is intended to supplement the underground ore

production from Krasny, rather than being operated as a standalone mining operation. Ore sourced from Vostochny will aid in maintaining the utilization of the processing plant capacity of

1.0 Mtpa for the life of the combined Krasny and Vostochny mining operations.

The Krasny underground mine will provide a nominal 0.487 Mtpa of ore production for

approximately nine years. Previous analysis of Vostochny showed that a total material movement

of 20 Mtpa was required to sustain ore production at 1.0 Mtpa without supplementation from external sources. This suggests that sustaining 1.0 Mtpa of ore production after completion of

Krasny underground would require significant capital investment due to the additional

requirements in mining capacity.

The annual head grade, ore and waste movements are summarized in Figure XI. Ore production

from Vostochny begins in 2027 and ore production from Krasny underground begins in 2028.

Figure XI Combined Krasny and Vostochny production profile

Combined Krasny and Vostochny cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of the combined Krasny and Vostochny production scenario. The cumulative undiscounted cash flow is presented

in Figure XII and cumulative discounted cash flow is presented in Figure XIII. The financial model for this scenario which includes mining and processing physicals is in Appendix D. A discount

rate of 6% was used.

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Figure XII Cumulative undiscounted cash flow excluding capital

Figure XIII Cumulative discounted cash flow excluding capital

Combined Krasny and Vostochny cash flow comparison

AMC has used Micon’s assessment of capital costs in the 2018 Mineral Resource and Ore Reserve

report to provide high-level indicative cash flows inclusive of capital costs for each production scenario. Micon’s capital cost estimates were based on an operation with 0.4 Mtpa plant capacity

and 5 Mtpa mining capacity.

AMC has used the six-tenths rule to scale Micon’s capital estimates to cover the spectrum of

processing and mining rates that have been presented. Different configurations of plant and

mining equipment would be more appropriate for larger scale operation. The scalability of mining equipment has not been considered in this cash flow analysis and a capital cost schedule has not

been produced. This rudimentary approach to the capital analysis provides a basic comparative

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output of project viability, however AMC recommend more detailed mining and processing

equipment specification activities be undertaken.

The joint Krasny and Vostochny cumulative undiscounted cash flow including capital is presented

in Figure XIV and cumulative discounted cash flow including capital is presented in Figure XV.

Figure XIV Undiscounted cash flow including capital

Figure XV Discounted cash flow including capital

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• Dilution and ore loss analysis. There are areas of Krasny and Vostochny orebodies which

contain narrow vein mineralization where the application of dilution and ore loss factors in

Whittle is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones that cannot be selectively mined to the level of accuracy suggested by these

modifying factors. Conversely, application of global dilution and ore loss factors can

penalize bulkier zones of the orebody.

• High-grading and stockpiling study. Production scheduling using specialized software such as Minemax is recommended as analysis in Milawa is restrictive and is less suited to multi-

pit scenarios.

• Capital cost estimate and re-evaluation of operating costs for trade-off between operating

scenarios.


Key financial outcomes

Following the completion of Study’s alternative productions scenarios, and associated Project

cash flow analysis, Kopy requested that AMC update the Project sensitivity analysis to reflect an

updated nominated gold price of US$1,300/oz.

The results from the updated project cash flow, for the combined Krasnoe and Vostochny

production scenario, is shown below in Table III.

Table III Krasnoe and Vostochny base case sensitivity analysis

Parameter Sensitivity Base Case Sensitivity

Gold price (USD/Oz) 1,200 1,250 1,300 1,350 1,400

DCF at 6%, pre-tax (MUSD) 63.6 83.9 104.2 124.5 144.8

IRR (%) 19 22 26 29 32

Discount rate (%) 5 6 7 8 9

DCF, pre-tax (MUSD) 118.2 104.2 91.9 80.9 71.2

Gold Grade, variance (%) 90 95 100 105 110

DCF, pre-tax (MUSD) 51.6 77.9 104.2 130.6 156.9

IRR (%) 16 21 26 30 34

A detailed memorandum has been produced to report this updated Project sensitivity work and the outcomes of the wider study results. A copy of this memorandum, Krasny Scoping Study

mine production scenarios and key financial outcomes 29 May 2019, is included in Appendix E

of this report.

Environmental aspects

AMC’s review of the environmental and social conditions of the Project analysed potential key

issues for further project development. The findings provided are based on relevant information gathered during a high-level desk-top review of the data and reports provided by Kopy and

others.

Based on the review of the provided information AMC has not found any environmental or social

fatal flaws or risks that could prevent or significantly delay the Project. AMC considers that the


amcconsultants.com xx

issues mentioned above are manageable and, if addressed appropriately, will not constitute a

major risk.

AMC recommends that Kopy develops and implements an environmental health and safety management system which is structured towards developing a proactive approach to the

management of environmental impacts and risks.

Due to the recent changes of the Russian regulatory requirements AMC strongly recommend

developing the environmental and social management procedures and plans taking the new

regulation into account.


amcconsultants.com xxi

Quality control

The signing of this statement confirms this report has been prepared and checked in accordance

with the AMC Peer Review Process.

Project Manager

24 June 2019

Adrian Jones Date

Peer Reviewer

24 June 2019

Martin Staples Date

Important information about this report

Confidentiality

This document and its contents are confidential and may not be disclosed, copied, quoted or

published unless AMC Consultants Pty Ltd (AMC) has given its prior written consent.

No liability

AMC accepts no liability for any loss or damage arising as a result of any person other than the

named client acting in reliance on any information, opinion or advice contained in this document.

Reliance

This document may not be relied upon by any person other than the client, its officers and

employees.

Information

AMC accepts no liability and gives no warranty as to the accuracy or completeness of information

provided to it by or on behalf of the client or its representatives and takes no account of matters

that existed when the document was transmitted to the client but which were not known to AMC

until subsequently.

Precedence

This document supersedes any prior documents (whether interim or otherwise) dealing with any

matter that is the subject of this document.

Recommendations

AMC accepts no liability for any matters arising if any recommendations contained in this document are not carried out, or are partially carried out, without further advice being obtained

from AMC.

Outstanding fees

No person (including the client) is entitled to use or rely on this document and its contents at

any time if any fees (or reimbursement of expenses) due to AMC by its client are outstanding.

In those circumstances, AMC may require the return of all copies of this document.

Public reporting requirements

If a Client wishes to publish a Mineral Resource or Ore / Mineral Reserve estimate prepared by

AMC, it must first obtain the Competent / Qualified Person’s written consent, not only to the estimate being published but also to the form and context of the published statement. The

published statement must include a statement that the Competent / Qualified Person’s written

consent has been obtained.

The signatory has given permission

to use their signature in this AMC

document

The signatory has given permission

to use their signature in this AMC

document


amcconsultants.com xxii

Contents

1 Introduction ........................................................................................................ 1

2 Mineral resource model review ............................................................................... 2 2.1 Data reviewed .............................................................................................. 2 2.2 Verification of reported tonnes and grades ....................................................... 2 2.3 Drilling adequacy .......................................................................................... 2 2.4 Interpretation .............................................................................................. 2 2.5 Statistics and variography .............................................................................. 5 2.6 Model construction ........................................................................................ 5 2.7 Density assignment ...................................................................................... 5 2.8 Grade estimation .......................................................................................... 7 2.9 Resource classification ................................................................................... 9 2.10 Krasny mineral resource opportunities ........................................................... 10

3 Mineral processing review .................................................................................... 12 3.1 Samples .................................................................................................... 12 3.2 Test results ................................................................................................ 13

3.2.1 Primary testing – Irgiredmet, 2012 ................................................ 13 3.2.2 Primary, oxide testing – Irgiredmet, 2015 ....................................... 14 3.2.3 Oxide testing – Irgiredmet recommended flowsheet, 2016 ................ 15 3.2.4 Variability testing – Irgiredmet, 2016 ............................................. 16 3.2.5 Vostochny testing – TOMS, 2016 ................................................... 16 3.2.6 Pilot-scale testing – Irgiredmet, 2017............................................. 17

3.3 Irgiredmet recommended circuit ................................................................... 17 3.4 Micon review and recommendations .............................................................. 20 3.5 AMC review and comments .......................................................................... 21

3.5.1 Sample selection ......................................................................... 21 3.5.2 Test work conducted .................................................................... 22 3.5.3 Flowsheet design ........................................................................ 23

4 Hydrogeology .................................................................................................... 24 4.1 Introduction ............................................................................................... 24 4.2 Information sources .................................................................................... 24 4.3 Hydrogeology overview ............................................................................... 25 4.4 Hydrogeological works completed ................................................................. 25

4.4.1 Test wells .................................................................................. 25 4.4.2 Assessment of inflows .................................................................. 28

4.5 Conclusion ................................................................................................. 29

5 Geotechnical ...................................................................................................... 31 5.1 Introduction ............................................................................................... 31 5.2 Geology and structure ................................................................................. 31 5.3 Previous stability assessments ...................................................................... 35

5.3.1 INRTU (2017) study .................................................................... 35 5.3.2 Review by Moscow State Mining Institute (2018) ............................. 35

5.4 Engineering geology .................................................................................... 36 5.4.1 Weathering ................................................................................ 36 5.4.2 Degree of fracturing .................................................................... 37 5.4.3 Rock mass classification ............................................................... 37 5.4.4 Rock mass structure .................................................................... 38 5.4.5 Geotechnical domains .................................................................. 39

5.5 Geotechnical design parameters ................................................................... 40 5.5.1 Unit weight ................................................................................ 40 5.5.2 Rock mass shear strength parameters ............................................ 41 5.5.3 Design parameters for discontinuities parallel to foliation .................. 42 5.5.4 Design groundwater conditions ..................................................... 42

5.6 Pit slope stability assessments ...................................................................... 42 5.6.1 Uncertainties in the geotechnical model .......................................... 43


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5.6.2 Potential failure modes ................................................................ 43 5.6.3 Acceptance criteria ...................................................................... 43 5.6.4 Overall slope stability analysis ....................................................... 44 5.6.5 Assumptions ............................................................................... 44 5.6.6 Results ...................................................................................... 44 5.6.7 Slope design recommendations ..................................................... 47

6 Krasny mining review .......................................................................................... 50 6.1 Introduction ............................................................................................... 50 6.2 Krasny pit optimization ................................................................................ 50

6.2.1 Whittle block model ..................................................................... 50 6.2.2 Krasny pit optimization parameters ................................................ 51 6.2.3 Krasny pit optimization results ...................................................... 52 6.2.4 Comparison of Krasny pit optimization results ................................. 54

6.3 Krasny pit optimization sensitivity ................................................................. 56 6.3.1 Krasny sensitivity analysis – Measured and Indicated ....................... 57 6.3.2 Krasny sensitivity analysis – Measured, Indicated and Inferred .......... 61

6.4 Krasny underground optimization .................................................................. 67 6.5 Krasny underground MINPROP field analysis ................................................... 68 6.6 Krasny production scheduling ....................................................................... 68

6.6.1 Scenario 1 open pit (MI) – 0.4 Mtpa plant throughput ...................... 69 6.6.2 Scenario 2 open pit (MI) – 1.0 Mtpa plant throughput ...................... 70 6.6.3 Scenario 3 open pit (MII) – 1.0 Mtpa plant throughput ..................... 70 6.6.4 Scenario 4 combined open pit and underground – 1.0 Mtpa plant

throughput ................................................................................. 71 6.6.5 Scenario 5 open pit (MII) – 2.0 Mtpa plant throughput ..................... 72 6.6.6 Scenario 6 open pit (MII) – 3.0 Mtpa plant throughput ..................... 73

6.7 Krasny cash flow analysis ............................................................................ 74

7 Exploration target – Vostochny ............................................................................. 77 7.1 Vostochny pit optimization results ................................................................. 77 7.2 Vostochny production scheduling .................................................................. 81

7.2.1 Scenario 1 open pit (MII) – 0.4 Mtpa plant ...................................... 81 7.2.2 Scenario 2 open pit (MII) – 1.0 Mtpa plant ...................................... 82

7.3 Vostochny cash flow analysis ........................................................................ 83

8 Combined Krasny and Vostochny production scenario .............................................. 85 8.1 Combined Krasny and Vostochny cash flow analysis ........................................ 85 8.2 Combined Krasny and Vostochny cash flow comparison .................................... 86 8.3 Recommendations for future work ................................................................. 89 8.4 Key financial outcomes ................................................................................ 89

9 Environmental aspects ........................................................................................ 91 9.1 Introduction ............................................................................................... 91 9.2 Regulatory framework ................................................................................. 91

9.2.1 Russian environmental regulation .................................................. 91 9.2.2 International financing requirements .............................................. 92

9.3 The Project environmental management and studies ....................................... 93 9.4 Environmental and social settings ................................................................. 93 9.5 Environmental and social issues and risks ...................................................... 95 9.6 Studies required for the next stages of the Project development ........................ 96

9.6.1 Environmental scoping study ........................................................ 96 9.6.2 Baseline studies .......................................................................... 97 9.6.3 Stakeholders engagement ............................................................ 97 9.6.4 Full-scale impact assessment and management system .................... 98

9.7 Conclusions ............................................................................................... 98

10 References ........................................................................................................ 99 10.1 Mineral processing ...................................................................................... 99 10.2 Mineral resource model ............................................................................... 99


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10.3 Environmental aspects ................................................................................ 99 10.4 Geotechnical .............................................................................................. 99

Tables

Table 2.1 Bulk density statistics by oxidation zone (t/m3) ............................................. 6

Table 3.1 Samples for metallurgical testing .............................................................. 13

Table 3.2 Gold recovery by gravity and flotation – variable oxidation levels ................... 16

Table 4.1 Supplied information sources .................................................................... 24

Table 4.2 Test pumping summary (Kopy, 2016) ........................................................ 27

Table 4.3 Estimated indicators of surface water inflow (Kopy, 2016) ............................ 29

Table 5.1 Rock strength data (MSMI, 2018) .............................................................. 36

Table 5.2 Stability assessment results (MSMI, 2018) ................................................. 36

Table 5.3 Rock mass classification based on RQD and RMR ......................................... 38

Table 5.4 Joint condition rating ............................................................................... 38

Table 5.5 The range RMR89 and GSI ratings applicable to Krasny rock mass .................. 38

Table 5.6 Design rock mass shear strength parameters .............................................. 42

Table 5.7 Typical slope design acceptance criteria (Read and Stacey, 2009) .................. 43

Table 5.8 Adopted slope design acceptance criteria ................................................... 43

Table 5.9 Results of the stability analysis ................................................................. 44

Table 5.10 Recommendations for slope design ............................................................ 48

Table 6.1 Mineral Resource model fields used in optimization ...................................... 51

Table 6.2 Pit optimization cost and revenue parameters ............................................. 52

Table 6.3 Krasny pit optimization results for run 8 MII ............................................... 53

Table 6.4 Krasny pit optimization results for run 8 MI ................................................ 53

Table 6.5 Comparison of AMC and Micon pit optimization results ................................. 55

Table 6.6 MI sensitivity - pit optimization results ....................................................... 57

Table 6.7 MII sensitivity - pit optimization results ...................................................... 62

Table 6.8 Summary of MSO outputs ........................................................................ 68

Table 7.1 Pit optimization results for run 1 MII 0.4 Mtpa ............................................ 78

Table 7.2 Pit optimization results for run 1 MII 1.0 Mtpa ............................................ 79

Table 8.1 Capital costs for scenario comparison ........................................................ 88

Table 8.2 Krasnoe and Vostochny base case sensitivity analysis .................................. 90

Table 9.1 Average monthly temperatures and precipitations ....................................... 94

Figures

Figure 2.1 Krasny: interpreted mineralizes zones ......................................................... 3

Figure 2.2 Holes inclined down-dip: oblique ................................................................. 4

Figure 2.3 Holes inclined down-dip: cross section ......................................................... 4

Figure 2.4 Krasny bulk density distributions by oxidation zone ....................................... 7

Figure 2.5 Spatial distribution of potential outlier grades ............................................... 8

Figure 2.6 Misaligned search orientation: upper southern zone ....................................... 9

Figure 2.7 Krasny: Apparent fold-fault structural setting: view to east ........................... 10

Figure 2.8 Potential plunge orientation of gold grades ................................................. 11

Figure 3.1 Irgiredmet flowsheet ............................................................................... 19

Figure 3.2 Recommended processing flowsheet (Micon, Aug 2018) ............................... 21

Figure 4.1 Overview map of the area of work. Scale 1: 250,000 (Отчет гидрогеология 2016-

HydrologyREport2016, Kopy) ................................................................... 24


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Figure 4.2 Test well locations (Kopy, 2016) ............................................................... 26

Figure 5.1 Geological map of the Krasny Deposit area (after Micon, 2018) ..................... 32

Figure 5.2 Geological cross section across the central part of the Deposit (Micon, 2018) .. 32

Figure 5.3 Geological sections A-A1, B-B1, C-C1 and D-D1 .......................................... 34

Figure 5.4 Rock fracture data for drillhole 141789 ...................................................... 37

Figure 5.5 A potential foliation shear in drillhole 141478 .............................................. 39

Figure 5.6 Geotechnical domains in the Krasny mining area ......................................... 40

Figure 5.7 Geotechnical domain-1 stability of 50° overall slope .................................... 45

Figure 5.8 Geotechnical domain-3 stability of 50° overall slope (failure through rock mass)

............................................................................................................ 45

Figure 5.9 Geotechnical domain-3 stability of 45° overall slope (failure through rock mass

and along foliation, no draw down) ............................................................ 46


and along foliation, complete depressurization) ........................................... 47

Figure 5.11 Proposed slope profile for geotechnical domains 1,2 and 4 ............................ 48

Figure 5.12 Proposed slope profile for geotechnical domain-3 ........................................ 49

Figure 5.13 Geotechnical domains and overall slope design recommendations .................. 49

Figure 6.1 Pit optimization results for run 8 MII .......................................................... 54

Figure 6.2 Pit optimization results for run 8 MI ........................................................... 54

Figure 6.3 West east cross section of RF1 pit shells .................................................... 55

Figure 6.4 Grade tonnage curve ............................................................................... 56

Figure 6.5 MI sensitivity - undiscounted cash flow ...................................................... 58

Figure 6.6 MI sensitivity – production rate – undiscounted cash flow ............................. 58

Figure 6.7 MI sensitivity – pit slopes - undiscounted cash flow ..................................... 59

Figure 6.8 MI sensitivity - recovery - undiscounted cash flow ....................................... 59

Figure 6.9 MI sensitivity - ore tonnage ...................................................................... 60

Figure 6.10 MI sensitivity – production rate – ore tonnage ............................................ 60

Figure 6.11 MI sensitivity - pit slopes - ore tonnage ..................................................... 61

Figure 6.12 MI sensitivity - recovery - ore tonnage ....................................................... 61

Figure 6.13 MII sensitivity - undiscounted cash flow ..................................................... 63

Figure 6.14 MII sensitivity - production rate - undiscounted cash flow ............................. 64

Figure 6.15 MII sensitivity - pit slopes - undiscounted cash flow ..................................... 64

Figure 6.16 MII sensitivity - recovery - undiscounted cash flow ...................................... 65

Figure 6.17 MII sensitivity - ore tonnage .................................................................... 65

Figure 6.18 MII sensitivity - production rate - ore tonnage ............................................ 66

Figure 6.19 MII sensitivity - pit slopes - ore tonnage .................................................... 66

Figure 6.20 MII sensitivity - recovery - ore tonnage ..................................................... 67

Figure 6.21 Scenario 1 staging .................................................................................. 69

Figure 6.22 Scenario 1 production profile .................................................................... 69





Figure 6.27 Open pit with underground stopes ............................................................. 72





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Figure 6.33 Cumulative undiscounted cash flow excluding capital ................................... 75

Figure 6.34 Cumulative discounted cash flow excluding capital ....................................... 75

Figure 7.1 Pit optimization results for run 1 MII 0.4 Mtpa ............................................ 80

Figure 7.2 Pit optimization results for run 1 MII 1.0 Mtpa ............................................ 80







Figure 8.1 Combined Krasny and Vostochny production profile ..................................... 85



Figure 8.4 Micon capital cost schedule ...................................................................... 87

Figure 8.5 Undiscounted cash flow including capital .................................................... 88

Figure 8.6 Discounted cash flow including capital ........................................................ 89

Figure 9.1 Land disturbance in Krasny stream valley ................................................... 94

Figure 9.2 Average annual wind rose ........................................................................ 95

Appendices

Appendix A Krasny pit optimization results

Appendix B Krasny preliminary financial mining models

Appendix C Vostochny preliminary financial models

Appendix D Combined Krasny and Vostochny cash flow analysis

Appendix E Memorandum: Krasny Scoping Study Mine production scenarios and key financial

outcomes

Distribution list

1 e-copy to Mikhail Damrin, CEO, Kopy Goldfields 1 e-copy to AMC Perth office

OFFICE USE ONLY

Version control

24 June 2019 1200


amcconsultants.com 1

1 Introduction


Project Scoping Study (the Study).

AMC understands that Krasny Project (the Project) is a joint venture between Kopy and open

joint-stock company (OJSC) GV Gold. However, AMC has been exclusively engaged by, take and

report to Kopy.

Kopy’s brief was to proceed with the Study based on a resource model prepared by others. The

Study includes a review of the proposed approach to mine development options for the Krasny Project, a preliminary review of the resource model and Mineral Resource estimate, and an



The review activities have also considered the economic viability of the Vostochny exploration area, with a preliminary review of resource model and an outline economic assessment of the


The Study includes:

• A brief review of the input assumptions to identify critical opportunities and threats in the

project. This includes review of the resource model and Mineral Resource estimate.

• Mine planning based on currently available information.

• Development of a strategic mine plan and simple financial model to explore possible

alternative scenarios.

• Recommendations for further work to improve the confidence in plans and estimates to

support estimation of Ore Reserve estimates.

The execution of the Study has been undertaken in separate discipline work packages and this

report reflects methodology, results and recommendation provided by each of the separate study

areas as follows:

• Mineral resource model review.

• Mineral processing review.

• Hydrogeology.

• Geotechnical.

• Krasny mining review.

• Exploration target – Vostochny.

• Environmental aspects.



2 Mineral resource model review

AMC has undertaken a high-level review of the Krasny resource model, together with the

supporting data provided, and has concluded that the model is suitable as a basis for mining

evaluation at the scoping level of study.

2.1 Data reviewed

AMC has undertaken a short review of the Krasny resource model and supporting data provided.

Of the information available to AMC, the review has focussed on work documented in Micon

(2018) which relates to the resource block model used in the scoping study. The following data

was selected by AMC for inclusion in the review:

• Drillhole database in Microsoft Access format (db_kra_2018_igt.mdb).

• Block model: Krasny (bm_krasn_upd.csv).

• Block model: Vostochny (bm_vost.csv).

• Mineralization wireframe solids: Krasny (krasn_all.dxf).

• Mineralization wireframe solids: Vostochny (vost_all.dxf).

• Oxidation wireframe surfaces: Oxidation_zones.tridb.

Micon (2018) has been the primary reference document (Krasny_Final_Report_ENG_signed.pdf)

used by AMC.

Tables of drillhole collars, downhole surveys, and assays for the period 2011 to 2018 were

extracted from the drillhole database and imported into the Datamine software package. In consideration of the low proportion of trench channel data relative to the drillhole data, the

trench data was not included in the short review.

2.2 Verification of reported tonnes and grades

Table 10.16 of Micon (2018) summarizes the Krasny estimated tonnes and grades, as at

1 January 2018, at cut-off grades ranging from 0.0 g/t Au through to 1.0 g/t Au. The table lists Indicated and Inferred categories separately. AMC has reported the contents of the block model

at the corresponding cut-off grades and categories and was able to match the Micon tonnes and grades figures exactly. The objective of AMC’s comparison was to verify that the model supplied

was consistent with that described in Micon (2018); however, AMC cautions that Table 10.16

tonnages and grades do not constitute the reported Krasny Mineral Resource.

2.3 Drilling adequacy

While AMC is not able to comment on the quality of drillhole sampling of Krasny deposit, AMC

notes that all drillhole are diamond core, and that the majority are HQ core size. Subject to core

recoveries AMC’s experience is that HQ diamond core typically return good sample volumes for

gold deposit evaluation.

The underlying drillhole section spacing is variable, typically ranging from 40 m to 80 m, with hole intervals on section of 40 m. However, within the main areas of mineralization interest the

spacing is reduced to 40 m by 20 m, and in places down to 20 m x 20 m or less. AMC considers the 40 m by 20 m grid to be suitable for scoping study assessment, but the appropriate spacing

for further feasibility evaluation will need to account for the local observed variabilities in

mineralization zone geometries and grade continuities.

2.4 Interpretation

Micon (2018) describes the interpretation of mineralized zones being “contoured using the cut-off grade of 0.4 g/t Au”, with adjustments made to capture suitable intervals of marginal samples

or isolated sample. AMC considers much of the resulting interpretation to be reasonable; however, AMC has noted a number of instances where the inclusion of unmineralized



intersections appears to be unnecessary and potentially allows the smearing of higher grades

into the associated model volumes during grade estimation.

The Krasny interpretation wireframe solids (Figure 2.1) present as relatively simple structures,

yet descriptions of the regional geology in Micon (2018) refer to complex faulting and folding at multiple levels. AMC cautions that the use of low-grade boundary cut-offs during the

interpretation may have oversimplified the geometries of the mineralization and that, at mining

scales, the local mineralization shapes may be considerably more complex.

Figure 2.1 Krasny: interpreted mineralizes zones

Source: Micon (2018)

AMC notes that about 15 holes are oriented towards 020, at inclinations that approximately

follow the dips of the mineralization. Drillholes that are inclined at low angles to, or follow the mineralization, are at risk of biasing block grades during estimation. Intersections of

mineralization in these holes may legitimately be used to define zone boundaries but should be excluded from the estimation sample set. Figure 2.2 shows an oblique view of the identified

Krasny drillholes with low intersection angles relative to the mineralization solids, and Figure 2.3

shows two specific examples in cross section.



Figure 2.2 Holes inclined down-dip: oblique

Figure 2.3 Holes inclined down-dip: cross section

Micon (2018) does to comment on whether any holes inclined down dip were excluded from

grade estimation. At scoping study level, AMC considers the bias risk to not be material, but recommends that for subsequent studies any holes that intersect the mineralization at low angles

should not be used for grade estimation.



2.5 Statistics and variography

Micon (2018) presents gold statistics for each of the four mineralized zones, further partitioned

by sampling method (core or trench channel).

Sample procedures and lower sample weights are common causes of poor channel sample quality, but no discussion is given Micon (2018) as to whether the trench channel samples were

assessed for suitability for grade estimation. Mineralization core samples are reported to average 4 kg, but no weights of channel samples are described for comparison. AMC recommends that

an independent evaluation of the channel samples, as well as comparisons with core samples, be undertaken to check both the quality of channel sampling and whether the two sample types

can justifiably be merged. AMC notes that the channel samples for the Upper Northern and

Southern zones return significantly higher mean gold grades than for the corresponding core samples. This may be associated with spatial differences but may also relate to differences in

sample quality and type.

Variographic analysis was used by Micon to determine estimation search ellipse dimensions. Only

one zone variogram example (Upper Southern) is presented in the document, and AMC considers the modelling of this variogram to have exaggerated the grade continuities. Consequently, the

selected search dimensions are optimistic.

2.6 Model construction

The block model received by AMC represents only those blocks within the interpreted

mineralization zones. Model blocks have been coded according to oxidation zone, however no

codes are available to differentiate between the four separately defined mineralized zones.

Model block dimensions are a regular 5 m x 5 m x 5m. AMC considers these block dimensions to only be reasonable in the areas with drilling densities of 20 m x 20 m or less. At lower drilling

densities the risks of estimation bias as a consequence of the small blocks increase. AMC recommends that larger estimation blocks be used for future models, with appropriate sub-

blocking to represent zone boundary geometries.

2.7 Density assignment

The Micon (2018) report states that an “average value of bulk density equal to 2.68 t/m3 has

been adopted for the purpose of the resource and reserve calculations”. AMC has confirmed this single value in the block model. Micon further reports that “bulk density ranges from 1.48 t/m3

to 3.53 t/m3 [3,099 measurements]”, and that “the rocks of the deposit and the mineral occurrence typically have an inconsistent density resulting from the variability of their

petrographic and mineral composition, secondary alteration, presence or absence of ore

mineralization, etc.”

No further data or commentary is provided by Micon to demonstrate the statistical or spatial distributions of the bulk density data, yet the deposit has been subject to significant oxidation,

and “the lower boundary of the oxide ores are located around 20 m to 100 m from the surface”

(Micon, 2018). Three oxidation zones (oxide, transition, and fresh) have been coded into the model, therefore AMC sought to establish whether there is a significant relationship between

oxidation zone and bulk density.

AMC coded the bulk density data table by oxidation zone using the wireframe surfaces provided.

Basic density statistics subset by oxidation zone, as shown in Table 2.1,reveal that the transition and fresh zones have very similar density characteristics, but the oxide zone has a slightly lower

mean value (about 4% lower).



Table 2.1 Bulk density statistics by oxidation zone (t/m3)

Oxidation Zone

Oxide Transition Fresh

Count 709 509 1881

Min 1.63 1.48 1.22

Max 3.70 3.53 3.53

Mean 2.58 2.66 2.68

The charts shown in Figure 2.4 confirm the slight downward shift of density values in the oxide

zone. However, the magnitude of shift is not considered material at the scoping study level, therefore AMC considers the application in the block model of a blanket bulk density value of

2.68 t/m3 to be slightly high, but not unreasonable.



Figure 2.4 Krasny bulk density distributions by oxidation zone

2.8 Grade estimation

AMC considers the method of determining high grade capping (top cuts), as documented in Micon

(2018) to be simplistic. Specifically, the rudimentary use of cumulative frequency charts is

inadequate for establishing capping thresholds, because the charts do not give the necessary spatial insight into the potential effects of high grades during estimation. AMC recommends that

statistical charts should only serve as one source of information in the capping decision process.



Further, the application of a single high-grade cap across all four identified mineralized zones

fails to recognize that the statistics for the individual zones demonstrate significantly different

zonal grade distribution characteristics.

AMC’s review scope does not provide for independent check of the capping strategy. However, AMC conducted a brief visual assessment of the spatial locations of gold assays above 19 g/t Au

(the global drillhole top cut applied was 19.23 g/t Au).

Figure 2.5 shows an oblique 3D view of a sub area of samples greater than 5 g/t Au. Samples

coloured red are above 19 g/t Au, green between 10 g/t Au and 19 g/t Au, and blue below 10 g/t Au. Risks of undue high-grade influence during estimation will be higher where the high

grades are isolated from other higher grades (nuggety). AMC notes some degree of clustering

of the Krasny high grades, but in detail they are frequently isolated. AMC has further reviewed block estimated grades against high grade samples. Notwithstanding the limited high-grade

clustering, concludes that the capping values applied by Micon have reasonably minimized any undue high-grade influence. However, for future studies AMC recommends as assessment of

high-grade caps that takes into account the spatial characteristics of grades.

Figure 2.5 Spatial distribution of potential outlier grades

Inverse distance weighting squared interpolation has been applied for gold grade estimation at Krasny. Micon (2018) does not explain why ordinary kriging was not selected for estimation.

AMC advises that for future studies, a more comprehensive variographic analysis be undertaken

with the objective of utilising a kriging estimator.

The estimation search ellipse orientations are set as single values for each mineralized zone. For

the current stage of study and, given the relative consistencies of strikes and dips for each zone, AMC considers search ellipse strategy to be reasonable. However, AMC has noted cases where

the intended search orientations appear not to have been properly applied.

Figure 2.6 is an example of search orientation misalignment, showing a cross-section slice

through the Upper Southern zone. The documented search orientation for this zone is -83°, being a down-dip alignment. However, the trend in estimated grades in Figure 2.6 suggests an

actual orientation closer to -35°. AMC notes that this degree of misalignment appears to be

localized, and that the impacts on the model will not be material to the study. Nonetheless, AMC recommends that a more sophisticated search orientation strategy be introduced for future

studies.



Figure 2.6 Misaligned search orientation: upper southern zone

2.9 Resource classification

The Krasny Mineral Resources have been classified as either Indicated or Inferred. The division

between Indicated and Inferred volumes has been set by Micon according to whether the drill spacing is less than (Indicated) or more than (Inferred) an approximate 40 m to 50 m square

grid. AMC is not able to endorse these classifications but can offer a view as to whether they

appear reasonable.

The simple approach adopted by Micon does not consider variations in geometric or grade continuities across the deposit, but for the current level of study is reasonable. In places the

Indicated areas are supported by only relatively sparse drilling, but overall the assignment has

been appropriately restrained.

Some of the Inferred mineralization, however, has very little drill support, specifically the Lower

Western units. Many of the drill intersection in this unit are more than 150 m apart, and some sections have only a single drillhole. For the Krasny style of mineralization AMC considers this

level of drilling information to be inadequate for Inferred classification. AMC suggests that the Lower Western zone be re-evaluated for potential demotion to “unclassified”, pending further

definition work. For the purposes of the current study, however, the Lower Western

mineralization is not considered material.



2.10 Krasny mineral resource opportunities

The following opportunities for improvement in the evaluation of Krasny mineral resources have

been identified by AMC to augment recommendations already set out in this review report.

Interpretation

Micon describes the Krasny interpretation as consisting of four identified zones, made up of 12

individual solid wireframes. The different zones have similar strikes and are mainly separated by poorly mineralized gaps or on the basis of different dips. However, no underlying structural

framework is described.

AMC has observed a possible relationship between some of the Krasny zones that may provide

such a framework for improved interpretations.

Figure 2.7 shows an east-facing cross-section of the Micon interpretation shapes. The left-hand panel has the interpretation outline superimposed over a window of drillhole grades, with values

below 0.5 g/t Au filtered out, and with higher grades scaled for exaggeration. The right-hand panel is the same section but with no window restriction on the visible samples. The right-hand

panel image is strongly suggestive of an antiformal fold hinge, and a faulted offset of the lower limb. AMC suggests that this structural framework be further investigated and, if substantiated,

it can be used to refine the interpretations.

Figure 2.7 Krasny: Apparent fold-fault structural setting: view to east

AMC has further observed a potential plunge orientation not described by Micon, as illustrated in Figure 2.8. If the plunge orientation can be confirmed, then this provides an opportunity for

potentially improving variogram quality, and also for a refinement of grade estimation.



Figure 2.8 Potential plunge orientation of gold grades

Estimation method

Further to AMC’s recommendation that a robust kriging estimation strategy should be introduced

to replace the inverse distance method applied at Krasny, AMC considers the Krasny spatial

distribution of gold to be particularly suited to non-linear methods of estimation. Linear techniques such as ordinary kriging, when applied to estimation panels (blocks) in the Krasny

style of mineralization are at risk of over-smoothing the estimates relative to the gold distribution evident from the drillhole assays. In these circumstances AMC recommends the appropriate use

of non-linear techniques, such as multiple indicator kriging (MIK). By applying a localized version of MIK (LMIK) the benefits of robust MIK estimates can be realized, but the estimates are

presented as single gold grade values within selective mining unit-sized blocks, rather than as

grade distributions within panels, as generated by conventional MIK.



3 Mineral processing review

The Study investigated processing options for ore from the Project consisting of the Krasny

deposit and the Vostochny mineral occurrence. In August 2018, Micon International Limited (Micon) reviewed all testwork and studies to date in a document entitled “Mineral Resources and

Ore Reserves Estimate of the Krasny Gold Deposit and the Vostochny Mineral Occurrence,

Irkutsk Region, Russian Federation”. The following metallurgical testing programs have been

conducted and reported:

• Studies of composition and processing properties of ore from the lower mineralized zone

of the Krasny Deposit; OJSC Irgiredmet, Irkutsk, 2012.

• Development of technology of processing ore deposits “Red” with delivery of production

schedules; OJSC Irgiredmet, Irkutsk, 2015.

• Technological mapping of ores for Project Red; OJSC Irgiredmet, Irkutsk, 2016.

• Studies of composition and processing properties of ore from the Vostochny Mineral

Occurrence; OJSC TOMS, Irkutsk, 2018.

• Technical – Economic comparison of two mining scenarios (open pit and open

pit/underground combined) for Krasny Deposit; OJSC TOMS, Irkutsk, 2017.

• Study of Material Composition and Technological Properties of Vostochny ore; OJSC TOMS,

Irkutsk, 2018.

The ore is characterized as a low-sulphide gold-quartz type. Samples that were tested were composed of quartz sandstones, siltstones and shales. An oxidation zone extending down 20 m

to 100 m from surface is present in the deposit. Samples referred to as “primary”, “transitional”, and “oxide” were tested. Gold predominantly occurs in association with pyrite in primary ore and

iron hydroxides in the oxide zone. Oxide ore is considered to be free milling, with 91% cyanide-

leachable, while primary ore is deemed refractory with 85% able to be placed in solution by

cyanide.

Preg-robbing carbon (organic carbon) was analysed in the samples that were tested. Reporting at 0.4% to 0.8% in oxide ore, 1.2% to 2.8% in primary ore, and 4% to 5% in flotation

concentrate were reported.

Testing programs examined physical and mineralogical characteristics of samples of the ore, and

tested the following processing methods:

• Heap leaching.


• De-sliming.

• Flotation.

• Cyanide leaching.

Micon recommended a gravity-flotation-CIL flowsheet which is typically used to process gold

ores of this type.

3.1 Samples

Samples that were selected for testing are shown in Table 3.1. A primary sample was tested at laboratory scale for preliminary responses in 2012. The tests were conducted by OJSC Irgiredmet

(Irgiredmet) in Irkutsk.

Oxide and primary samples were laboratory tested by Irgiredmet in 2015 and 2016 (TP-1, TP-

2, TP-3) and a basic processing approach was selected.

In 2016, Irgiredmet received 545 core samples that had been collected and visually logged. Oxidation level was assessed. 43 composites were created to represent primary, transition, and

oxide zones of the orebody; based on the initial assays and logging. Oxidation level (%) was



calculated from Fe and S assays to express the relationship between Fe2+ to Fe3+. Three

categories of ore were designated on the basis of degree of oxidation of iron to Fe3+:



• Oxide ore >90%.

Six metallurgical composites (TK-1 to TK-6) were created from the 43 composites for variability testing (mapping exercise). The metallurgical composites represented the basic ore types from

various locations. Testing was conducted in 2016.

In 2016, a composite sample from the central part of the Vostochny mineral occurrence was

tested at OJSC TOMS (TOMS). Findings were reported in 2018.

In 2017, a master composite sample (TP-4) of approximately 3,000 kg was processed in a pilot plant simulating the preferred circuit arrangement. The master composite was created to

simulate the average blend of ROM ore and was comprised of primary ore (45.2%), transition

ore (23.4%), and oxide ore (31.4%).

Table 3.1 Samples for metallurgical testing

Sample I.D. Year Ore Type Sample Type Gold Content

(g/t)

Sample No.1 2012 Primary Laboratory 2.50

TP-1 2015 Oxide Laboratory 2.02

TP-2 2015 Primary Laboratory 2.14

TP-3 2016 Oxide Laboratory 1.74

TP-4 2017 Master Composite Pilot-scale 1.92

TK-1 2016 Primary Variability 0.94

TK-2 2016 Transition Variability 1.32

TK-3 2016 Oxide Variability 1.16

TK-4 2016 Oxide Variability 0.81



Vostochny 2016 Composite Laboratory 1.45

3.2 Test results

3.2.1 Primary testing – Irgiredmet, 2012

The sample tested was identified as originating from ore zone 2. It was characterized by

Irgiredmet as primary ore with an oxidation level of 16%. Irgiredmet identified gold (Au) as being relatively coarse and as being associated with pyrite. No significant levels of deleterious

elements were detected, with arsenic (As) measures at 0.014%.

Organic carbon (Corg) at 0.7% was identified as a potential problem due to preg-robbing during

cyanidation.

Application of a conventional processing approach for ores from the region (gravity-flotation-

cyanidation of flotation concentrate) was anticipated and testing was focused on this approach.

Detailed screening and development of metallurgical parameters was performed. Using these optimized parameters, overall Au recovery of 92.82% was reported; comprised of 82.6% by

gravity and 10.22% by flotation. The portion of 73.3% of Au in flotation concentrate was recovered by cyanidation. The low recovery of Au from solution was noted and the presence of

preg-robbing carbon cited as the likely cause.



Pressure oxidation tests were also conducted on flotation concentrate where 85.4% of Au was

extracted. Further experimentation was recommended to verify whether the increased Au

extraction can justify increased capex and opex for pressure oxidation.

3.2.2 Primary, oxide testing – Irgiredmet, 2015

Preliminary screening of oxide (TP-1 in Table 3.1) and primary sample (TP-2 in Table 3.1) for

response using some typical separation techniques was conducted by Irgiredmet in 2015. Basic

comminution characteristics were also examined.

Primary ore was noted to be generally harder and more abrasive than oxide ore. The following

physical and ore hardness parameters were noted for primary ore:

• Protodiakonov strength Class IV (hard).



• Bond ball mill work index (BWi) 11.46 kWh/t to 15.54 kWh/t (medium hard to hard).


The following concentration techniques were examined:

• Particle sorting by X-ray radiometric analysis.

⎯ Proved to be unsuccessful with no appreciable concentration of Au produced.

⎯ No further testing undertaken.

• Heap leaching.

⎯ Oxide sample (TP-1) 24% Au recovered.

⎯ Primary sample (TP-2) 7.5% Au recovered.

⎯ No further testing undertaken.

• Gravity concentration.

⎯ Potential for significant recovery of Au by gravity was established in the 2012 testing.

⎯ Laboratory-scale jigs and shaking tables recovered the following Au.

- Oxide 44%.

- Primary 86%.

⎯ Standard gravity recoverable gold (GRG) testing estimated GRG to be 73.5% for all

tests at an optimal feed size of 160 µm.

⎯ This gravity recoverable gold (GRG) recovery is typical for gold ores of the region

and encouraged researchers to pursue gravity separation as part of the final

recommended circuit.

⎯ Final testing following development and refinement of procedures produced the following recoveries that were used in subsequent estimates of recommended circuit

performance:

- Oxide 60.3%.

- Primary 88.0% (gravity cons73.6%, gravity mids14.4%).

• Flotation.

⎯ A standard arrangement of flotation of gravity tailings was tested.

⎯ Carbon removal by flotation.

- Removal of preg-robbing carbon by flotation is widely practiced avoiding the loss

of Au from leach solution by adsorption on fine, organic carbon particles from the

ore which cannot be recovered by screening in the CIL process.

- Carbon pre-float returned the following results:

- Oxide – 19.6% Corg recovered, carrying 7% of the Au

- Primary – 21.8% Corg recovered, carrying 2.4% of the Au



- Pre-flotation for carbon removal was not recommended due to the poor efficiency

of carbon removal.

⎯ De-sliming.

- In some instances, Corg is concentrated in ultra-fine slimes fractions during crushing and grinding. Removal of slimes from flotation concentrate; usually by

hydrocycloning, may sufficiently reduce the amount of Corg reporting to the CIL circuit (and the Au lost by preg-robbing) to compensate for the Au lost in the

discarded slimes fraction of flotation concentrate.

- De-sliming returned the following results:

- Oxide – 20.5% Corg removed, carrying 13.8% of the Au.

- Primary – 22.3% Corg removed, carrying 3.1% of the Au.

- De-sliming was included in the recommended circuit as a method of removal of

preg-robbing carbon.

⎯ Oxide flotation.

- Standard xanthate flotation with regrinding to a medium P80 size of 75 µm

returned the following results.

- Flotation Au recovery 20.4%.

- Gravity + flotation recovery 80.7%.

- Organic carbon recovered 43.7%.

⎯ Primary flotation

- The same flotation arrangement was tested for the primary sample.

- The following results were obtained:

- Flotation Au recovery 70.7%.

- Gravity + flotation recovery 91.4%.

- Organic carbon recovered 27.8%.

• Cyanide leaching was also evaluated for use in addition to the primary leaching of gravity

and flotation concentrates. The following investigations were reported:

⎯ Direct leaching of tailings following Au recovery by gravity.

- Oxide ore 63.4% Au recovery was achieved.

- Primary ore 63.6% Au recovery.

⎯ Intensive cyanide leaching of concentrate from gravity separation. This is the typical processing route for extraction of Au from gravity concentrate as it permits Au from

this source to join a common stream for recovery from solution. In addition, it improves security by removing Au from a coarse, easily misappropriated intermediate

product. The following results were obtained:

- Oxide ore 99.3% Au recovery from gravity concentrate.

- Primary ore 99.2% Au recovery from gravity concentrate.

- Primary ore 96.1% Au recovery from intermediate gravity concentrate.

3.2.3 Oxide testing – Irgiredmet recommended flowsheet, 2016

In 2016, Irgiredmet tested an Oxide ore sample (TP-3) using a flowsheet developed from the

results of their 2015 testwork. The basic flowsheet was configured as follows:


• Flotation of gravity tailings.

• Intensive cyanidation of de-slimed gravity concentrate followed by carbon in leach (CIL)

to recover Au from solution.

• Cyanide leaching of flotation concentrate, followed by CIL to recover Au from solution.

A combined Au recovery of 90% into the two concentrates was achieved.



Au recoveries from gravity concentrate by intensive cyanidation of 99.03% and 98.30% were

achieved. Au recoveries from de-slimed flotation concentrate by cyanide leaching ranged from

87.28% to 90.23%.

Overall recoveries from this circuit arrangement were estimated to range from 78.0% to 79.1%. Irgiredmet asserted that these results confirmed that the proposed circuit arrangement could be

used to treat both oxide and primary ores.

3.2.4 Variability testing – Irgiredmet, 2016

A variability series of tests (referred to as “Technological mapping”) were conducted on six composite samples (TK-1 to TK-6). Table 3.1 and Table 3.2 show the variability samples. TK-1

with an oxidation level of 21% is termed Primary as discussed in 3.1. TK-2 and TK-5 are classed

as Transition while TK-3, TK-4, and TK-6 are classed as Oxide.

Oxide samples showed somewhat lower gravity recoveries and markedly lower flotation

recoveries as would be expected. Transition and Primary samples returned overall recoveries ranging from 84.8% to 92.5%, although no clear correlation between oxidation level and overall

recovery is evident.

Table 3.2 Gold recovery by gravity and flotation – variable oxidation levels

Sample

I.D.

Gold

Content

(g/t)

Oxidation

Level

(%)

Ore Type Corg

(%)

Recovery to

Gravity

Concentrate

(%)

Recovery to

Flotation

Concentrate

(%)

Recovery

Overall

(%)

TK-1 0.94 21 Primary 0.94 72.6 12.2 84.8

TK-2 1.32 49 Transition 1.32 77.5 15.0 92.5

TK-3 1.16 98 Oxide 1.16 60.2 4.0 64.2

TK-4 0.81 97 Oxide 0.81 76.0 4.7 80.7

TK-5 1.18 69 Transition 1.18 83.1 9.1 92.2

TK-6 0.97 99 Oxide 0.97 70.2 7.2 77.4

Preg robbing was analysed during cyanide leaching trials. Relative preg-robbing values from

9.13% to 54.23% were calculated, confirming earlier observations that significant losses will be

suffered if no control measures are taken.

3.2.5 Vostochny testing – TOMS, 2016

Vostochny ore is characterized in all reports as geologically similar to Krasny ore, and the

expectation is that metallurgical response will also be basically similar. It contains gold-quartz, low-sulphide mineralization with the predominant sulphide being pyrite. The orebody contains

an upper oxidized zone as at Krasny.

OJSC Tomskneft in Irkutsk conducting testing on Vostochny ore. “Study of Material Composition and Technological Properties of Vostochny ore; OJSC TOMS, Irkutsk, 2018” reported on the

work. A bulk sample of Vostochny ore was used for the testing. The sample weighed 459 kg and was comprised of drill core obtained in 2016. The sample was designated Vostochny TP-No.5

(VTP-5). The provenance of the core and the rationale for selection of material for VTP-5 were

not discussed in the TOMS report.

The sample contained 1.48% Au and Corg of 0.54%. An Oxidation Level of 89% was calculated, indicating a transition-oxide response might be expected. A bond ball mill work index test was

conducted; yielding a BWi of 13.18 kWh/t which is in the Krasny range.



Basic gravity separation and flotation testing at bench scale and pilot scale confirmed similar

performance to Krasny ore. The following extractions were obtained from the pilot-scale test:

• Gravity extraction 73.82%.

• Flotation (of gravity tails) 16.61%.

• Overall extraction 90.43%.

3.2.6 Pilot-scale testing – Irgiredmet, 2017

A master composite sample (TP-4) was tested at pilot scale in 2017 using the basic gravity-

flotation circuit arrangement developed in Irgiredmet’s earlier work (see section 3.1). Testing of 3,000 kg of sample was conducted at 40 kg/hr. The plant feed averaged a gold head grade of

1.6 g/t (measured) and 1.9 g/t (calculated). The ore would be characterized as transition with

an oxidation level of 61%. The following processing steps were used:

• Gravity separation – producing concentrate, middlings, and tailings.

• Regrinding of gravity middlings.

• Intensive cyanidation (ICL) of gravity concentrate and reground gravity middlings.

• Flotation of gravity tailings.

• Cyanide leaching and CIL of flotation concentrate (flot con), reground gravity middlings

(grav mids) and pregnant leach solution from ICL (ICL soln) to recovery gold from solution.

Organic carbon depression in the flotation stage was selected to reduce the presence of preg-

robbing carbon in leach solutions. A reduction from 4.22% to 1.27% was achieved.

The following results were obtained for the test:

• Gravity extraction 70.4%.

⎯ Au recovery by intensive cyanidation 94%.

• Flotation recovery 20.6%.

⎯ Au recovery by CIL 98%.

• Cyanide leaching and CIL – flot con, gravity mids, ICL soln 98.9% (lab-scale test).

Overall, the calculated Au recovery of the pilot-scale test using the Irgiredmet arrangement was

88.5%.

Testing of unit processes required for the circuit confirmed the applicability of standard practices

for the industry, such as:

• Counter-current decantation arrangement in the CIL circuit.

• Industry-standard activated carbon management.

• Thickener (with flocculation) for flotation tailings preparation.

• Thickening (with flocculation) and filtration of leaching residue.

3.3 Irgiredmet recommended circuit

Figure 3.1 shows the basic gravity / flotation flowsheet recommended by Irgiredmet on the basis of their testwork. It was used in the processing schedule submitted for the project. The flowsheet

contains the following circuits:

• Semi-autogenous (SAG) milling.

⎯ 1.0 Mtpa nominal feed rate.

⎯ -400 mm feed size.

⎯ Initial gravity separation using jigging (Jigging-1 in Figure 3.1).

⎯ Jigging concentrate is further upgraded using shaking tables, with middling streams

reground to an 80% passing size (P80) of 71 µm and retreated using shaking tables.

⎯ Concentrate reports to intensive cyanidation (cone leach reactor, by Irgiredmet), with

solution sent to the CIL circuit for gold recovery.



⎯ Jigging tails undergoes two-stage classification by hydrocyclone:

- Underflow-1 is returned to the SAG mill.

- Overflow-1 is re-classified.

- Underflow-2 is reground and treated by two-stage gravity (jigging, shaking table), then cyclone, with all tailings recirculated for further grinding and

concentrate reporting to the shaking tables ahead of intensive cyanidation.

- Overflow-2 reports to flotation.

⎯ Flotation using an organic carbon depressant to control preg-robbing by reducing recovery of organic carbon to flotation concentrate was specified. The recommended

circuit consists of:

- Rougher-1.

- Rougher-2.

- Rougher-scavenger.

- Cleaner-1.

- Cleaner-2.

- Middlings.

⎯ CIL circuit consists of:

- Thickener and lime conditioning (pH control) for flotation concentrate.

- CIL leaching using counter-current decantation tanks.

- Elution and electrowinning to recover Au from solution.

- Smelting and casting to produce Au-Ag doré bars.

- Detoxification circuit to reduce CN- concentration below legal limit.



Figure 3.1 Irgiredmet flowsheet

Irgiredmet forecast an overall Au recovery of 85.5%, from a feed grade of 1.54 g/t Au, using an adjustment factor based on the expected head grade (rather than the grade measured in the

test work). The following intermediate recoveries were estimated:







3.4 Micon review and recommendations

As part of a review by Micon International Co Limited (Micon) of mineral resources and ore reserves for the Krasny gold deposit and the Vostochny mineral occurrence, a review of all

metallurgical test work was conducted (Mineral Resources and Ore Reserves Estimate of the Krasny Gold Deposit and the Vostochny Mineral Occurrence, Irkutsk Region, Russian Federation,

Micon International Co Limited, 30 August 2018. After their review, Micon concluded the

following:

• While the gold occurrence at Krasny is relatively fine with 66.5% at -70 µm, recovery of 68.4% of gold in the feed to the gravity concentrate (gravity concentrate plus gravity

middlings) was possible using jigging and shaking tables.

• The gravity circuit recommended by Irgiredmet was quite complex and it relied on multiple units of older-generation technology; that is, jigging and shaking tables. Micon

recommended the circuit arrangement shown in Figure 3.2 where single-stage gravity separation using modern, centrifugal separators (such as Falcon, or Knelson) will deliver

superior performance with pre-screening at 1.0 mm and regrinding of +1.0 mm material.

• Micon recommended a simplified flotation arrangement of rougher, scavenger, and single-

stage cleaner to produce final concentrate, with no regrinding of recirculating streams.

• Micon noted the use of a similar circuit to successfully treat ore at the Pavlik Mine, Magadan

Region, Russian Federation. Pavlik ore also contains preg-robbing, organic carbon and has

a large component of fine-sized gold which Micon state is successfully recovered using

Knelson centrifugal separators.

Micon support the average recovery estimation of 85.5% from an average feed grade of 1.54 g/t Au that was made by Irgiredmet and recommend the use of a simplified flowsheet as

shown in Figure 3.2 below.



Figure 3.2 Recommended processing flowsheet (Micon, Aug 2018)

3.5 AMC review and comments

3.5.1 Sample selection

A discussed in section 3.1, sample selection for metallurgical testing was based primarily on degree of oxidation; as characterized by oxidation level. This percentage value was calculated

using iron assays, and it expressed the ration of iron fully oxidized to the Fe3+ state. Three ore

types were defined using oxidation level:



• Oxide ore >90%.

Samples of drill core were selected and composited to provide material for testing that

represented the three ore types.

While this approach yielded data on metallurgical performance for each ore type, AMC notes that samples were not chosen and tested to examine locational variability throughout the orebody.

This applies to comminution characteristics, gold recoverability, and presence of preg-robbing



carbon. AMC recommends performance of a full geometallurgical examination to model

metallurgical parameters during the next phase of study.

3.5.2 Test work conducted

Experience with a range of similar gold ores from the Irkutsk region and elsewhere in Russia led Irgiredmet to anticipate good metallurgical responses from SAG milling, gravity separation and

flotation of gravity tailings. Preliminary scoping tests were undertaken to investigate other approaches such as pressure oxidation, x-ray radiometric ore sorting and heap leaching,

however results were not positive, and the basic gravity-flotation combination was carried

forward.

Preg-robbing organic carbon in the ore was identified as a potential source of significant gold

loss. Pre-floating of organic carbon and discarding of the concentrate is often used to remove the gold-robbing fine particles prior to the CIL circuit. Irgiredmet did not recommend this

approach on the basis of high gold losses experienced in early test results. Also, not recommended was de-sliming of flotation concentrate by hydrocyclone classification which can

be economically viable if preg-robbing organic carbon is preferentially present in the ultrafine fraction, and the gold loss in the discarded ultrafines is less than the gold loss in the escaping

organic carbon when ultrafines are not removed. Both conclusions should be rechecked during

the next phase of study.

Use of organic carbon depression was evaluated and found to effectively reduce the organic

carbon concentration in flotation concentrate (and hence in the CIL circuit). Detailed tests to

evaluate reagents and optimize dosage should be conducted.

Irgiredmet forecast an overall Au recovery of 85.5%, from a feed grade of 1.54 g/t Au, with the

following intermediate recoveries:





Micon used the three ore types (Primary, Transition, Oxide) in their financial model of the Krasny

project, estimating overall gold recovery as follows:

• Primary 88.5%.

⎯ No direct basis for use of the TP-4 test result which was obtained from a blend of the

three ore types.

⎯ However, Primary ore tests produced recoveries ranging from 84.8% to 92.8%, so

the use of this estimation is not unreasonable.

• Transition 87.8%

⎯ Based on the pilot-scale test conducted in 2017 using a bulk composite (TP-4) with

a head grade of 1.6 g/t Au measured (1.9 g/t Au calculated) and Oxidation Level of

61%. Au recovery of 88.5% was estimated.

⎯ Transition ore tested during the Mapping series (TK-2 and TK-5) produced good

recoveries similar to those achieved with Primary ore.

⎯ This estimate is adequate for this stage of the project.

• Oxide 77.5%.

⎯ Based primarily on 2016 testing of the recommended flowsheet using the TP-3 Oxide

sample.

⎯ Testing of Oxide ore during the Mapping series (TK-1 to TK-6) produced variable

results (64.2% to 80.7%).



Use of a modelled estimation of gold recovery based on degree of oxidation would improve the

reliability of gold recovery estimation. As discussed previously, a geometallurgical study could

provide data to develop such a relationship.

The Micon financial model, 2018, shows an average head grade for the project of 1.089 g/t Au and a gold recovery of 83.9%. The recoveries used are consistent with the testwork completed

on the three ore types. AMC recommends more work to be done to quantify locational variability,

and to establish a reliable relationship between degree of oxidation and gold recovery.

3.5.3 Flowsheet design

AMC is generally aligned with the flowsheet design with the Micon-recommended changes

incorporated.

The comminution circuit appears to be designed on the basis of tests using a single Primary ore sample (Sample No.1). Primary ore was stated to be generally harder and more abrasive than

Oxide ore, so testing of only Primary material was deemed sufficient. The following physical and

ore hardness parameters were determined:

• Protodiakonov Strength Class IV (hard)



• Bond ball mill work index (BWi) 11.46 kWh/t to 15.54 kWh/t (medium-hard to hard).


As observed by Irgiredmet and Micon, Krasny ore can be characterized as medium-hard to hard and quite abrasive. A sample of Vostochny Transition ore was also tested, returning a BWi of

13.18 kWh/t which is consistent with Krasny material.

AMC recommends that the following additional testing be conducted:

• Testing specific to the use of SAG milling which is a central part of the flowsheet.

• Testing of oxide and transition material to confirm plant operating ranges when treating

different materials.

• Testing to quantify locational variability of ore across the life of the project.

The simplified gravity-flotation circuit recommended by Micon has several significant

advantages:

• High efficiency centrifugal separators give the best opportunity to maximize gold collection

early in processing which increases recovery.

• Feed is not over-ground prior to gravity separation, limiting the opportunities for over-

grinding and loss of gold to the unrecoverable, ultra-fine fraction.

• The simplified flotation circuit requires less capital and is easier to run and maintain which

leads to increased recovery.

AMC recommends confirmation with testwork that the regrinding is not required in the flotation

circuit.



4 Hydrogeology

4.1 Introduction

The following sections presents a review of hydrology reports to assess dewatering requirements and potential for surface and ground water to impact upon the Project slope stability and mining

operations.

4.2 Information sources

Kopy provided the following documents for this review (Table 4.1).

Table 4.1 Supplied information sources

Origin Title Date Reference

Kopy Отчет гидрогеология 2016-HydrologyREport2016 10-Jan-15 Kopy 2016

Kopy Отчет гидрогеология 2018-HydrologyReport2018 12-Sep-18 Kopy 2018

The Krasny gold deposit is part of the Artemovsk ore cluster and is located within the Bodaibo

district of the Irkutsk region, some 80 km north of the regional center of the village Bodaybo

(Figure 4.1).

The ‘hydrology’ studies undertaken describe the hydrogeological conditions of the Artemovsk ore

cluster and include assessment of potential inflows to the Krasny gold deposit.

Figure 4.1 Overview map of the area of work. Scale 1: 250,000 (Отчет гидрогеология 2016-

HydrologyREport2016, Kopy)



4.3 Hydrogeology overview

The climate of the region is sharply continental. The average annual air temperature is 6° С. Fluctuations in average temperatures from -54°С in January and up to +34°С in July. The

average annual rainfall is 350 mm, most of which falls in summer. Snow falls in mid or late

September and melts completely in late June. Snow cover in valleys reaches 2 m to 4 m.

The project area is intersected by the Bodaibo and Vitim Rivers, and a network of small streams

that almost completely freeze in winter.

Hydrogeological conditions of the region are largely determined by permafrost occurrence. However, Kopy (2016) conclude that permafrost was not present near the proposed project and

would have no influence on hydrogeological or geotechnical conditions relevant to its

development. The basis for this conclusion is not stated but assumed to be accurate for the

purposes of this review.

In the vicinity of the project, two primary aquifers have been identified:

• Quaternary alluvial aquifer.

• Fractured rock aquifer of the Upper Proterozoic metamorphic and intrusive rocks.

The alluvial aquifer of the river valleys typically does not freeze at any part of the year and

recharge occurs during the spring and summer floods.

Groundwater recharge areas of the Fractured rock aquifer occur where the host rocks reach the

surface (Kopy, 2016).

The fractured rock aquifer is represented by phyllite, quartz sandstones, siltstone, quartzite, metasandstones, sericite-quartz, quartz-sericite, carbonaceous and aleurite schists and is

characterized by variable annual level fluctuations.

4.4 Hydrogeological works completed

Hydrogeological and analytical studies, statistical and other calculations were undertaken in 2014 to 2015 to assess the hydrogeological conditions of the Krasny deposit development up to

the designed pit depth of 150 m. Further studies, completed in 2018, expanded on the previous

programme and included drilling of a test bore to 400 m depth.

4.4.1 Test wells

In 2014 to 2015, four hydrogeological wells were constructed to depths of 160 m to 200 m and two observational gauging stations were established within the planned pit boundary

(Figure 4.2).



Figure 4.2 Test well locations (Kopy, 2016)

Pumping Tests undertaken in completed wells to assess hydrogeological parameters in the

alluvial and fractured rock aquifers are summarized on Table 4.2.



Table 4.2 Test pumping summary (Kopy, 2016)

Number Depth (m)

Testing Interval

(m)

Geological Index

Features Lithology Static Level (m)

Debit (l/s)

Decrease or Increase

(m)

Specific Flow Rate (l/s * m)

Water conductivity

(Km) m2 / day

Coefficient Filtration

(K), m / day

Level Conductivity (a), m2 / day

1 2 3 4 5 6 7 8 9 10 11 12

Trial single FEM:

Pouring:

141626 4,5 0-4,5 Q4 Crushed stone and loam 4,35 0,364 0,99 0,3677 – 15,1 –

141667 5 0-5 Q4 Crushed stone and loam 6,55 0,43 2,75 0,1564 21,9 7,96 –

141623 8 0-8 Q4 Crushed stone and loam 4,45 0,299 1,97 0,1518 10,9 1,98 –

141667 100 5-100 R3vc2 Slates, aleuroplanes and metasandstones

74,22 0,294 3,27 0,0899 8,08 0,28 –


74,22 0,295 2,21 0,1335 11,0 0,38 –

Откачки:

141626 100 4,5-100 R3vc2 Slates, aleuroplanes and metasandstones

23,9 0,509 1,78 0,2860 42,4 0,56 –


23,9 0,502 6,40 0,078 5,28 0,053 –

141623 160 8-160 R3vc2 Alevroslantsy and Meta sandstones

97,77 0,284 8,42 0,0337 2,97 0,043 –

Spray pumping:


105,42 2,842 2,51 1,13 47,5 0,64 –

141623 160 0-160 97,13 – 0,33 – – – –

141667 160 0-160 95,66 – 0,85 – 47,5 0,64 2,39*103

Source: Отчет гидрогеология 2016-HydrologyREport2016



Interpretation of pumping tests was by Jacob's1 graphical-analytical method, which is a

simplification of the Theis2 formula:

where:

s = drawdown measured in a monitoring well (m) Q = discharge from pumping well (constant) (m3/d)

KD = transmissivity of the aquifer (m2/d) r = distance between the monitoring well and pumping well (m)

S = storativity of the aquifer (dimensionless)

t = time since pumping started (days)

The uppermost quaternary alluvial aquifer is characterized by a permeability of 2 m to 15 m/day.

Kopy, 2016, indicate its effect on the water inflow into the pit is insignificant, likely due to the

limited saturation of this aquifer.

The lower part of the fractured aquifer zone, which determines the flow of groundwater into the open pit, is characteristically heterogeneous. The calculated average hydraulic conductivity is in

the range 0.043 m to 0.64 m/day.

The 2018 programme included drilling of two additional bores GG-1 and IG-3 to 400 m and

250 m depth respectively. Test pumping of these deeper bores suggested a hydraulic

conductivity of approximately 0.06 m/day.

4.4.2 Assessment of inflows

The water inflow into the pit was calculated by the hydrodynamic method, which includes

analytical calculation via several inflow pathways, including:

• Q1 groundwater inflow.

• Q2 storage.

• Q3 inflow of surface water.

Calculations were made on the basis of averaged hydrogeological parameters determined during

testing in 2014 to 2015.

The inflow of groundwater into the open pit for the conditions of a semi-infinite reservoir (H =

const) is calculated using the “big well” method using the formula:

𝑄1 =𝜋𝑘(𝐻2 − ℎ2)

ln 2𝑙 − ln 𝑟0, м3/сут (3.6)

where k is the average filtration coefficient, 0.33 m / day

H – aquifer thickness, defined as the pre-mining level of groundwater in the pit centre (817.7 mRL) to the pit base (150 m 727.2 RL) = 144.5 m

h – residual column of water, m (0 m) t – operation time, 7 * 365 = 2,555 days

l – distance from the center of the pit to the river, 1,250 m

r0 – pit radius, m

𝐹 = Flow, m3/day

1 Cooper, H.H., and C.E. Jacob,1946, A generalized graphical method for evaluating formation constants and

summarizing well field history, Am. Geophys. Union Trans, Vol. 27, pp.526-534

2 Theis, C.V., 1935, The relation between the lowering of the piezometric surface and the rate and duration of discharge

of a well using groundwater storage, Trans. Amer. Geophys. Union, Vol. 16, pp. 519-524



𝑟0 = √F

π (3.7)

The surface area of the pit that exposes underground water is approximately 110,000 m2.

Accordingly, the reduced radius is estimated as √ (110,000 / 3.14) = 187 m.

With the specified parameters, the water inflow into the open pit (Q1) will be 8,348 m3/day.

The volume of groundwater inside the “big well” as a product of its water-cut part for water loss is 110,000 * 144.5 * 0.02 = 317,900 m3. With a uniform discharge for 2,555 days, the inflow of

groundwater from storage (Q2) will be 317,900/2,555 = 124 m3/day.

The total flow from groundwater is therefore Q1 + Q2 = 8,348 + 124 = 8,472 m3/day =

353 m3/hour.

In the immediate vicinity of the proposed pit are the Teply and the Wet streams, which are

planned to be diverted beyond the influence of mining operations. As a consequence, their

potential impact was not considered in the inflow calculation.

The water inflow due to precipitation was determined in accordance with the SNiP 2.06.14-853

and SNiP 2.02.01-833 guidelines for the design of protection of mine workings from underground and surface water. The estimated inflow of rainwater is determined by the method of limiting

intensities, based on a 1 in 10-year daily rainfall intensity.

The total of inflow calculations are presented on Table 4.3.

Table 4.3 Estimated indicators of surface water inflow (Kopy, 2016)

Components of Water Inflow m3/day m3/hour

Groundwater 8,472 353

Rainfall 2,687 112

Snow melted waters 210 9

Average (normal) rainfall inflow 1,075 45

Common during intense rainfall 11,159 465

General low season 9,547 398

The total average daily inflow is estimated at 9,547 m3/day (398 m3/hour) during low-flow

periods, and up to 11,159 m3/day (465 m3/hour) in a 1 in 10-year daily rainfall event.

4.5 Conclusion

The investigations and conclusions presented in Micon Mineral Resource and Ore Reserves

Estimates report, 2018, are a reasonable preliminary estimate of total potential inflow to the pit.

The preliminary nature of the assessment must be emphasized, and the results cannot be carried forward to a dewatering plan. While the mine comprises a stratigraphic sequence of meta-

sediments, groundwater inflow will occur at discrete locations in association with structural

features.

The predicted volumes are such that management are likely to be difficult by sump pumping only. Advanced dewatering with strategically located boreholes screened across potential water

3 SNiP 2.06.14-85 Protection of mines from underground and ground waters. СНиП 2.06.14-85 Защита от мин из

подземных и грунтовых вод



bearing structures have the potential to significantly reduce inflow volumes and pore pressures

near the pit face.

AMC recommend structural mapping to identify potentially water bearing structures that will

intersect the pit and provide targets for advance dewatering boreholes.

In addition, the paths of the Teplyi Creek and Wet streams must be diverted beyond the limits

of the Krasny pit prior to the commencement of mining to prevent surface water inflows.



5 Geotechnical

5.1 Introduction

Kopy Goldfields AB (Kopy) engaged AMC Consultants Pty Ltd (AMC) to conduct a scoping study for their Krasny resource in the Bodaybo District in Irkutsk Region. A geotechnical review was

undertaken as part of the AMC scoping study, which included an assessment of the previous

geotechnical investigations and supporting data, and a review of the appropriateness of the slope

design recommendations.

This report presents the outcome of the review.

5.2 Geology and structure

The geological characteristics, particularly the geological structure is considered to significantly impact the pit slope design for Krasny deposit. A brief description of the geology relevant to

slope design extracted from previous studies is presented in this section.

The following account of the geology and structure were taken from Miramine (2012) and Micon

(2018) reports.

Regionally, the Krasny deposit is located in the miogeosyncline (shallow water sediments deposited on the continental shelf) Bikalid Belt, in the northern limb of the Bodaybo complex

syncline. This is one of the main structures in the central part of the Bodibo syncinorium

(Miramine, 2012).

The development area is composed of Upper Riphean carbonaceous shales, sericite-quartz shales with rare interlayers of sericite-quartz sandstones from the Vachskaya Suite (R3vc). These are

underlain by interstratified quartz sandstones and carbonaceous shales from the Aunakitskaya Suite (R3au) and are capped by interstratified polymictic feldspar-quartz sandstones and

carbonaceous phyllites from the Anangrskaya Suite (R3an). A geological map of the Krasny

deposit is presented in Figure 5.1 and a geological section across the central part of the deposit

(exploration profile 42) is presented in Figure 5.3.



Figure 5.1 Geological map of the Krasny Deposit area (after Micon, 2018)

Figure 5.2 Geological cross section across the central part of the Deposit (Micon, 2018)

The deposit occurs in the rocks of the upper sub-suite of the Aunakitskaya Suite and represents

a zone of vein-veinlet-disseminated quartz-sulphide mineralization, confined to the axial part of the Rudnaya anticline, the main structure of the deposit. The anticline represents an overturned

fold striking ESE, both limbs of which are dipping towards NNE, 85° for the northern limb and



70° to 75° for the southern limb. The limbs are composed of interstratified sandstones and

phyllites with thicknesses of up to 60 m. The fold is cut by large scale faults.

The rocks had undergone greenschist facies metamorphism. They are dark coloured, fine

grained, lightly to well foliated rocks.

The subvertical dips of strata in the southern limb of the anticline can be observed in the

geological sections A-A1, B-B1, C-C1 and D-D1 (Figure 5.2). The southwest, south and southeast sections of the pit are comprised of subvertical strata. The northern limb is folded into several

minor folds and are more open, leading to the strata have gentler SSW or NNE dips.



Figure 5.3 Geological sections A-A1, B-B1, C-C1 and D-D1



5.3 Previous stability assessments

5.3.1 INRTU (2017) study

A geotechnical slope design study was undertaken by the Irkutsk National Research Technical

university in 2017 (INRTU, 2017). The geotechnical parameters used in the study, namely the

rock strength data and structural data were obtained from INRTU (2015a) and INRTU (2015b).

The INRTU (2017) report discusses in detail the factors influencing the pit slopes, which is mainly the strength of different rock types. This especially applies to the weak rocks like shales and the

geological structures, including unfavourably oriented strata and major structures with low shear

strength properties.

Stability assessments on the eight slope sections were conducted in the study. These are shown

in the geological sections A-A1, B-B1, C-C1 and D-D1 (Figure 5.3).

The methodologies used in the stability assessment were the ‘limit equilibrium analysis’ (LE),

‘force polygon method’ and a combination of both methods.

Two-dimensional (2D) LE and finite element (FE) analyses are industry accepted methods for

the slope stability assessments. However, the INRTU approach is differs to the Australian and international systems where the rock mass classification and rock strength are used to derive

shear strength parameters for the stability assessment. AMC is not familiar with the INRTU approach, and as such a review of the results was not conducted. Instead, AMC conducted limited

analyses using LE methods for comparison, which are presented in Section 6.

INRTU (2017) presents analyses for slope heights up to 350 m and recommended to adopt 35° to 38° overall slopes irrespective of the pit sector. They consider that the recommended slope

angles are conservative, but the risks imposed by the potential presence of weak rocks and unfavourable structures will be reduced. They further recommend that these slope angles can

be adjusted (positively or negatively) as further geological information becomes available.

The report further states that the slope design assessments were conducted according to the

following regulatory standards:

• Technological design standards for base metal open pits (1986). (Нормы

технологического проектирования горнорудных предприятий цветной металлургии

открытым способом разработки» ВНТП-35-86 МЦМССС, М., 1986г).

• Technological design standards for open pits (1991). (Нормы технологического

проектирования горнорудных предприятий металлургии c открытым способом

разработки». Гипроруда Л., 1991г. кн 2., Министерство металлургии СССР).

5.3.2 Review by Moscow State Mining Institute (2018)

A review of the INRTU (2017) study and optimization of the pit slope angles was undertaken by

the Department of Geology, Moscow State University in 2018. The results of the review were

presented in MSMI (2018). The work undertaken included:

• Assessments of the factors influencing the stability of the pit slopes including:

⎯ Engineering geological conditions.

⎯ Fracturing and the physicomechanical properties of the deposit.

• Geotechnical profiles were built using the existing geological sections (Figure 5.3).

• Calculation of the stability of the pit walls using:

⎯ Properties of the rocks.

⎯ Structure and fracturing of the rock mass.

The stability analyses were conducted to a target factor of safety (FOS) of 1.15 to 1.2, with

consideration to the mine life of 10 to 15 years (’temporarily permanent slopes’ category).



The rock strength parameters presented in Table 5.1 were used in the stability assessments.

Table 5.1 Rock strength data (MSMI, 2018)

№ Rock Type Density, γ

(t/m3)

Uniaxial Compressive

Strength

(MPa)

Cohesion

(MPa)

Angle of Internal

Friction, Ф

(°)

1 Slates 2,60 53 15.2 30

2 Sandstones 2,80 68 17 37

3 Alevrolity (siltstone) 2,68 118 32 33

4 Ore 2,66 96 16.4 37

The shear strength of the fractured rock mass was estimated using an empirical methodology proposed by G.L. Fisenco (MSMI 2018). LE and force polygon methods were used in the stability

analyses similar to the previous study. The analytical methods were described in detail in the

report.

The results obtained for each geotechnical section are presented in Table 5.2 and batter berm

design recommendations had been provided based on the overall slope angles (adjusted to

achieve the recommended overall slope angles).

Table 5.2 Stability assessment results (MSMI, 2018)

Geological Section Overall Slope

(°)

Slope Height

(m) FOS

А-А1 198° 45 271.45 1.153

А-А1 18° 40 347.3 1.15

B-B1 264° 52 178.0 1.29

B-B1 84° 45 233.9 1.153

C-C1 288° 44 292.0 1.178

C-C1 108° 41 316.8 1.187

D-D1 144° 51 220.0 1.164

D-D1 324° 48 245.79 1.15

5.4 Engineering geology

The engineering geology of the Krasny deposit is based on previous geotechnical reports (INRTU

2015 and MSMI 2018) and basic geotechnical logging data from the Vostochny deposit which is

located approximately 4 km NE of Krasny. The information included:

• Interval data such as lithology, rock quality designation (RQD), fracture frequency and

material strength (index strength).

• Rock property strength estimates from laboratory testing.

• Inspection of the core photos of a small number of drillholes in the Krasny area.

AMC used the data to determine the engineering geology of the deposit, which is presented and

discussed in this section.

5.4.1 Weathering

The areas to the east and west of the Krasny deposit are covered with Quaternary alluvium with a maximum depth of about 20 m. Rock outcrops are commonly observed in the areas not

covered by alluvium. Complete weathering is very shallow and moderately weathered but

competent rock is generally located at depths of ≤5 m. Hydrogeology



The groundwater study conducted on Krasny deposit (Kopy, 2016) indicated that the rock mass

has a low permeability and a permafrost layer is not present.

5.4.2 Degree of fracturing

The degree of fracturing of the rock mass is low to moderate. Zones of intense fracturing are apparent which are associated with the hinges of folds, faults and sheared zones. Inspection of

the core photos indicated two defect sets. The prominent defect set is the foliation or axial cleavage in the folds. The other defect set is generally perpendicular to the foliation. Other

random defects are rarely present. Generally, the RQD values range from 60% to 80% and fracture spacing ranges from 75 mm to 150 mm. An example from the Vostochny deposit is

presented in Figure 5.4.

Figure 5.4 Rock fracture data for drillhole 141789

5.4.3 Rock mass classification

Rock mass classification is one of the methods used to objectively characterize the rock mass and, together with engineering geology, rock mass classification provides a basis for final

selection of the bedrock geotechnical domains.

The Krasny slopes will be comprised mainly of meta-sandstone, meta-siltstone and interlayered

meta-sandstone/meta-siltstone, which have been metamorphosed to greenschist facies. These units have similar strength and defect characteristics, so they were grouped together as a single

domain in the rock mass classification assessment. Furthermore, sufficient geotechnical logging

data was not available for a detailed classification.

Based on the assessment of rock material strength, RQD, discontinuity spacing and condition,

the rock domain was classified using Rock Mass Rating (RMR) (Bieniawski, 1989, RMR89). The RMR values are subsequently used to estimate the Geological Strength Index (GSI), which was

used to estimate the rock mass shear strength parameters. Hoek, Kaiser and Bawden (1995) provide descriptions of these classification systems and their inter-relationship. These

classification systems are considered to be appropriate for all rock materials present at Krasny.

Table 5.3 presents the general rock mass classes based on RQD and RMR.

0

50

100

150

200

250

300

350

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120 140 160 180 200

Fra

ctu

re s

pa

cin

g (

mm

)R

QD

(%

)

Depth (m)



Table 5.3 Rock mass classification based on RQD and RMR

RQD RMR89

RQD Value

(%) Rock Mass Class RMR89 Value Rock Mass Class

< 25 Very poor < 20 V – Very poor

25 to 50 Poor 21 to 40 IV – Poor rock

50 to 75 Fair 41 to 60 III – Fair rock

75 to 90 Good 61 to 80 II – Good rock

90 to 100 Excellent 81 to 100 I – Very good rock

The basic geotechnical parameters RQD, intact rock strength and defect spacing obtained from geotechnical logging of Vostochny core were used to derive RMR89. Assumptions were made on

the joint roughness characteristics based on the core photos of Krasny core and AMC’s

experience with similar rock types. Assumptions for the continuity of the defects were made

based on the structural geology information.

The ‘joint condition rating’, a parameter in RMR89, was derived as in Table 5.4.

Table 5.4 Joint condition rating

Parameter Description Upper Bound Lower Bound

Discontinuity length rating 3 m to 10 m and 10 m to 20 m 2 1

Separation (aperture) <0.1 mm and 0.1 mm to 1 mm 5 4

Roughness rating slightly rough and smooth 3 1

Infill (gouge) rating none and soft infill <5 mm 6 2

Weathering unweathered and slightly weathered 6 5

Joint Condition Rating 22 13

The different parameters used to derive RMR89 and the applicable ratings are presented in Table 5.5. According to the derived range of RMR89, the Krasny rock mass class can be classified

as ‘Fair’ to ‘Good’ rock.

Table 5.5 The range RMR89 and GSI ratings applicable to Krasny rock mass

Parameter Description Upper

Bound

Lower

Bound

Strength of intact rock 50 MPa to 100 MPa 7 7

Drill core quality- RQD 50% to 75% 13 13

Spacing of discontinuities 200 mm to 600 mm and 60 mm to 200 mm 10 8

Condition of discontinuities 22 13

Groundwater (for GSI estimation, dry condition

assumed, Hoek 1995)

Dry 15 15

RMR89 67 56

Geological Strength Index (GSI)1 62 51

1 GSI = RMR89 – 5 (Hoek, Kaiser and Bawden, 1995)

5.4.4 Rock mass structure

AMC considers that the most significant influence on slope stability at Krasny will be the geological structure. Very broadly, the rocks comprising the southern sector of the proposed

Krasny pit will have sub vertical dips. This will be favourable for slope stability unless

unfavourably oriented faults or shears are present. The rocks are intensely foliated, and axial cleavage is prominent, and as such there is a risk of toppling failure, which will have implications

for the batter design.



In the northern half of the proposed pit, the anticlinal fold limb is characterized by a shallower

dip and subjected to en-echelon folding. As a result, the attitude of the foliation can be variable in different sectors of the wall depending upon the folding. This is reflected in the geological

sections presented in Figure 5.3. Given the strongly anisotropic nature of the foliated metasedimentary rocks, the foliation is ubiquitous and is the most important of the potential

pervasive structures that could influence slope stability and hence the slope design at the

northern end.

Shears and faults will also impact slope stability. Jointing is considered as unlikely to be a major

driver of overall slope-scale instability based on AMC’s experience in hard rock open pit mines.

In folded metamorphic rocks, shearing parallel to the foliation is a common occurrence, caused

by the relative movement of layers during folding on weaker foliations. Such shears are continuous over long distances and are often filled with soft gouge and characterized by

smooth/polished surfaces. The shear strength of these structures is very low and has a significant

influence on slope stability.

AMC considers that there is a high potential for the occurrence of foliation shears in the Krasny rocks. However, scrutiny of the core photos from a limited number of drillholes from Krasny

deposit indicated that these are a rare occurrence. Detailed geotechnical logging will be necessary to identify these structures. An example of a potential foliation shear is shown in

Figure 5.5.

Figure 5.5 A potential foliation shear in drillhole 141478

5.4.5 Geotechnical domains

Weathering, strength and fracturing of the various rock units at Krasny are considered to be fairly similar. As such, four geotechnical domains (sectors) were loosely defined in the Krasny

mining area based on geological structure, and mainly the differences in foliation orientation.

These domains are shown in Figure 5.6.



Figure 5.6 Geotechnical domains in the Krasny mining area

Geotechnical domain-1: Defined by the near vertical dip of strata. Inherently stable. There is

some potential for toppling which can influence batter stability.

Geotechnical domain-2: Foliation dips into the slope approximately 10° to 20°. Slope stability

can be influenced by the anisotropy by providing a basal sliding plane.

Geotechnical domain-3: Foliation dips out of the slope, which can be variable from 10° to 20°.

Anisotropy has a significant influence on slope stability.

Geotechnical domain-4: Similar to domain-2. Foliation dips into the slope at approximately

15°. Slope stability can be influenced by the anisotropy by providing a basal sliding plane.

5.5 Geotechnical design parameters

This section presents the geotechnical design parameters used in slope stability analyses and

where appropriate, summarizes the process used to estimate the parameters. They include:

• Unit weight.

• Intact strength of rock material.

• Defect shear strength.

• GSI and rock mass shear strength.

5.5.1 Unit weight

The unit weight of rock materials used in the stability analyses were estimated from laboratory

density measurements (MSMI, 2018).



5.5.2 Rock mass shear strength parameters

Rock mass shear strengths are used in the analysis of rotational sliding through the weathered and fresh rock masses. Depending on the degree of anisotropy expected in the strength of the

rock mass, two approaches have been adopted to model rock mass failure. For the strongly anisotropic meta-sedimentary rock mass, a specialized Mohr-Coulomb strength model was used,

where the foliation shear strengths are assigned at an angle matching foliation dip, and rock

mass shear strengths are assigned perpendicular to foliation.

To determine the rock mass strength, the Generalized Hoek-Brown non-linear failure criterion

for rock masses was used.

The Hoek-Brown criterion is defined as:

σ1 = σ3 + σc(mb(σ3/ σc) + s)a

Where:

σ1 = Major principal stress at failure.

σ3 = Minor principal stress at failure.

σc = uniaxial compressive strength (UCS) of intact material.

‘mb’, ‘s’ and ‘a’ are Hoek-Brown parameters for the rock mass.

The Mohr-Coulomb criteria represents a linear approximation of the Hoek-Brown non-linear failure envelope. Using procedures described by Hoek, Kaiser and Bawden (1995), and modified

by Hoek, Carranza-Torres and Corkum (2002), the domain GSI and a disturbance factor ‘D’ were

used to estimate the Hoek-Brown parameters ‘s’ and ‘a’ and the parameter ratio ‘mb/mi’. The various input parameters to the Hoek-Brown criterion for the various domains have been

determined and/or selected as follows:

• The GSI estimates derived from RMR89.

• The parameter ‘mi’ depends on lithology and rock texture and is estimated from published

tables (Marinos and Hoek, 2000).

For batter stability assessments, a D value of 0.5 representing ‘good’ open pit blasting practices was used to indicate stress relief and blast damage during mining. For overall slope assessments

(where the expected slip surface is sufficiently deep-seated beyond the blast damage zone),

blast damage is not expected but a D value of 0.7 was used to account for potential rock mass

deterioration due to stress relaxation.

The Hoek-Brown shear strength parameters are applied directly in slope stability analyses to explicitly accommodate variations in principal stresses within the analysis model. However, for

the anisotropic model where Mohr-Coulomb parameters are used, design rock mass shear strengths were assessed for the nominal minor principal stress level range appropriate for the

Krasny open pit slopes, where expected depths range from 250 m to 350 m (equivalent to a

maximum range of σ3 from 3 MPa to 6 MPa).

The resulting design Hoek-Brown rock mass strength parameters and corresponding Mohr-

Coulomb shear strength parameters cohesion (c) friction angle (Φ) and applied to each rock unit are presented in Table 5.6. The program Rocdata (Rocscience, verion 5) was used to derive the

Mohr-Coulomb shear strength parameters.



Table 5.6 Design rock mass shear strength parameters

Rock Type Hoek-Brown Strength Parameters 150 m Slope

Height

300 m Slope

Height

Unit Weight

(kN/m3)

UCS

(MPa) RMR89 GSI mi

c

(kPa)

Ф

(°)

c

(kPa)

Ф

(°)

Alluvium 18 — — — — 201 28.01 — —

Upper bound parameters

Meta-Sandstone (SST) 27 68

56 51

17 965 41.4 1458 36.1

Meta-Siltstone (SLT) 26 118 7 1005 38.2 1408 33.1

Interlayered SST/SLT 26.5 751 10* 895 38.3 1318 33.1

Lower bound parameters

Meta-Sandstone (SST) 27 68

67 62

17 1383 47.0 2009 41.9

Meta-Siltstone (SLT) 26 118 7 1815 43.2 2279 38.5

Interlayered SST/SLT 26.5 751 10* 1337 40.0 1758 35.1

1 Assumed value

5.5.3 Design parameters for discontinuities parallel to foliation

Pervasive discontinuity orientation, continuity, and shear strength are used in the analysis of

structurally controlled stability in open pit overall slopes. The ubiquitous foliation imparts significant rock mass strength anisotropy to the foliated rocks. Based on the current geological

model, structural domains for slope design purposes within the rock mass have been defined by

the modelled bedding orientation (anticline fold limbs).

In AMC’s experience of previous slope performance, where the foliation is moderately dipping out of the slope, the batter and overall slope stability is almost exclusively controlled by the

structures parallel to foliation. This is due to the pervasive nature of these structures, typically

low shear strengths, and significant persistence. Joint related kinematic instability in foliated rock masses will typically have a minor impact to achievable slope design due to a combination

of higher shear strength and limited continuity.

In the absence of laboratory shear strength tests on foliation defects, the following shear

strength parameters were used for the structures parallel to foliation:

• Cohesion (c) = 10 kPa.

• Friction angle (Ф) = 22°.

5.5.4 Design groundwater conditions

The groundwater study conducted on Krasny deposit (Kopy, 2016) indicated that the rock mass

has a low permeability. A permafrost layer is not present and therefore the groundwater depth contours map presented in Kopy (2016) were used to develop applicable piezometric surfaces

for the stability models.

Sensitivity to water table drawdown was also assessed in some of the stability models.

5.6 Pit slope stability assessments

Stability assessments were conducted to for the review of MSMI (2018) slope design

recommendations and to validate them for the pit optimization. In this regard, the stability analyses undertaken were only focussed on the ultimate pit slopes. Sufficient data is not

available to conduct a kinematic analysis for batter stability.

Based on AMC’s understanding of the geotechnical conditions, the following methodology was

used to assess the stability of the pit slopes and subsequent designs:

• Geological cross-sections developed by Kopy (2016) which are representative for each

geotechnical domain were used to develop stability models.



• Potential modes of failure were identified for each sector.

• Stability analyses were conducted for representative cross sections in each sector using

the linear anisotropic strength function in the LE program Slide (Rocscience, version 2018).

• The overall slope stability for different slope angles was analysed for each cross-section. The results were reviewed to assess the general stability of the slopes against a set of

acceptance criteria and to identify adjustments required to achieve an optimal design.

• Design recommendations were evaluated with a pseudo-static earthquake loading factor

applied.

5.6.1 Uncertainties in the geotechnical model

The geotechnical model developed for Krasny is considered a basic model as there is no

geotechnical drillhole coverage. AMC used the supplied geological model to develop the

geotechnical model.

5.6.2 Potential failure modes

The potential modes of instability of all pit walls were likely to be complex due to the strong

directional strength bias characteristic of the anisotropic (foliated) materials. Potential modes of

instability include:

• Circular failure, where failure occurs predominantly through the rock mass. In this case,

the rock mass strength takes precedence over structural influence on slope stability.

• Failure with partial control from structures, where the failure surface occurs partially

through the rock mass and partially along a structure.

5.6.3 Acceptance criteria

The slope design acceptance criteria represent the limits that the slope design must satisfy to be deemed to have an acceptable level of confidence of stability. The criteria are based on ‘factor

of safety’ (FOS) and ‘probability of failure’ (POF) values determined as part of the analysis.

Table 5.7 presents acceptance criteria typically applied within the mining industry (Read and

Stacey, 2009). The values adopted by AMC for this study are presented in Table 5.8, and were selected to align with typical values applied within the mining industry and with consideration of

the likely consequences of slope failure at the project.

Table 5.7 Typical slope design acceptance criteria (Read and Stacey, 2009)

Slope Scale Consequences

of Failure1 Acceptance Criteria2

FOS (min) – Static FOS (min) – Dynamic POF (max) P[FOS ≤1]

(%)

Bench Low to high 1.1 N/A 25 to 50

Inter-ramp Low 1.15 to 1.2 1.0 25

Moderate 1.2 1.0 20

High 1.2 to 1.3 1.1 10

Overall Low 1.2 to 1.3 1.0 15 to 20

Moderate 1.3 1.05 10

High 1.3 to 1.5 1.1 5

1 Semi-quantitatively evaluated

2 Needs to meet all acceptance criteria

Table 5.8 Adopted slope design acceptance criteria

Material Type Slope Scale Acceptance Criteria

FOS – Static FOS – Dynamic POF (max) P[FOS≤1]

All Overall 1.3 NA N/A



5.6.4 Overall slope stability analysis

Slope stability assessments were conducted for overall, inter-ramp and batter scale slopes using

the LE analysis program Slide (Rocscience, version 2018).

A rigorous critical failure surface search process was used to determine the minimum FOS for each slope. AMC applied the non-circular search functions, specifically “Path Search” and “Auto

Refine” in the program, and targeted various vertical sections of the slope. The resulting critical surface was then subjected to the program’s built-in optimization to search for the minimum

FOS. The LE methods used were Bishop Simplified, Spencer, and Morgenstern-Price, and the

minimum resulting FOS value of the Spencer and GLE methods was selected.

5.6.5 Assumptions

The following assumptions were made in the stability analyses:

• The phreatic surface assumptions as described in Section 5.5.4. Where low FOS values

were obtained due to groundwater influence, sensitivity analyses were conducted by

assuming different water table drawdown conditions.

• The foliation in the basic gneiss unit is ubiquitous.

• The continuity of the defects parallel to foliation was assumed to be persistent enough to

facilitate overall slope scale instabilities.

• Geotechnical design parameters presented in Section 5.5 were used in all assessments.

5.6.6 Results

A summary of the stability analysis results is presented in Table 5.9 and some of the stability

models are presented in Figure 5.7 to Figure 5.10.

Table 5.9 Results of the stability analysis

Geotechnical

Domain

Slope Height

(m)

Slope Angle

(°) Groundwater Method Selected FOS

1 (Section 1, 198°) 273

47

880 m RL, on the slope

Circular

failure/path

search

1.80

50 1.70

3 (Section 1, 018°)

347 50

920 m RL, on the slope

Circular

failure/path

search 1.44

Anisotropic

linear

0.77

Some drawdown adjacent

to slope 0.88

352 45

No Draw down 0.79


to slope 0.92

Complete depressurization 1.27

352 40

No Draw down 0.84


to slope 0.95

Complete depressurization 1.32

3 (Section 4, 108°

and 288°) 292 50

885 m RL, no draw down

Circular

failure/path

search 1.67

Anisotropic

linear

1.24


to slope 1.30



Figure 5.7 Geotechnical domain-1 stability of 50° overall slope

Figure 5.8 Geotechnical domain-3 stability of 50° overall slope (failure through rock mass)




and along foliation, no draw down)




and along foliation, complete depressurization)

5.6.7 Slope design recommendations

Structural data was not available to conduct kinematic stability analyses, and as such, batter slope design was not conducted. However, based on the geological sections and observations of

the rock mass conditions using the core photographs, AMC considers that batter face angles up

to 75° can be achieved for 20 m high batters.

Using the empirical formula proposed by Call & Nicholas (Read & Stacey, 2009) for the berm

width calculation, the required berm width is 8.5 m for a 20 m high bench:

Berm width = 0.2 x bench height + 4.5 m

Based on the results of the stability assessment, AMC’s recommendations for overall and batter slope design angles are presented in Table 5.10, and illustrated in Figure 5.10 and Figure 5.12.

The overall slope design recommendations are presented on the geotechnical domain plan in

Figure 5.13.

It is noted that these slope design recommendations are comparable to the recommendations

given in MSMI (2018) report.



Table 5.10 Recommendations for slope design

Geotechnical

Domain

Batter Design Overall Slope

Bench

Height

(m)

Bench Face

Angle

(°)

Bench Width

(m)

Geotechnical Berm Slope

Height

(m)

Slope

Angle

(°)



3 20 60 10 20 m 100 m vertical depth 360 41.4


Figure 5.11 Proposed slope profile for geotechnical domains 1,2 and 4

0

50

100

150

200

250

300

350

0 50 100 150 200 250 300 350

Ve

rtic

al (m

)

Horizontal (m)



Figure 5.12 Proposed slope profile for geotechnical domain-3

Figure 5.13 Geotechnical domains and overall slope design recommendations

0

50

100

150

200

250

300

350

0 50 100 150 200 250 300 350 400

Ve

rtic

al (m

)

Horizontal (m)



6 Krasny mining review

6.1 Introduction

AMC undertook a review of the available mining reports to consider the deposit’s potential to be developed into a viable economic mining operation. AMC have also performed a series of Project

sensitivity analyses to investigate the potential opportunities to enhance the economic viability


6.2 Krasny pit optimization

The limits for an open pit can be selected through analysis of the Whittle Four-X application of the Lerchs Grossman (LG) algorithm. Whittle Four-X software applies the pit slope angles to

generate linked blocks that must all be mined to establish the required slope angle. Each block is assigned a value that is the difference between the revenue derived from processing and

selling any ore within the block, and any costs incurred in mining and processing the block. In this way, all linked blocks that have a total value that are positive, for a particular set of

commodity prices, will be included within a pit shell.

The Whittle Four-X package develops a series of pit optimization shells that can be regarded as concentric pits, each generating the maximum undiscounted operating surplus cash flow for the

set of economic parameters used to develop that optimization shell. The shells are developed by varying the commodity prices, but once defined they are all evaluated at the base case

commodity price.

These nested shells can be used to develop indicative production schedules for fixed plant

throughput and mining rates, and hence estimate discounted operating surpluses. Two extreme schedules are developed, a best case and a worst-case schedule. The best-case schedule

assumes the pits can be mined optimally with each optimization shell being completed before

mining of the next shell commences. The worst-case schedule assumes that no staging of the pits is possible and that the entire pit area is mined out on each bench before proceeding to the

next. The reality of a practical mining schedule would lie between these extreme schedules. Both

schedules can be used to generate a highest discounted operating surplus.

The inputs to the Whittle Four-X analysis are:

• Product prices.

• Mining costs.

• Processing, realization and administration costs.

• Process recoveries.

• Pit slope angles.

• Prepared model.

The pit optimization was based on differing sets of resource classification configurations,

producing two runs, as follows:

• Run 8 MII for Measured, Indicated and Inferred Resources (MII).

• Run 8 MI for Measured and Indicated Resources (MI) only.

6.2.1 Whittle block model

The Whittle 4X block model was generated from the 2018 mineral resource model supplied in

the data room by Micon (bm_krasn_upd.csv). The supplied model contained gold mineralization

only and additional background waste was created using the supplied LIDAR surface,

(TOPO_KRA_LIDAR.dxf). Generated waste blocks were assigned a bulk density of 2.53.

The model fields have been modified for the purpose of optimization. Some geological fields were removed, and additional fields required for the optimization process were added. Table 6.1 lists



all the model fields contained in the regularized resource model that were relevant for the

optimization process.

Table 6.1 Mineral Resource model fields used in optimization

Name Value Description

XMORIG, YMORIG, ZMORIG 367400; 6463600; 400; Origin of the model

NX, NY, NZ 500; 240; 130; Number of model parent cells in XYZ directions

XINC, YINC, ZINC 25; 25; 4; XYZ cell dimensions

XC, YC, ZC coordinates XYZ coordinates of the cell centre

IJK parent cell identifier Numeric parent cell identifier

RESCAT 1 ; 2 Resource classification (numeric)

AU variable Gold grade

class Inferred; Indicated Resource classification (alpha-numeric)

DENSITY 2.68 Density

WEAZONE 0; 1; 2 Weathering zone

MINPROP variable Proportion of mineralization within block

6.2.2 Krasny pit optimization parameters

All pit optimization parameters are derived from the 2018 Mineral Resource and Ore Reserve

report prepared by Micon, Table 6.2 shows all the parameters used in the optimization.

AMC added $0.70/t to milling cost to represent the additional haulage cost associated with

transporting ore to the existing concentration plant located 14 km from Krasny. AMC additionally

applied the difference between ore and waste mining costs as an ore premium. Models are prepared for optimization by adding cost, recovery, royalties and revenue drivers to individual

blocks within the model using Datamine macros. This process provides an audit trail and reduces

errors in assigning optimization parameters.

Within the optimization process a mining dilution of 10% and mining loss 5% was applied. Whittle applies dilution by increasing parcel tonnage by the specified amount while keeping the total

metal content constant. The dilution material now considered as ore is then removed from the waste tonnage for that parcel. Whittle applies ore loss by decreasing parcel tonnage and metal

content by the specified amount. The ore loss material is no longer considered as ore and is

treated as waste tonnage for that parcel.

A minimum gold grade of 0.4 g/t was applied as a cut-off when determining ore classification in

the mining model.



Table 6.2 Pit optimization cost and revenue parameters

Item Unit Value Unit Value

Mining costs

Waste mining cost RUB/t mined 83.06 US$/t mined 1.38

Ore mining cost RUB/t ore 109.00 US$/t ore 1.82

Processing costs

Milling cost RUB/t ore 417.20 US$/t ore 7.65

General production costs RUB/t ore 248.20 US$/t ore 4.14

Administration costs RUB/t ore 84.00 US$/t ore 1.40

Payments (land, use of subsoil, ecology, transport tax) mln. RUB/year 12.06 US$/t ore 0.07

Revenue

Gold price US$/oz 1250 US$/g 40.19

Exchange rate RUB/US$ 60

Refinery and transport % Revenue 0.24 US$/g 0.10

Royalty % Revenue 6.5 US$/g 2.61

Modifying factors

Ore loss % 5

Dilution % 10

Metallurgical recoveries

Oxide ore % 77.5

Transitional ore % 87.8

Primary ore % 88.5

Overall slope angles - all material

Bearing - 18° ° 40

Bearing - 84° ° 43

Bearing - 108° ° 41

Bearing - 144° ° 46

Bearing - 198° ° 45

Bearing - 264° ° 46

Bearing - 288° ° 44

Bearing - 324° ° 48

Miscellaneous

Material movement limit Mtpa 1

Plant throughput limit Mtpa 0.4

Discount rate % 6

6.2.3 Krasny pit optimization results

Pit shells were produced by the optimization process based on two Mineral Resource classification

configurations:

• Run 8 MII – Measured, Indicated and Inferred Resource.

• Run 8 MI – Measured and Indicated Resource.

Each optimization run produced a set of nested shells by applying a revenue factor to metal

price, ranging from 0.6 to 1.4 times the base gold price. For each shell the undiscounted cash

flow was calculated based on cost and price inputs. As a result, Pit shell 5, revenue factor = 1.0 (RF1) shell, produced maximum cash flow for both MII and MI resource runs. The summary

results for MII shown in Table 6.3 and MI in Table 6.4.



Table 6.3 Krasny pit optimization results for run 8 MII

Table 6.4 Krasny pit optimization results for run 8 MI

Tonnes In-situ Au Recovered

Au

(mRL) (Mt) (g/t) (g/t) (Mt) (Mt) (W:O) ($/t) ($/t) (koz) ($/oz) ($M) ($M) ($M) ($M) ($M) ($M) ($/oz)

1 0.60 600 17.0 1.62 1.41 172.5 189.5 10.1 15.4 15 593 1,240 -304 -262 964 399 -14 -14 954

2 0.70 590 23.3 1.67 1.46 273.4 296.6 11.8 17.6 24 841 1,282 -419 -409 1,367 539 -14 -19 1,062

3 0.80 575 24.9 1.69 1.48 310.1 335.0 12.5 18.6 33 909 1,304 -450 -462 1,478 566 -14 -19 1,218

4 0.90 560 25.7 1.69 1.48 329.2 354.9 12.8 19.1 34 939 1,321 -464 -490 1,527 573 -14 -19 1,418

5 1.00 560 26.0 1.69 1.48 338.3 364.4 13.0 19.3 36 951 1,331 -471 -503 1,547 573 -14 -20 1,563

6 1.10 555 26.4 1.69 1.48 347.9 374.3 13.2 19.6 43 962 1,341 -476 -516 1,566 573 -14 -20 1,702

7 1.20 550 28.0 1.67 1.46 393.5 421.5 14.1 20.8 40 1,012 1,396 -505 -582 1,646 560 -14 -20 1,887

8 1.30 550 28.4 1.67 1.46 407.4 435.8 14.4 21.2 51 1,025 1,412 -512 -601 1,667 554 -14 -21 2,044

9 1.40 550 28.7 1.67 1.46 418.0 446.6 14.6 21.5 55 1,034 1,424 -517 -616 1,682 549 -14 -21 2,203

Pit

Shell

Revenue

Factor

Bench Total Ore

Base Shell Data Value

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce

Undiscounted

Surplus

RevenueMining

Cost

Processing

Cost

Total

Rock

Tonnes

Total

Waste

Tonnes

Cost per

Ounce

Recovered

Ounces

Incremental

Mining Cost

per Tonnes

of Ore

Mining

Cost per

Tonnes

of Ore

Strip

Ratio

Tonnes In-situ Au Recovered

Au


1 0.60 865 3.1 1.22 0.99 8.5 11.6 2.7 5.2 5 76 1,158 -51 -16 123 56 33 33 890

2 0.70 825 5.8 1.21 1.01 25.0 30.8 4.4 7.4 10 143 1,255 -96 -43 233 95 38 22 1,048

3 0.80 820 5.9 1.21 1.01 26.7 32.6 4.5 7.6 15 148 1,264 -99 -45 240 97 39 21 1,223

4 0.90 820 6.1 1.21 1.01 29.3 35.4 4.8 8.0 24 152 1,281 -101 -49 248 98 39 18 1,385

5 1.00 810 6.3 1.20 1.01 31.5 37.8 5.0 8.3 16 157 1,302 -105 -52 255 98 39 16 1,568

6 1.10 805 6.4 1.20 1.00 32.8 39.2 5.1 8.4 18 159 1,314 -106 -54 258 98 39 15 1,699

7 1.20 805 6.5 1.19 1.00 34.2 40.7 5.3 8.6 20 161 1,328 -108 -56 262 97 39 14 1,880

8 1.30 800 6.6 1.19 1.00 36.3 42.9 5.5 8.9 28 163 1,347 -110 -59 265 96 39 12 2,003

9 1.40 795 6.6 1.19 1.00 36.9 43.6 5.6 9.1 40 164 1,352 -110 -60 266 96 39 11 2,157

Pit Shell Revenue

Factor

Bench Total Ore


Total

Waste

Tonnes

Total

Rock

Tonnes

Strip

Ratio

Mining

Cost per

Tonnes

of Ore

Incremental

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce

Processing

Cost

Mining

Cost

Revenue Undiscounted

Surplus

Discounted

Surplus -

Best Case



Figure 6.1 and Figure 6.2 show the relationship between incremental pit shells generated by the

optimization for the MI and MII models respectively for different revenue factors, pit inventory,

and cash flow.

Figure 6.1 Pit optimization results for run 8 MII

Figure 6.2 Pit optimization results for run 8 MI

6.2.4 Comparison of Krasny pit optimization results

Details of Revenue Factor 1 pit shells generated by AMC and Micon for MII and MI cases is

summarized in Table 6.5. The RF1 pit shells generated by AMC and Micon are similar in size with a variance of 2% to 5% in total material. The AMC pit shells achieved a similar depth and

contained 3% to 6% less ore tonnage compared to Micon RF1 pit shells.

0

50

100

150

200

250

300

350

400

450

500

0

100

200

300

400

500

600

700

0.60 0.70 0.80 0.90 1.00 1.10 1.20 1.30 1.40

To

nn

es (M

t)Un

dis

co

un

ted

S

urp

lus ($

M)

Revenue FactorOre Waste Undisc. Surplus

0

5

10

15

20

25

30

35

40

45

50

0

20

40

60

80

100

120

0.60 0.70 0.80 0.90 1.00 1.10 1.20 1.30 1.40

To

nn

es (M

t)Un

dis

co

un

ted

S

urp

lus ($

M)

Revenue FactorOre Waste Undisc. Surplus



Table 6.5 Comparison of AMC and Micon pit optimization results


Figure 6.3.

Figure 6.3 West east cross section of RF1 pit shells





It is worth noting that the project is characterized by large quantities of marginally economic

grade ore, and relatively small fluctuations in the application of cut-off grade result in significant


Inspection of the Krasny grade-tonnage curve illustrates that around the cut-off grade of 0.4 g/t gold, which is the limit applied to the current Project Ore Reserve statement, there are sharp



artificially swell the ore inventory of the optimization outputs and may lead to negative impacts

on the project financial results.

AMC have utilized a cut-off grade of between 0.5g/t gold to 5.0g/t gold for the calculation of

underground inventories utilising the Mineable Shape Optimizer (MSO). The open pit Whittle pit optimizations utilized the 0.4g/t gold cut-off, in order to be comparable to the previous iterations

of work and align with the currently quoted 2018 Ore Reserve reporting by Micon. The combined open pit and underground production scenarios reported here by AMC, are based upon a higher


Factor

Total

Mining

Waste Ore Stripping

Ratio

Gold Gold Gold

g/t Mt Mt Mt (t:t) kg oz g/t

MII Micon 0.40 1 383.4 356.7 26.7 13.36 43,890 1,411 1.64

MII AMC 0.40 1 364.4 338.3 26.0 12.99 43,958 1,413 1.69

Variance -5.0 -5.1 -2.5 -2.8 0.2 0.2 2.9

MI Micon 0.40 1 38.6 31.9 6.7 4.76 7,659 246 1.14

MI AMC 0.40 1 37.8 31.5 6.3 5.00 7,565 243 1.20

Variance -2.0 -1.1 -5.9 5.0 -1.2 -1.2 5.2






AMC recommends estimating a cut-off grade that more closely represents the calculated cut-off

from operating costs and gold recoveries. This is likely to be higher in future studies and is likely


The Krasny grade-tonnage curve graph is shown below in Figure 6.4.

Figure 6.4 Grade tonnage curve

6.3 Krasny pit optimization sensitivity

The sensitivity of the project pit optimization results to variations in the major input parameters

was tested by changing the value of individual parameters while keeping all others constant.

Individual parameters changed include:

• Metal price.


• Mining cost.




Sensitivity analysis was completed for both MI and MII scenarios. The RF1 pit shells were

selected for parameter variance to explore the sensitivity of output shell size and corresponding

financial metrics. The applied variation range for the input parameters were ±50% for metal price, processing cost and mining cost. +50% to +400% for production rate, ±5° for pit slopes

and -10% to +2% for recovery.

Changes in the undiscounted cash flow and ore tonnage variance for each parameter have been

plotted, where a steeper slope on any curve represents greater sensitivity to the parameter

represented by that curve.

0

1

2

3

4

5

6

7

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t)


Tonnes Au



6.3.1 Krasny sensitivity analysis – Measured and Indicated

The pit optimization results are shown in Table 6.6.

Table 6.6 MI sensitivity - pit optimization results


tonnes with results presented in Figure 6.5 to Figure 6.8 for cash flow sensitivity and Figure 6.9

to Figure 6.12 for ore tonnage sensitivity.

The sensitivity analysis demonstrates that the undiscounted cash flow is most sensitive to changes in gold price. A 10% reduction in gold price results in a 25% decrease in undiscounted

cash flow. The undiscounted cash flow is less sensitive to changes in mining cost than processing cost. A 10% increase in mining costs results in a 5% decrease in cash flow. A 10% increase in

processing cost results in a 10% decrease in cash flow.

Total Rock

Tonnes Au Recovered Au Tonnes

($/oz) (kt) (g/t) (oz) (kt) (kt) ($M)

-50% 1250 6,676 1.00 214 37,978 44,654 126

-30% 1250 6,557 1.00 211 35,366 41,922 114

-20% 1250 6,411 1.00 207 33,116 39,527 109

-10% 1250 6,376 1.01 206 32,532 38,908 103

Base 1250 6,306 1.01 204 31,540 37,845 98

10% 1250 6,123 1.01 199 29,526 35,649 93

20% 1250 6,082 1.01 198 29,073 35,155 88

30% 1250 6,049 1.01 196 28,371 34,420 83

50% 1250 5,929 1.01 192 26,423 32,351 74

-50% 1250 7,398 0.92 220 34,338 41,737 156

-30% 1250 7,300 0.93 217 32,767 40,067 132

-20% 1250 7,134 0.94 215 32,157 39,290 120

-10% 1250 6,799 0.97 211 32,148 38,947 109

Base 1250 6,306 1.01 204 31,540 37,845 98

10% 1250 5,724 1.05 194 29,852 35,575 88

20% 1250 5,345 1.10 188 30,086 35,431 79

30% 1250 4,985 1.14 182 29,941 34,926 70

50% 1250 4,343 1.22 170 29,898 34,241 54

-50% 1250 376 1.51 18 1,500 1,876 2

-30% 1250 4,379 1.18 166 26,429 30,808 28

-20% 1250 5,040 1.11 180 27,566 32,607 50

-10% 1250 5,671 1.06 193 29,725 35,395 73

Base 1250 6,306 1.01 204 31,540 37,845 98

10% 1250 6,790 0.97 211 32,394 39,184 124

20% 1250 7,167 0.94 217 33,531 40,699 151

30% 1250 7,403 0.93 221 35,482 42,885 178

50% 1250 7,545 0.92 224 37,626 45,171 234

-5 degrees 1250 6,170 1.01 199 35,740 41,910 89

Base 1250 6,306 1.01 204 31,540 37,845 98

+5 degrees 1250 6,318 1.01 205 27,150 33,469 105

0.4 Mtpa (Base) 1250 6,306 1.01 204 31,540 37,845 98

0.6 Mtpa 1250 6,933 0.95 213 32,137 39,070 112

0.8 Mtpa 1250 7,149 0.94 215 32,150 39,299 121

1.0 Mtpa 1250 7,287 0.93 217 32,772 40,059 128

1.2 Mtpa 1250 7,303 0.93 217 32,772 40,075 133

1.4 Mtpa 1250 7,305 0.93 217 32,772 40,076 137

1.6 Mtpa 1250 7,308 0.93 217 32,796 40,104 141

-10% 1250 5,671 1.06 193 29,725 35,395 73

-5% 1250 5,916 1.03 196 29,696 35,612 85

-2% 1250 6,231 1.01 203 31,598 37,830 93

Base 1250 6,306 1.01 204 31,540 37,845 98

2% 1250 6,399 1.00 205 31,706 38,105 103

Run Au Price Ore Undisc.

Cash Flow

Mining Cost

Waste

Tonnes

Processing

Cost

Gold Price

Pit Slopes

Production

Rate

Recovery



The ore tonnage is most sensitive to changes in gold price and processing cost. A 10% reduction

in gold price results in a 10% decrease in ore tonnage. A 10% increase in processing cost results in a 9% decrease in ore tonnage. The pit optimization was not sensitive to variations in mining

cost. A change in mining cost of 50% results in a 6% change in ore tonnage.

Figure 6.5 MI sensitivity - undiscounted cash flow

Figure 6.6 MI sensitivity – production rate – undiscounted cash flow

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Figure 6.7 MI sensitivity – pit slopes - undiscounted cash flow

Figure 6.8 MI sensitivity - recovery - undiscounted cash flow

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Figure 6.9 MI sensitivity - ore tonnage

Figure 6.10 MI sensitivity – production rate – ore tonnage

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2,000

3,000

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5,000

6,000

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8,000

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Ore

To

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e (kt)

Variance (%)


-

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0.4 0.6 0.8 1 1.2 1.4 1.6

Ore

To

nn

ag

e (kt)




Figure 6.11 MI sensitivity - pit slopes - ore tonnage

Figure 6.12 MI sensitivity - recovery - ore tonnage

6.3.2 Krasny sensitivity analysis – Measured, Indicated and Inferred

The pit optimization results are shown in Table 6.7.

-

2,000

4,000

6,000

8,000

10,000

12,000

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Ore

To

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ag

e (kt)

Variance (Degrees)

-

2,000

4,000

6,000

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Ore

To

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e (kt)

Recovery Variance %



Table 6.7 MII sensitivity - pit optimization results

The sensitivity analysis was reported on percentage change in undiscounted cash flow and ore tonnes with results presented in Figure 6.13 to Figure 6.16 for cash flow sensitivity and

Figure 6.17 to Figure 6.20 for ore tonnage sensitivity.

The sensitivity analysis demonstrates that the undiscounted cash flow is most sensitive to

changes in gold price. A 10% reduction in gold price results in a 27% decrease in undiscounted

cash flow. A 10% increase in processing cost results in an 8% decrease in cash flow.

The ore tonnage is sensitive to changes in gold price. A 10% reduction in gold price results in an 5% decrease in ore tonnage. A 10% increase in processing cost results in a 4% decrease in

ore tonnage.

Total Rock

Tonnes Au Recovered Au Tonnes

($/oz) (kt) (g/t) (oz) (kt) (kt) ($M)

-50% 1250 28,973 1.46 1,361 434,860 463,833 858

-30% 1250 28,326 1.46 1,332 406,070 434,396 735

-20% 1250 26,613 1.48 1,263 355,367 381,980 676

-10% 1250 26,278 1.48 1,250 346,148 372,426 624

Base 1250 26,038 1.48 1,238 338,341 364,379 573

10% 1250 25,831 1.48 1,227 331,820 357,651 524

20% 1250 25,196 1.48 1,200 318,454 343,650 475

30% 1250 25,011 1.48 1,189 312,939 337,950 428

50% 1250 23,776 1.46 1,120 282,780 306,555 336

-50% 1250 29,263 1.41 1,324 384,795 414,058 821

-30% 1250 27,806 1.42 1,268 345,657 373,462 720

-20% 1250 27,548 1.42 1,261 342,712 370,260 670

-10% 1250 27,022 1.44 1,255 342,135 369,157 621

Base 1250 26,038 1.48 1,238 338,341 364,379 573

10% 1250 24,931 1.52 1,216 333,524 358,455 527

20% 1250 23,963 1.56 1,201 332,897 356,860 483

30% 1250 23,108 1.60 1,185 331,775 354,882 439

50% 1250 20,810 1.69 1,130 321,757 342,567 359

-50% 1250 1,181 1.85 70 9,937 11,119 6

-30% 1250 19,725 1.64 1,041 276,904 296,628 137

-20% 1250 22,731 1.58 1,153 312,224 334,955 274

-10% 1250 24,668 1.52 1,208 330,251 354,919 421

Base 1250 26,038 1.48 1,238 338,341 364,379 573

10% 1250 27,102 1.45 1,261 347,155 374,257 730

20% 1250 29,237 1.42 1,331 392,214 421,451 891

30% 1250 29,826 1.41 1,350 405,970 435,796 1,058

50% 1250 30,239 1.40 1,365 419,532 449,772 1,398

-5 degrees 1250 25,370 1.48 1,209 398,058 423,428 468

Base 1250 26,038 1.48 1,238 338,341 364,379 573

+5 degrees 1250 27,394 1.47 1,293 312,144 339,538 653

0.4 Mtpa (Base) 1250 26,038 1.48 1,238 338,341 364,379 573

0.6 Mtpa 1250 27,242 1.44 1,257 342,034 369,277 634

0.8 Mtpa 1250 27,572 1.42 1,262 342,689 370,261 674

1.0 Mtpa 1250 27,755 1.42 1,266 344,632 372,387 702

1.2 Mtpa 1250 27,829 1.42 1,269 346,379 374,208 724

1.4 Mtpa 1250 27,935 1.42 1,272 348,470 376,406 741

1.6 Mtpa 1250 27,957 1.42 1,273 349,279 377,236 756

-10% 1250 24,668 1.52 1,208 330,251 354,919 421

-5% 1250 25,405 1.50 1,223 333,013 358,418 497

-2% 1250 25,682 1.48 1,226 332,774 358,456 543

Base 1250 26,038 1.48 1,238 338,341 364,379 573

2% 1250 26,272 1.47 1,243 340,293 366,565 604

Au Price Ore Undisc.

Cash Flow

Mining Cost

Processing

Cost

Waste

Tonnes

Gold Price

Pit Slopes

Production

Rate

Recovery

Run



AMC notes an average mining cost was applied in the pit optimizations. The MII pit optimizations

achieve a greater depth compared to the MI case. Application of an incremental mining cost will have a significant impact on the pit optimization due to the increased stripping ratio of the larger

MII pit shells. The sensitivity analysis shows a 30% increase in mining cost results in an 25% decrease in cash flow. AMC recommend more detailed work be undertaken, during future study

activities, in order to more accurately determine the variable open pit mining cost in the deeper

MII pit optimizations.

Figure 6.13 MII sensitivity - undiscounted cash flow

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Figure 6.14 MII sensitivity - production rate - undiscounted cash flow

Figure 6.15 MII sensitivity - pit slopes - undiscounted cash flow

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Figure 6.16 MII sensitivity - recovery - undiscounted cash flow

Figure 6.17 MII sensitivity - ore tonnage

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Ore

To

nn

ag

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Variance (%)




Figure 6.18 MII sensitivity - production rate - ore tonnage

Figure 6.19 MII sensitivity - pit slopes - ore tonnage

25,500

26,000

26,500

27,000

27,500

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28,500

0.4 0.6 0.8 1 1.2 1.4 1.6

Ore

To

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Figure 6.20 MII sensitivity - recovery - ore tonnage

6.4 Krasny underground optimization

The underground potential was assessed and optimized using the Mineable Shape Optimizer

(MSO) process in Datamine’s 5D Planner (5DP) software package. This process generates stope shapes at a range of variables including cut-off grades, floor to floor lift heights, stope widths

and stope strike lengths. This allows a relatively quick assessment of a deposit’s applicability for underground exploitation, the types of mining methodology that may be applied (together with

geological and geotechnical inputs) and a preliminary assessment of potential mining inventory.

AMC conducted two types of MSO assessments. The first MSO assessment was to determine the

suitability of the block model with the MSO process. This involved running MSO in multiple

scenarios with differing stope dimensions to ascertain any limiting or preferable variables. The results of this initial assessment showed that the block model was robust and that no limiting




minimum 1.5 m stope width as these stoping dimensions allow extraction by the most commonly used underground mining equipment. The MSO process was ran using these stoping dimensions


The results were summarized and assessed using an AMC Microsoft Excel template generated for this purpose. The MSO template applies key metrics such as recovery and dilution factors to

the MSO results, it also applies basic cost and revenue data and uses Longs Rule to assess

possible annual extraction rates. The results of this analysis include:

• Estimated annual underground extraction rates.

• Estimated mining costs and revenue streams.

• Estimated net present values.

• Estimated mining inventory including total mining tonnes, total recovered metal and the

average grade for each MSO run.

24,400

24,600

24,800

25,000

25,200

25,400

25,600

25,800

26,000

26,200

26,400

-10 -8 -6 -4 -2 0 2

Ore

To

nn

ag

e (kt)

Recovery Variance %



A summary of the MSO outputs is shown in Table 6.8.

Table 6.8 Summary of MSO outputs

MSO Run Cut-off Grade

(g/t Au)

Tonnes

(t)

Gold Grade

(g/t)

Gold Ounces

(oz)

20mS x 20mL_0.5 0.5 37,615,883 1.64 1,981,560

20mS x 20mL_1.0 1.0 24,594,252 2.12 1,677,444

20mS x 20mL_1.5 1.5 15,466,655 2.63 1,305,560

20mS x 20mL_2.0 2.0 9,200,290 3.20 946,565

20mS x 20mL_2.5 2.5 5,692,649 3.75 686,556

20mS x 20mL_3.0 3.0 3,611,067 4.26 494,643

20mS x 20mL_3.5 3.5 2,483,531 4.67 372,670

20mS x 20mL_4.0 4.0 1,574,725 5.16 261,209

20mS x 20mL_4.5 4.5 795,767 5.92 151,549

20mS x 20mL_5.0 5.0 678,113 6.12 133,404

6.5 Krasny underground MINPROP field analysis

The MINPROP field was not utilized in the underground optimization component of this work. This is due to the fact that the underground MSO shapes have external dilution added to their



The portion of the block model cells outside of the mineralization zone for these underground

MSO shapes would then still be included, as external dilution.

An analysis was undertaken to verify this. This involved reviewing the MSO tonnages with high, low and average dilution estimates as well as high, low, and average recovery estimates. The

analysis showed that the estimated change in tonnage from the MINPROP field tonnages to the MSO tonnages were approximately 15.7% using the average estimates. Well within the accuracy

level of this Study.

6.6 Krasny production scheduling


production to the processing plant. The 2018 Mineral Resource and Ore Reserve report

considered a nominal plant throughput rate of 0.4 Mtpa, which AMC considers to be very low for the magnitude of the Krasny project. In order to present an easy comparison with the previous

iterations of study work, AMC has considered the same nominal plant throughput rate of 0.4 Mtpa, as well as presenting an additional analysis of 1.0 Mtpa, 2.0 Mtpa and 3.0 Mtpa

throughputs, as a higher production rate is likely to present more favourable economic outcome.

Pit optimization results for 1.0 Mtpa, 2.0 Mtpa and 3.0 Mtpa plant throughput capacities are

summarized in Appendix A.

The RF1 pit shell was selected as the ultimate pit in each production scenario, pit staging was

considered to defer waste stripping and maximize cash flow during early years of production.

Staging was determined by visual inspection of interim pit shells with consideration for minimum mining width. A maximum vertical advance rate of 50 m per annum has been used for

scheduling. Stockpiling of ore has not been considered, but is likely to achieve a superior

economic outcome, following more detailed study work.





consideration of underground mining.

6.6.1 Scenario 1 open pit (MI) – 0.4 Mtpa plant throughput

Scenario 1 considers mining of a two-stage open pit with Inferred resources excluded as ore in

the mining inventory. Pit shell 10, RF0.58 was selected as the interim stage. An overview of the

pit stages is shown in Figure 6.21.

Figure 6.21 Scenario 1 staging

A peak material movement of 3.0 Mtpa was required to maintain 0.4 Mtpa of ore production.

This mining rate is sustained for the first nine years in the 16-year mine life. The annual head

grade, ore and waste movements are summarized in Figure 6.22.

Figure 6.22 Scenario 1 production profile

0.4 Mtpa MI RF1 Pit

0.4 Mtpa MI RF0.58 Pit

0.00

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2020202120222023202420252026202720282029203020312032203320342035

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Ore Waste Au Grade



6.6.2 Scenario 2 open pit (MI) – 1.0 Mtpa plant throughput

Scenario 2 considers mining of a three-stage open pit with Inferred resources included as ore in the mining inventory. Pit shell 2 (RF0.42) and pit shell 7 (RF0.52) were selected as the interim

stages. An overview of the pit stages is shown in Figure 6.23.


A peak material movement of 6.0 Mtpa was required to maintain 1.0 Mtpa of ore production. This mining rate is sustained for the first six years in the seven and a half-year mine life. The

annual head grade, ore and waste movements are summarized in Figure 6.24.


6.6.3 Scenario 3 open pit (MII) – 1.0 Mtpa plant throughput



1.0 Mtpa MI RF1 Pit



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Ore Waste Au Grade





This mining rate is sustained for the first 19 years in the 28.8-year mine life.

The annual head grade, ore and waste movements are summarized in Figure 6.26.


6.6.4 Scenario 4 combined open pit and underground – 1.0 Mtpa plant throughput

Scenario 4 is an extension of the mining schedule presented in Scenario 2 and considers mining

of Inferred resources using an underground mining method. Scenario 4 uses MSO stopes generated at a 3.0 g/t Au cut-off grade. The ore production rate from underground method is

487 ktpa. A schematic the open pit and underground stopes are shown in Figure 6.27.

1.0 Mtpa MII RF1 Pit

1.0 Mtpa MII RF0.52 Pit


0.00

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Ore Waste Au Grade



Figure 6.27 Open pit with underground stopes

The annual head grade, ore and waste movements are summarized in Figure 6.28. Ore

production from underground begins in 2028, Figure 6.28 does not show waste tonnage

associated with underground development.





0

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This mining rate is sustained for eight years in the 15.5-year mine life.




Scenario 6 considers mining of a three-stage open pit with Inferred resources included as ore in

the mining inventory. Pit shell 4 (RF0.46) and pit shell 5 (RF0.48) were selected as the interim





0.00

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This mining rate is sustained for five years in the 11.3-year mine life.



6.7 Krasny cash flow analysis


production scenario. The cumulative undiscounted cash flow is presented in Figure 6.33 and cumulative discounted cash flow is presented in Figure 6.34. The financial model for each

scenario which includes mining and processing physicals is in Appendix B. A discount rate of 6% was used. Cash flows for the Micon scenario was derived from the Micon report. The pre-

production years, capital, property tax and profit tax have been removed for comparison

purposes.




0.00

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2.00

2.50

3.00

0

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20,000

30,000

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2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032

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Figure 6.33 Cumulative undiscounted cash flow excluding capital

Figure 6.34 Cumulative discounted cash flow excluding capital

The outcomes of cash flow analysis show benefit in increasing the plant throughput rate from 0.4 Mtpa to 1.0 Mtpa. In the MI open pit scenario, the discounted value increased by 31%,

exclusive of capital expenditure. By increasing the ore production rate, value is realized much




MI open pit captures a significant portion of the mineralization near surface and the remaining portion of the orebody is at much greater depths. A significant amount of waste stripping is

required upfront to expose the mineralization in latter cutbacks to maintain ore production


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compared to the 1.0 Mtpa MII open pit. The transition to underground does not require immediate capital investment as in the MII open pit scenario as a portal can be established



For the current presentation of resource modelling, mineral processing and economics inputs; AMC considers the combined Krasny open pit to underground mining scenario, at a production

rate of 1.0 Mtpa, to produce the highest value balanced against cash flow risk.



7 Exploration target – Vostochny


north-east of the Krasny deposit.

A Whittle 4X block model was generated from the 2018 mineral resource model supplied in the

data room by Micon (bm_vost.csv). The supplied model contained Inferred gold mineralization

only and additional background waste was created using the supplied LIDAR surface,

(TOPO_KRA_LIDAR.dxf). Generated waste blocks were assigned a bulk density of 2.53.

Pit optimizations were completed using Krasny input parameters described in Table 6.2. No allowances have been made for overhaul costs associated with ore transport to the processing

facility, which is likely to be in close proximity to the Krasny deposit.

7.1 Vostochny pit optimization results


resources at 0.4 Mtpa and 1.0 Mtpa plant configurations.

Each optimization run produced a set of nested shells by applying a revenue factor to metal

price, ranging from 0.4 to 1.4 times the base gold price. For each shell the undiscounted cash flow was calculated based on cost and price inputs. As a result, Pit shell 31, revenue factor

= 1.0 (RF1) shell, produced maximum cash flow for both runs. The summary results for 0.4 Mtpa

plant is shown in Table 7.1 and 1.0 Mtpa plant in Table 7.2.



Table 7.1 Pit optimization results for run 1 MII 0.4 Mtpa

Total

Waste

Tonnes

Total Rock

Tonnes

Strip

Ratio

Mining Cost

per Tonnes

of Ore

Incremental

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Processing

Cost

Mining Cost Revenue Undiscounted

Surplus

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce

Tonnes Insitu Au Recovered Au


1 0.40 1,025 0.0 1.83 1.42 0.1 0.1 1.7 3.8 4 2 803 -1 0 3 2 2 2 618

2 0.42 1,020 0.1 1.74 1.40 0.2 0.3 2.2 4.4 5 4 837 -2 0 6 3 3 3 667

3 0.44 1,015 0.1 1.71 1.39 0.3 0.5 2.4 4.7 6 5 854 -2 -1 8 5 4 4 697

4 0.46 1,010 0.3 1.50 1.23 0.7 1.1 2.1 4.3 4 10 928 -6 -1 17 10 9 9 760

5 0.48 1,005 0.5 1.57 1.30 1.6 2.0 3.4 6.0 11 15 953 -8 -3 24 13 13 13 778

6 0.50 1,005 0.6 1.59 1.33 2.2 2.8 3.9 6.8 11 18 971 -10 -4 30 16 15 15 808

7 0.52 1,005 0.6 1.62 1.35 2.9 3.5 4.5 7.6 14 21 988 -11 -5 35 19 17 17 838

8 0.54 1,005 0.8 1.66 1.39 4.1 4.9 5.4 8.8 15 26 1,011 -14 -7 43 22 20 20 858

9 0.56 1,005 0.8 1.66 1.39 4.3 5.0 5.5 8.9 13 27 1,014 -14 -7 44 23 21 21 890

10 0.58 1,005 0.8 1.67 1.40 4.8 5.6 5.9 9.4 22 28 1,024 -15 -8 46 24 22 21 930

11 0.60 1,005 0.9 1.68 1.41 5.4 6.2 6.2 10.0 19 30 1,038 -15 -9 49 25 23 23 960

12 0.62 1,000 0.9 1.68 1.42 5.7 6.6 6.5 10.3 19 31 1,047 -16 -9 51 26 23 23 991

13 0.64 1,000 0.9 1.68 1.42 6.4 7.3 6.8 10.7 18 33 1,063 -17 -10 54 27 24 24 1,028

14 0.66 915 2.2 1.64 1.42 22.5 24.7 10.1 15.4 19 78 1,237 -40 -34 126 52 42 42 1,051

15 0.68 870 3.8 1.54 1.35 39.9 43.7 10.5 15.9 17 126 1,314 -67 -60 205 78 55 51 1,105

16 0.70 870 3.9 1.54 1.34 41.0 45.0 10.5 15.8 14 130 1,318 -69 -62 211 79 56 52 1,121

17 0.72 870 4.1 1.52 1.33 42.9 47.0 10.4 15.8 15 135 1,325 -72 -65 219 82 57 52 1,161

18 0.74 870 4.5 1.50 1.31 47.2 51.7 10.5 15.8 16 146 1,341 -79 -71 238 87 59 53 1,181

19 0.76 855 5.2 1.49 1.30 55.9 61.0 10.9 16.4 20 166 1,370 -91 -84 270 95 63 52 1,218

20 0.78 855 5.3 1.49 1.30 58.3 63.7 10.9 16.4 18 171 1,379 -94 -88 279 97 64 53 1,251

21 0.80 845 5.9 1.46 1.27 64.2 70.1 10.9 16.4 16 185 1,401 -103 -97 301 102 65 52 1,287

22 0.82 845 6.0 1.46 1.27 65.7 71.7 11.0 16.5 20 188 1,406 -105 -99 307 103 66 52 1,315

23 0.84 845 6.2 1.46 1.27 68.9 75.1 11.2 16.8 26 194 1,416 -108 -104 316 104 66 51 1,354

24 0.86 840 6.3 1.45 1.27 71.4 77.7 11.2 16.9 21 199 1,426 -111 -107 324 105 67 50 1,389

25 0.88 835 6.6 1.45 1.27 76.7 83.3 11.6 17.4 28 208 1,443 -116 -115 338 107 67 48 1,421

26 0.90 835 6.7 1.45 1.27 78.0 84.7 11.7 17.5 32 210 1,448 -117 -117 341 108 67 47 1,443

27 0.92 835 6.8 1.45 1.27 80.9 87.7 11.9 17.8 31 214 1,458 -119 -121 349 108 68 46 1,486

28 0.94 835 6.9 1.45 1.27 82.2 89.1 11.9 17.9 27 216 1,463 -120 -123 352 108 68 45 1,517

29 0.96 835 7.0 1.46 1.27 84.2 91.1 12.1 18.1 42 219 1,469 -122 -126 356 109 68 45 1,551

30 0.98 830 7.0 1.45 1.27 85.7 92.8 12.2 18.2 26 221 1,475 -123 -128 360 109 68 44 1,578

31 1.00 830 7.0 1.45 1.27 86.0 93.0 12.2 18.2 44 222 1,476 -123 -128 360 109 68 44 1,606

32 1.02 830 7.2 1.45 1.27 88.3 95.5 12.3 18.3 25 225 1,487 -126 -132 366 109 68 42 1,642

33 1.04 825 7.3 1.45 1.27 91.0 98.3 12.5 18.6 41 228 1,497 -127 -136 372 109 68 41 1,679

34 1.06 825 7.6 1.43 1.25 95.1 102.6 12.5 18.7 20 235 1,516 -132 -142 382 108 68 38 1,703

35 1.08 825 7.6 1.43 1.25 95.4 103.0 12.6 18.7 49 235 1,517 -132 -142 383 108 67 38 1,737

36 1.10 825 8.0 1.46 1.28 114.3 122.3 14.2 21.0 59 255 1,579 -141 -169 415 105 66 27 1,783

37 1.12 825 8.3 1.45 1.27 119.1 127.5 14.3 21.1 24 262 1,599 -146 -176 426 104 66 24 1,798

38 1.14 825 8.4 1.44 1.26 120.6 129.1 14.3 21.1 21 264 1,605 -148 -178 429 103 66 23 1,832

39 1.16 825 8.5 1.44 1.26 121.4 129.9 14.3 21.1 35 265 1,608 -148 -179 430 103 66 22 1,871

40 1.18 825 8.5 1.44 1.26 122.3 130.8 14.4 21.2 52 266 1,611 -149 -181 432 103 66 22 1,906

41 1.20 825 8.6 1.44 1.26 124.2 132.8 14.4 21.3 26 268 1,619 -150 -183 436 102 66 20 1,950

42 1.22 825 8.7 1.44 1.26 126.6 135.2 14.6 21.5 47 270 1,627 -152 -187 440 101 65 19 1,976

43 1.24 825 8.7 1.44 1.26 128.3 137.1 14.7 21.6 46 272 1,633 -153 -189 442 101 65 18 2,001

44 1.26 825 8.8 1.44 1.26 128.9 137.6 14.7 21.7 51 272 1,635 -153 -190 443 100 65 17 2,038

45 1.28 825 8.8 1.44 1.26 129.6 138.4 14.8 21.8 45 273 1,638 -153 -191 444 100 65 17 2,066

46 1.30 825 8.8 1.44 1.26 130.3 139.1 14.8 21.8 52 274 1,640 -153 -192 445 100 65 17 2,086

47 1.32 825 8.8 1.44 1.26 131.8 140.6 14.9 22.0 69 275 1,645 -154 -194 447 99 65 15 2,133

48 1.34 825 8.8 1.44 1.26 132.0 140.8 15.0 22.0 76 275 1,646 -154 -194 448 99 65 15 2,160

49 1.36 825 8.8 1.44 1.26 133.1 141.9 15.0 22.1 82 276 1,650 -155 -196 449 99 65 15 2,197

50 1.38 820 8.9 1.44 1.26 134.8 143.7 15.1 22.3 45 278 1,657 -155 -198 452 98 65 13 2,235

51 1.40 820 9.0 1.44 1.27 141.9 150.9 15.7 23.0 68 283 1,682 -158 -208 461 94 64 8 2,253

Total OrePit Shell Revenue

Factor

Bench




Table 7.2 Pit optimization results for run 1 MII 1.0 Mtpa

Total

Waste

Tonnes

Total Rock

Tonnes

Strip

Ratio

Mining Cost

per Tonnes

of Ore

Incremental

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Processing

Cost


Surplus

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce



1 0.40 1,005 0.5 1.46 1.20 1.0 1.5 2.3 4.5 4 13 755 -6 -2 22 14 14 14 581

2 0.42 1,005 0.6 1.52 1.26 1.9 2.4 3.3 5.9 11 18 783 -7 -3 29 18 18 18 668

3 0.44 1,005 0.7 1.57 1.31 2.8 3.5 4.2 7.1 14 22 807 -9 -5 35 22 21 21 704

4 0.46 1,005 0.8 1.61 1.34 3.7 4.4 4.9 8.1 16 25 827 -10 -6 41 25 24 24 736

5 0.48 1,005 0.8 1.64 1.37 4.3 5.1 5.4 8.8 20 27 839 -10 -7 44 27 25 25 760

6 0.50 1,005 0.8 1.63 1.37 4.5 5.3 5.4 8.9 11 28 846 -11 -7 45 27 26 26 801

7 0.52 1,000 0.9 1.65 1.39 5.2 6.0 5.9 9.6 22 30 861 -11 -8 49 29 27 27 834

8 0.54 1,000 0.9 1.65 1.38 5.7 6.7 6.2 9.9 16 32 876 -12 -9 52 30 29 29 862

9 0.56 995 1.0 1.66 1.39 6.2 7.1 6.5 10.3 24 33 886 -13 -10 53 31 29 29 894

10 0.58 915 2.2 1.61 1.39 22.0 24.2 9.8 15.0 18 77 1,060 -29 -33 125 62 57 57 915

11 0.60 870 3.9 1.52 1.33 40.5 44.4 10.3 15.6 16 129 1,133 -51 -61 209 97 84 82 956

12 0.62 870 4.2 1.51 1.32 43.1 47.3 10.3 15.6 16 136 1,142 -54 -65 221 102 88 84 998

13 0.64 865 4.5 1.49 1.30 46.7 51.3 10.3 15.6 15 146 1,154 -59 -71 237 108 92 88 1,017

14 0.66 855 5.1 1.46 1.28 52.2 57.2 10.3 15.6 16 160 1,174 -65 -79 260 116 98 92 1,060

15 0.68 850 5.7 1.44 1.26 59.5 65.2 10.5 15.8 18 177 1,198 -73 -90 288 125 104 97 1,091

16 0.70 845 5.9 1.44 1.26 63.3 69.2 10.7 16.1 22 185 1,209 -76 -95 300 129 107 98 1,129

17 0.72 845 6.1 1.44 1.26 65.2 71.2 10.7 16.2 21 189 1,215 -78 -98 307 130 108 99 1,154

18 0.74 845 6.3 1.43 1.25 67.9 74.2 10.8 16.3 20 194 1,225 -81 -102 316 133 110 100 1,193

19 0.76 845 6.3 1.43 1.25 69.1 75.5 10.9 16.4 30 196 1,229 -81 -104 319 134 110 100 1,223

20 0.78 835 6.6 1.43 1.25 73.7 80.3 11.2 16.8 25 204 1,244 -85 -111 332 137 112 101 1,250

21 0.80 835 6.7 1.43 1.25 74.4 81.1 11.2 16.8 18 206 1,247 -85 -112 335 137 113 101 1,286

22 0.82 835 6.8 1.44 1.26 78.3 85.1 11.5 17.3 39 211 1,260 -87 -117 344 139 114 101 1,313

23 0.84 835 6.9 1.44 1.26 81.0 88.0 11.7 17.5 31 216 1,269 -89 -121 351 140 115 100 1,347

24 0.86 835 7.0 1.44 1.26 81.8 88.7 11.8 17.6 47 217 1,271 -89 -122 352 140 115 100 1,390

25 0.88 830 7.1 1.44 1.26 84.2 91.3 11.9 17.8 30 220 1,281 -91 -126 358 141 115 99 1,415

26 0.90 830 7.2 1.44 1.26 87.3 94.6 12.1 18.1 30 225 1,293 -93 -131 365 142 116 99 1,447

27 0.92 830 7.5 1.42 1.24 90.3 97.7 12.1 18.0 17 230 1,306 -96 -135 373 143 116 98 1,480

28 0.94 825 7.6 1.42 1.24 91.9 99.4 12.2 18.2 30 232 1,313 -97 -137 377 143 116 98 1,520

29 0.96 825 7.6 1.42 1.24 93.1 100.7 12.2 18.3 34 233 1,317 -97 -139 379 143 116 98 1,550

30 0.98 825 7.9 1.40 1.23 97.6 105.5 12.4 18.4 23 240 1,337 -101 -146 390 143 117 96 1,567

31 1.00 825 8.0 1.40 1.22 99.5 107.5 12.4 18.5 23 242 1,345 -102 -148 394 144 117 95 1,605

32 1.02 825 8.1 1.40 1.22 101.4 109.5 12.5 18.7 38 245 1,352 -103 -151 398 143 117 94 1,652

33 1.04 825 8.5 1.43 1.26 120.2 128.7 14.1 20.9 62 264 1,413 -109 -178 429 143 116 86 1,674

34 1.06 825 8.5 1.43 1.26 121.0 129.6 14.2 20.9 44 265 1,415 -110 -179 431 142 116 85 1,700

35 1.08 825 8.6 1.43 1.25 122.5 131.1 14.2 21.0 23 267 1,421 -111 -181 434 142 116 85 1,733

36 1.10 825 8.7 1.42 1.25 123.7 132.4 14.2 21.0 31 268 1,426 -111 -183 436 142 116 84 1,767

37 1.12 825 8.7 1.43 1.25 125.3 134.0 14.4 21.2 55 270 1,431 -112 -185 439 142 115 83 1,806

38 1.14 825 8.8 1.43 1.25 126.4 135.2 14.4 21.3 46 271 1,435 -112 -187 440 142 115 82 1,839

39 1.16 825 8.8 1.43 1.25 127.6 136.4 14.5 21.4 62 272 1,439 -113 -188 442 141 115 82 1,871

40 1.18 825 8.8 1.43 1.25 129.1 138.0 14.6 21.6 55 273 1,444 -113 -190 445 141 115 81 1,903

41 1.20 825 8.9 1.43 1.25 130.1 139.0 14.7 21.7 57 274 1,448 -114 -192 446 141 115 80 1,933

42 1.22 825 8.9 1.43 1.25 130.4 139.2 14.7 21.7 22 275 1,449 -114 -192 447 141 115 80 1,964

43 1.24 825 8.9 1.43 1.25 131.2 140.1 14.7 21.7 41 275 1,452 -114 -193 448 140 115 80 2,004

44 1.26 825 8.9 1.43 1.25 132.7 141.6 14.9 21.9 68 277 1,458 -115 -195 450 140 114 79 2,035

45 1.28 825 9.0 1.43 1.25 133.5 142.5 14.9 22.0 55 277 1,461 -115 -197 451 139 114 78 2,062

46 1.30 820 9.0 1.43 1.25 134.4 143.3 15.0 22.0 54 278 1,464 -115 -198 452 139 114 78 2,096

47 1.32 820 9.1 1.44 1.26 142.1 151.2 15.6 22.9 71 284 1,492 -117 -209 462 136 112 72 2,133

48 1.34 820 9.1 1.44 1.26 142.7 151.9 15.6 22.9 53 285 1,494 -117 -210 463 136 112 72 2,163

49 1.36 820 9.2 1.43 1.26 143.3 152.4 15.6 22.9 36 285 1,497 -118 -210 464 135 112 71 2,209

50 1.38 820 9.2 1.43 1.26 143.8 153.0 15.7 23.0 45 285 1,499 -118 -211 464 135 112 71 2,235

51 1.40 820 9.2 1.43 1.26 144.7 154.0 15.7 23.1 55 286 1,502 -118 -212 465 135 111 70 2,259


Factor

Bench




Figure 7.1 and Figure 7.2 show the relationship between incremental pit shells generated by the

optimization for the 0.4 Mtpa and 1.0 Mtpa runs respectively for different revenue factors, pit

inventory and cash flow.

Figure 7.1 Pit optimization results for run 1 MII 0.4 Mtpa

Figure 7.2 Pit optimization results for run 1 MII 1.0 Mtpa

0

20

40

60

80

100

120

140

160

0

20

40

60

80

100

120

0.4

0

0.4

4

0.4

8

0.5

2

0.5

6

0.6

0

0.6

4

0.6

8

0.7

2

0.7

6

0.8

0

0.8

4

0.8

8

0.9

2

0.9

6

1.0

0

1.0

4

1.0

8

1.1

2

1.1

6

1.2

0

1.2

4

1.2

8

1.3

2

1.3

6

1.4

0

To

nn

es (

Mt)

Un

dis

co

un

ted

S

urp

lus ($

M)

Revenue Factor

Ore Waste Undisc.Surplus

0

20

40

60

80

100

120

140

160

180

0

20

40

60

80

100

120

140

160

0.4

0

0.4

4

0.4

8

0.5

2

0.5

6

0.6

0

0.6

4

0.6

8

0.7

2

0.7

6

0.8

0

0.8

4

0.8

8

0.9

2

0.9

6

1.0

0

1.0

4

1.0

8

1.1

2

1.1

6

1.2

0

1.2

4

1.2

8

1.3

2

1.3

6

1.4

0

To

nn

es (

Mt)

Un

dis

co

un

ted

S

urp

lus ($

M)

Revenue Factor




7.2 Vostochny production scheduling


production to the processing plant. AMC has considered a nominal plant throughput rate of


The RF1 pit shell was selected as the ultimate pit in each production scenario, pit staging was considered to defer waste stripping and maximize cash flow during early years of production.

Staging was determined by visual inspection of interim pit shells with consideration for minimum mining width. A maximum vertical advance rate of 50 m per annum has been used for

scheduling. Stockpiling of ore has not been considered, but is likely to achieve a superior

economic outcome, following more detailed study work.

Two scenarios were produced based on 0.4 Mtpa and 1.0 Mtpa processing plant capacity

configurations.

7.2.1 Scenario 1 open pit (MII) – 0.4 Mtpa plant

Scenario 1 considers mining of a four-stage open pit with Inferred resources included as ore in the mining inventory. Pit shell 9 (RF0.56), pit shell 14 (RF0.66) and pit shell 17 (RF0.72) were

selected as the interim stages. An overview of the pit stages is shown in Figure 7.3.



This mining rate is sustained for the first 10 years in the 17.4-year mine life. The annual head

grade, ore and waste movements are summarized in Figure 7.4.



0.4 Mtpa MII RF0.56 Pit0.4 Mtpa MII RF0.66 Pit




7.2.2 Scenario 2 open pit (MII) – 1.0 Mtpa plant

Scenario 2 considers mining of a three-stage open pit with Inferred resources included as ore in

the mining inventory. Pit shell 9 (RF0.56) and pit shell 11 (RF0.60) were selected as the interim




This mining rate is sustained for four years in the nine-year mine life. The annual head grade,

ore and waste movements are summarized in Figure 7.6.

0

0.5

1

1.5

2

2.5

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

He

ad

Gra

de

(g

/t)

To

nn

es (kt)

Year

Ore Waste Au Grade







7.3 Vostochny cash flow analysis


production scenario. The cumulative undiscounted cash flow is presented in Figure 7.7 and cumulative discounted cash flow is presented in Figure 7.8. The financial model for each scenario

which includes mining and processing physicals is in Appendix C. A discount rate of 6% was

used.


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0

5000

10000

15000

20000

25000

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

He

ad

Gra

de

(g

/t)

To

nn

es (kt)

Year

Ore Waste Au Grade

-20

0

20

40

60

80

100

120

140

2020 2022 2024 2026 2028 2030 2032 2034 2036Un

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ash

Flo

w (

$M

)

Year





The outcomes of cash flow analysis show a three-year period where the project is approximately

cash flow neutral at a plant throughput rate of 1.0 Mtpa due to high material movement. There is a difference of approximately US$32M in discounted cash flow between the 0.4 Mtpa and




-10

0

10

20

30

40

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90

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w (

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)

Year




8 Combined Krasny and Vostochny production scenario

AMC has evaluated a combined production scenario of the Krasny deposit and Vostochny mineral

occurrence. This scenario can be considered as an extension of the Krasny open pit and underground scenario presented in section 6.5.4, with development of the Vostochny open pit

beginning in 2030. Development of the Vostochny open pit is intended to supplement the

underground ore production from Krasny, rather than being operated as a standalone mining operation. Ore sourced from Vostochny will aid in maintaining the utilization of the processing

plant capacity of 1.0 Mtpa for the life of the combined Krasny and Vostochny mining operations.

The Krasny underground mine will provide a nominal 0.487 Mtpa of ore production for

approximately nine years. Previous analysis of Vostochny showed that a total material movement of 20 Mtpa was required to sustain ore production at 1.0 Mtpa without supplementation from

external sources. This suggests that sustaining 1.0 Mtpa of ore production after completion of Krasny underground would require significant capital investment due to the additional

requirements in mining capacity. As such, pit shell 17 (RF0.72) was selected as the ultimate pit

to align with the Krasny underground inventory and minimize reinvestment in excess capital.

A Milawa analysis was completed to determine the required material movement profile to deliver

ore production at a rate of 0.513 Mtpa using pit shells generated from the 0.4 Mtpa pit optimization run. Pit shell 9 (RF0.56) and pit shell 14 (RF0.66) were selected as interim stages.

AMC notes that Milawa analysis of Krasny and Vostochny were completed separately, with the results combined to produce a basic compatible joint mining operation. Further iterations of the

combined operations, with increased level of detail, are likely to enhance profitability.

The annual head grade, ore and waste movements are summarized in Figure 8.1. Ore production

from Vostochny begins in 2027 and ore production from Krasny underground begins in 2028,

Figure 8.1 does not show waste tonnage associated with underground development.

Figure 8.1 Combined Krasny and Vostochny production profile

8.1 Combined Krasny and Vostochny cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of the combined Krasny and Vostochny production scenario. The cumulative undiscounted cash flow is presented

in Figure 8.2 and cumulative discounted cash flow is presented in Figure 8.3. The financial model

for this scenario which includes mining and processing physicals is in Appendix D. A discount

rate of 6% was used.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2020202120222023202420252026202720282029203020312032203320342035

He

ad

Gra

de

(g

/t)

To

nn

es (kt)

Year

Ore Waste Au Grade





8.2 Combined Krasny and Vostochny cash flow comparison

AMC has used Micon’s assessment of capital costs in the 2018 Mineral Resource and Ore Reserve report to provide high-level indicative cash flows inclusive of capital costs for each production

scenario. Micon’s capital cost estimates were based on an operation with 0.4 Mtpa plant capacity

and 5 Mtpa mining capacity are shown in Figure 8.4.

-

50

100

150

200

250

300

350

2020 2022 2024 2026 2028 2030 2032 2034 2036

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)

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)

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Figure 8.4 Micon capital cost schedule

Source: Krasny_Final_Report_ENG_signed



AMC has used the six-tenths rule to scale Micon’s capital estimates to cover the spectrum of

processing and mining rates that have been presented. Different configurations of plant and mining equipment would be more appropriate for larger scale operation. The scalability of mining

equipment has not been considered in this cash flow analysis and a capital cost schedule has not been produced. This rudimentary approach to the capital analysis provides a basic comparative



The capital costs associated with open pit have been applied as a lump sum in 2020 for each production scenario and underground development capital costs applied as a lump sum in 2030

for the relevant scenarios for comparison purposes, which are shown in Table 8.1.

The joint Krasny and Vostochny cumulative undiscounted cash flow including capital is presented

in Figure 8.5 and cumulative discounted cash flow including capital is presented in Figure 8.6.

A discount rate of 6% was used, which is the same rate utilized in the Micon 2018 Ore Reserve

reporting.

Table 8.1 Capital costs for scenario comparison

Figure 8.5 Undiscounted cash flow including capital

Item Unit Micon Krasny 0.4

Mtpa MI Open

Pit

Krasny 1.0

Mtpa MI Open

Pit

Krasny 1.0

Mtpa MII Open

Pit

Krasny 1.0 Mtpa

MI Open Pit +

Underground

Krasny 2.0

Mtpa MII Open

Pit

Krasny 3.0

Mtpa MII Open

Pit

Krasny 1.0 Mtpa MI Open

Pit + Underground +

Vostochny Open Pit

Plant Capacity Mtpa 0.4 0.4 1 1 1 2 3 1

Mining Capacity Mtpa 5 3 6 18 6 35 60 8

Design and Engineering US$'000 2,349 2,349 2,349 2,349 2,349 2,349 2,349 2,349

Plant Equipment US$'000 7,183 7,183 12,447 12,447 12,447 18,866 24,063 12,447

Plant Construction US$'000 18,997 18,997 32,919 32,919 32,919 49,896 63,639 32,919

Mining Equipment US$'000 9,703 7,142 10,825 20,926 10,825 31,186 43,094 12,864

Renewal of Fixed Assets US$'000 767 565 856 1,654 856 2,465 3,406 1,017

Reclamation US$'000 3,000 2,208 3,347 6,470 3,347 9,642 13,324 3,977

Underground Development US$'000 0 0 0 0 41,862 0 0 41,862

Total US$'000 41,998 38,443 62,742 76,766 104,604 114,405 149,874 107,436

-250

-150

-50

50

150

250

350

450

550

650

2020 2025 2030 2035 2040 2045 2050

Un

dis

co

un

ted

C

ash

Flo

w (

$M

)




Figure 8.6 Discounted cash flow including capital

8.3 Recommendations for future work





• Dilution and ore loss analysis. There are areas of Krasny and Vostochny orebodies which

contain narrow vein mineralization where the application of dilution and ore loss factors in Whittle is not appropriate. Some areas of the pit optimization are being driven by narrow

ore zones that cannot be selectively mined to the level of accuracy suggested by these




pit scenarios.


scenarios.


8.4 Key financial outcomes

Following the completion of Study’s alternative productions scenarios, and associated Project cash flow analysis, Kopy requested that AMC update the Project sensitivity analysis to reflect an

updated nominated gold price of US$1,300/oz.

The results from the updated project cash flow, for the combined Krasnoe and Vostochny

production scenario, is shown below in Table 8.2.

-200

-150

-100

-50

0

50

100

150

200

250

300

2020 2025 2030 2035 2040 2045 2050

Dis

co

un

ted

C

ash

Flo

w (

$M

)




Table 8.2 Krasnoe and Vostochny base case sensitivity analysis


Gold price (USD/Oz) 1,200 1,250 1,300 1,350 1,400


IRR (%) 19 22 26 29 32


DCF, pre-tax (MUSD) 118.2 104.2 91.9 80.9 71.2


DCF, pre-tax (MUSD) 51.6 77.9 104.2 130.6 156.9

IRR (%) 16 21 26 30 34

A detailed memorandum has been produced to report this updated Project sensitivity work and the outcomes of the wider study results. A copy of this memorandum, Krasny Scoping Study

mine production scenarios and key financial outcomes 29 May 2019, is included in Appendix E

of this report.



9 Environmental aspects

9.1 Introduction

This section of the Study report provides an outline of international financing and in-country environmental regulation, describes environmental and social conditions of the Project and

analyses potential key issues for further project development. The findings provided are based

on relevant information gathered during a short desk-top review of the data and reports provided

by Kopy and others.

9.2 Regulatory framework

9.2.1 Russian environmental regulation

Environmental protection in Russia is enshrined in primary legislation, principally the 2002 Federal law on environmental protection. This Federal Law proclaims a “polluter pays” principle,

regulates the requirements for the environmental permits and requires that an assessment of environmental impacts should be undertaken for any project that has the potential to impact the

environment, either directly or indirectly.

Detailed procedural measures, permitting procedures and the basis for environmental quality standards are provided in subsidiary legislation, which is formed by number of Federal laws and

other regulations, as well as national standards. The key legislative documents are listed below

(all as amended):

• Federal law on environmental protection No.7-FZ.

• Water code No.74-FZ.

• Land code No.136-FZ.

• Forestry code No.200-FZ.

• Federal law on ambient air protection No.96-FZ.

• Federal law on production and consumption wastes No.89-FZ.

• Subsurface law of the Russian Federation No.2395-1.

• Federal law on animal environment No.52-FZ.

• Federal law on specially protected nature territories No.33-FZ.

• Federal law on industrial safety of dangerous industrial objects No. 116-FZ.

• Federal law on public sanitation and epidemiology No.52-FZ.

• Federal law on environmental expertise No.174-FZ.

• Guidelines on environmental impact assessment for planned economic and other activities

in the Russian Federation (guidelines on OVOS), approved by the resolution of Russian

Federation committee on environmental protection No. 372 dated 16 May 2000.

• Provisions of the Russian government on rehabilitation of land, removal, preservation and

rational usage of fertile soil No.140.

Like laws, regulatory documents are subdivided by environmental components (atmospheric air,

surface water and ground water, vegetation and wildlife, land, subsurface, soils, etc.) and by different aspects of impact (waste, protected natural territories, etc.). The Russian

environmental protection system is based on environmental standards (criteria) of environment quality. There are two types of criteria, ambient environment quality criteria and discharge

criteria (admissible volumes and characteristics of emissions, discharge, waste, etc.).

According to the Russian environmental legislation decision making process related to all stages of the project development, including exploration, construction and operation, should be

supported by consideration of the environmental issues. At the design stage, an environmental impact assessment is performed, and impact mitigation activities are proposed. The impact

assessment results are reported in the Russian ESIA report (hereafter abbreviation OVOS).



For every stage of a mining project development (geological exploration, designing, construction,

operation) the Companies must apply for, get and update the permitting environmental documentation. On the operational stage a company must develop annual plans of the

environmental measures and undertake environmental monitoring and control of the pollutants

releases.

Requirements for mine closure and land reclamation are specified in the Forestry Code, Subsurface law of the Russian Federation, and in other regulatory Russian documents, such as

state standards (GOST) and guidelines. The mined deposits should be decommissioned in accordance with the plans approved by governmental authorities and the disturbed lands should

be restored. A conceptual closure plan shall be included in the set of design documentation, but

detailed closure plan is required only one year before the actual closure takes place.

There have been certain significant recent changes to Russian environmental regulation:

• The categorization of industrial facilities was introduced (which is like categorization of WB group and EBRD) with “industrial facilities with sever negative impacts” are categorized as

objects of I category. This put most of the mining companies on the federal supervisory level, while companies with the moderate and low impacts will be supervised on regional

level.

• From 1 January 2019, all category I companies must obtain the new complex

environmental permission (instead of three separate permissions for emissions, discharges

and waste disposal). Permission will be granted for seven years and may contain temporary

limits with obligations to improve environmental performance.

• New coefficients of payments will be introduced from 1 January 2020 in order to stimulate

companies to use the Best Available Technologies (BAT).

The number of best available technology (BAT) Reference Books have been developed and

published, including:

• Waste disposal BAT.

• Waste treatment (except burning) BAT.

• Mining – general processes and methods

• Emissions purification BAT.

• Waste water treatment BAT.

• General principles of industrial environmental control and its metrological insurance and

others.

9.2.2 International financing requirements

An international approach to the management of social and environmental risks is described in

the Equator Principles (June 2013). As of January 2019, the Equator Principles (EPs) were signed

by 93 funding organizations from 37 countries.

The EP were developed by a number of leading financial institutions, including the International

Finance Corporation (IFC), to provide an approach to determine, estimate and manage environmental and social risks in project financing for new and upgraded projects. The intention

of the principles is to ensure that projects are developed, operated and closed in a site-specific manner that is socially responsible and reflects sound environmental management practices.

Mining projects are typically classified as Category A according to EP classification and therefore

require a full impact assessment.

To provide guidance on how these principles can be made specific to an individual project, the IFC developed a number of standards and guidelines that reflect the best international practice



applicable to the projects. There are the IFC Performance Standards (January 2012), as listed

below:

• Performance standard 1: assessment and management of environmental and social risks

and impacts.

• Performance standard 2: labor and working conditions.

• Performance standard 3: resource efficiency and pollution prevention.

• Performance standard 4: community health, safety, and security.

• Performance standard 5: land acquisition and involuntary resettlement.

• Performance standard 6: biodiversity conservation and sustainable management of living

natural resources.

• Performance standard 7: indigenous peoples.

• Performance standard 8: cultural heritage.

The EP require observance of the World Bank Group and IFC (part of World Bank Group) Environmental, Health and Safety Guidelines (EHS). These include general guidelines and

guidelines for specific industry sectors, which provide examples of good international practice, typical impacts arising in different stages of project development and give recommendations for

their elimination/mitigation, along with efficient performance and monitoring parameters.

Among the EHS guidelines applicable to the Krasny project are:

• The General EHS Guidelines.

• The EHS guidelines for mining.

• The EHS guidelines for waste management.

• The EHS guidelines for water and sanitation.

9.3 The Project environmental management and studies

Although the goal of the Project is to manage the environmental issues in accordance with international best practice, currently all operations are managed according to Russian regulatory

requirements4. AMC has not analysed an efficiency of the Company’s environmental

management system as part of this work.

Some environmental baseline studies have been undertaken for the Project. Following the mine

licence5 requirement, “Program of complex environmental baseline assessment on site at Krasny” was developed in 2012. The Program assumed investigation of key environmental media

and collection of comprehensive environmental data on climate, flora and fauna, surface and ground water quality, air quality, radiation, social-economic studies, archaeology. However,

according to the Kopy, the following studies and measurements have been done sporadically and the results have not been properly reported, the results have not been provided to AMC for

the review. The later reports, such as “Report on the analysis of the environmental baseline conditions on site Krasny” 2014 or TOMS Scoping Study 2017, contain some data interpretation

and summary, so this environmental review is based on the available interpretive data.

AMC understands that no environmental or social studies have been undertaken in accordance

with international requirements.

9.4 Environmental and social settings

Environmental and social settings are described based on the data available in the “Report on

the analysis of the environmental baseline conditions on site “Krasny”, 2014.

4 The Company web-site http://kopygoldfields.com/operations/environment/ 5 Licence ИРК 02685 БР



The Project is located within the Patomsk highland in the relatively remote area in the upstream

of the Bodaybo river. The nearest settlement village Artyemovsky is located in 15 km, and the district centre town Bodaybo in 75 km from the site. Road Bodaybo-Kropotkin-Perevoz is crossing

the site, some gravel roads used by other alluvial miners also cross the site.

The locality around the Project is mountainous and largely forested. The absolute altitudes

changes between 800 m to 1,200 m ASL (above sea level) with relative altitudes 500 m to

600 m. Rivers valleys are wide, often swampy.

The area around the Project is traditionally associated with mining, and there are number of active mining operations in the vicinity, including extensive alluvial workings along the drainage

valleys in the immediate area. As a result, the lands of the Project area have significant historical

disturbance forming technogenic landscape as shown on the Figure 9.1.

Figure 9.1 Land disturbance in Krasny stream valley

Climate of the region is extreme continental, with difference between absolute minimum and maximum temperatures of 93°C. Annual precipitations are 370 mm to 500 mm, the

precipitations irregular with maximum in July and minimum in February. Average monthly

temperatures and precipitations based on the Svetly weather station records are shown in the

Figure 9.1, wind rose is demonstrated on the Figure 9.2.

Table 9.1 Average monthly temperatures and precipitations

Parameters Months

I II III IV V VI VII VIII IX X XI XII

Average

temperatures (°C) -27.7 -22.8 -14.2 -3.3 5.9 14.0 16.8 13.5 5.4 -4.0 -17.5 -26.3

Precipitations (mm) 9 7 5 13 35 63 82 70 55 21 15 10



Figure 9.2 Average annual wind rose

The project area flora and fauna forest associations are typical for East Siberia taiga zone, prevalent on the vast surrounding territories. Although reportedly no special protected species

have been registered on the Project site, this statement has not been confirmed by a special study. Besides, number of protected species have been registered within Bodaybo district. On

the Project site itself forest is practically absent within the project area, due to the removal of

trees associated with placer mining operations.

Permafrost is widely distributed with seasonal thawing layer of not more than 2 m on the southern slopes. Soils on the project area are barren due to the strong climate conditions and

permafrost, often destroyed by previous and current mining activity. Soils and vegetations

demonstrate vertical zoning (changing the compositions with the altitude).

The Bodaybo River and its tributaries, the Krasny, Teply and Mokry Streams, are the main

waterways in the area. The Bodaybo river flowing about 500 m from the Project site, and the streams cross the Project site and freeze almost till the bottom over the winter. Water regime

of all watercourses is naturally irregular with significant water flow fluctuations over the year but

impacted by the alluvial mining as well.

Sulphide mineralization is typical over the entire ore field with a wide distribution, mainly represented by pyrite. Key elements associated with gold within Krasny deposit are silver,

molybdenum, lead, zinc, arsenic. Alluvial horizon contains elevated (abnormal) concentrations

of the same elements plus copper, mercury, nickel, cobalt. All sulphide zones contain elevated concentrations of arsenic. Surface water quality data (TOMS, 2017) and description of mine

waste water quality also demonstrate elevated concentrations for number of elements as a result of metal leaching, although there is no evidence for the acid drainage, which is common issue

related to sulphides oxidation. All those elements in elevated concentrations are toxic for the environment. Although special environmental geochemical investigation has not been

undertaken for the acid mine rock drainage and metal leaching (ARDML) assessment, available data let assume that special studies with following design and mitigation measures most likely

will be required to manage the ARDML impacts.

9.5 Environmental and social issues and risks

Based on the available data, the items listed below have been identified as key issues or risks,

which means that either potentially require additional financing or may affect the Project

schedule.

• Environmental and social baseline studies and impact assessment – reportedly, environmental baseline studies for Krasny deposit site were undertaken in 2012, but the

report has not been provided to AMC for the review. Additional environmental and social baseline studies should be undertaken for further project development, but the scope and

the duration of the studies will differ depending on if the Project should meet only Russian

requirements or both Russian and international requirements and practice. Following



baseline studies, environmental and social impact assessment either on Russian or both

on Russian and international requirements should be undertaken starting from the Scoping Impact Assessment on the pre-feasibility study stage. If there is a need to meet

international requirements, then the studies should be scheduled and organized carefully

to avoid project delays, especially taking the seasonal limitations into account.

• ARDML water quality – geochemistry of the ore (and potentially host rock) let assuming that processes of acid drainage and metals leaching will take place during the Project

development. If not managed timely and carefully, it may cause significant additional resources for water treatment and long-term legal obligations for the Company. Main

sources of ARDML are open pit, waste rock dumps and tailings facility. Current project

design (TOMS 2017) suggests mine waste water settling in the pond with following additional treatment with module facility «FloTenk-OP-OM-SB». However, the treatment

technology of this facility provides treatment for suspended solids and oils only, so reported acceptable metals concentrations in the discharged water are precarious. Waste water

quality issue should be investigated with the following development of proper treatment

scheme.

• ARDML waste rock usage limitation – according to TOMS 2017 waste rock will be used for the road construction, surface profiling and other construction purposes. If ARDML

potential for waste rock is confirmed it cannot be used for the construction and it must be

considered in the Project design.

• Mine closure and costs estimation – disturbed land should be rehabilitated for the

further usage according to both Russian legislation and international good practice, but there is significant difference in closure planning process. Russian legislation (as well as

Krasny mining licence) requires closure plan to be developed only one year before the closure, although the need to provide the mine closure is mentioned in the Russian design

documentation. International requirements and practice consider closure planning as part of the project design process, which starts on early stage of a project development with

conceptual closure plan and continue developing in line with the overall project progress.

Accuracy of the mine closure costs depends on the stage of the Project development, but

the cost should be included into the financial model.

9.6 Studies required for the next stages of the Project development

To ensure the project’s compliance with Russian and international standards, including the

Equator Principles and IFC Performance Standards, additional environment and social studies are required including environmental and social impact assessment (ESIA) process. The

outstanding tasks are described below. Generally, the overall ESIA process meets the following

phases:

• Phase 1: environmental and social scoping study (usually is in line with pre-feasibility stage

of the project development).

• Phase 2: environmental and social baseline studies.

• Phase 3: impact assessment stage and management system framework development

phase.

Stakeholders engagement is running in line with the project development and environmental and social impact assessment (ESIA) process. Completion of the ESIA programme depends on

timely input of the project engineering design.

9.6.1 Environmental scoping study

Scoping environmental and social impact assessment allows recognize and preliminary assess

key environmental problems which might appear during project implementation with high possibility and help planning further studies more carefully. Scoping assessment is in line with



international approach and is usually required project design details adequate to the pre-

feasibility study level. Usually Scoping assessment include the following:

• Collection and analysis of available environmental and social data (especially collection all

primary, fieldwork data), including brief review of data taken from public sources.

• Site visit by environmental specialist.

• Stakeholders mapping, meetings and discussion of the Project with representatives of

some regulation and supervision bodies and other stakeholders, receiving some feedback.

• Meetings and discussions of environmental and social aspects with the Company’s staff on

site.

• Preliminary impacts identification and evaluation based on the design options valid at the

time of assessment.

• Preparation of a report on scoping environmental and social impact assessment with

specification of the key factors that may influence estimation and classification of ore reserves and project development. The report will contain a plan for detailed impact

assessment, and a preliminary plan of consultations with the interested parties.

9.6.2 Baseline studies

As mentioned above, some baseline studies were conducted in the Project area during last several years, but the studies were sporadic, and reports are not available. Data made available

are not adequate to complete the impact assessment process and develop appropriate mitigation

measures. To collect the information required, detailed baseline studies shall be implemented,

which will comply with Russian and international standards.

The key difference between Russian and international approach to the environmental baseline studies is the scope of the study and quality of the received data. First, any external

infrastructure related to the Project is considered as integral part of the Project and is subject to similar study. Secondly, international standards require the timing of baseline studies to be

adequate to understand all potential seasonal changes of the environment. In view of the Krasny Project climate conditions, field work associated with the full-scale baseline studies will take at

least eight months (one calendar year but taking account of long winter with similar conditions).

Some of the required studies do not require seasonal characterization (for example socio-

economic) and therefore can be completed within a shorter time frame.

On the initial stage overall baseline studies program and detailed Terms of Reference (ToR) for each discipline should be developed. To ensure international standards are adhered to, the

preparation of the ToR will include appropriate sampling methodologies, quality

assurance/quality control (QA/QC) techniques and reporting requirements.

9.6.3 Stakeholders engagement

Proper stakeholder’s engagement process is one of the key requirements of the international

financing institutes, which expect full, prior and informed consultations are held as part of the

impact assessment process and that consultations continue over the life of project, including the

closure stage.

The process starts from the stakeholder’s identification process, through the development of the Initial Stakeholders Engagement Plan to the initial consultation with all identified stakeholders

to gather issues of concern relating to the proposed project. Stakeholder issues represent an important input to defining the scope of the environmental and social impact assessment process

should ideally be considered before the scoping process can formally be considered complete.

Once the impact assessment process is complete, a further round of feedback consultations will

be required to fully meet international standards. This stage enables the study team to present

the results of the impact assessment process to stakeholders and seek their comments on the proposed management measures. The Initial Stakeholders Engagement Plan will be updated



regularly following the developing of the engagement process throughout the operational stage

of the Project.

9.6.4 Full-scale impact assessment and management system

Full-scale impact assessment according with international requirements should be done as a part of the Feasibility Study development, when final project description is fairly well defined. The

impact assessment will be done based on the data received as a result of the environmental and social baseline studies and on the detailed project description provided by the project engineers.

Different methods will be used for the assessment, including modelling and qualitative evaluation based on professional judgement. The exact scope of work will be determined based on the

results of baseline studies.

According to IFC Performance Standard 1, the company should develop and support an environmental and social management system to manage the environmental and social impact

and risks identified during the impact assessment process. The management of these impacts and risks is a continuous process through all stage of project development – from construction,

operation, closure and beyond the closure. Like other management systems, this system is cyclic

and includes regular review for efficiency assessment. According to Performance Standard 1:

• A dynamic, continuous process initiated by management and involving communication between the client, its workers, and the local communities directly affected by the project

(the affected communities).

• Based on the business management process of “plan, implement, check, and act”.

• Entails the thorough assessment of potential environmental and social impacts and risks

from the early stages of project development.

• Provides order and consistency for mitigating and managing these on an ongoing basis.

9.7 Conclusions

Based on the review of the provided information AMC has not found any environmental or social

fatal flaws or risks that could prevent or significantly delay the Project. AMC considers that the issues mentioned above are manageable and, if addressed appropriately and timeously, will not

constitute a major risk.

AMC recommends that Kopy develops and implements an environmental health and safety management system which is structured towards developing a proactive approach to the

management of environmental impacts and risks.

Due to the recent changes of the Russian regulatory requirements AMC strongly recommend

developing the environmental and social management procedures and plans taking the new

regulation into account.



10 References

10.1 Mineral processing

Micon International Limited, August 2018. Mineral Resources and Ore Reserves Estimate of the Krasny Gold Deposit and the Vostochny Mineral Occurrence, Irkutsk Region, Russian Federation.

A technical report prepared for Kopy Goldfields AB.

10.2 Mineral resource model

Micon 2018. Mineral Resources and Ore Reserves Estimate of The Krasny Gold Deposit and the

Vostochny Mineral Occurrence, Irkutsk Region Russian Federation. Report by Micon International

Co Limited to Kopy Goldfields AB.

10.3 Environmental aspects

Program for complex assessment of the environmental baseline conditions for the site Krasny

(licence IRK 02685), Irkutsk oblast, Bodaybo district, OOO “Krasny”, 2012.

Report “Mineral resources and ore reserves estimate of the Krasny gold deposit and the

Vostochny mineral occurrence in Irkutsk region Russian Federation”, Micon International, 2018.

Report “Mineralogical and petrographical investigation of ore and host rocks of the site “Krasny”,

Mineralogical Institute of Ural Branch of Academy of Sciences of Russian Federation, 2012.

Report “On analysis of the environmental baseline conditions on the site “Krasny”, management

company Kopylovskoye, Bodaybo, 2014.

Report “Technical-economic comparison of two mine development options (open pit and

combined) for Krasny deposit site in Bodaybo district of Irkutsk oblast”, TOMS, 2017.

Report “Technical-economic estimation of GOK construction for gold ore deposit “Krasny”,

Irgiredmet, 2016.

10.4 Geotechnical

Bieniawski ZT 1989. Engineering rock mass classifications, Wiley, New York.

Hoek, E., Carranza_Torres, C., and Corkum, B., (2002), “Hoek-Brown Criterion, 2002”, edn. In

Mining and Tunnelling Innovation and Opportunity. Proc. 5th North American Rock Mechanics

Symp., Vol.1, p.p.267-273.

Hoek, E., Kaiser, P. K. and Bawden, W. F., (1995) “Support of Underground Excavations in Hard

Rock”, Balkema, Rotterdam.

INRTU 2015 Technical report on the results of laboratory research "Definition division of physio-mechanical properties of underlying rocks from the Krasny site to obtain baseline data for

assessing the stability of the pit walls "/ INRTU, 2015. (Технический отчет по результатам

лабораторных исследований «Опре-деление физико-механических свойств вмещающих пород с участка«Красный» с целью получения исходных данных, предназначенных для

оценки устойчивости бортов карьера» / ИРНИТУ, 2015.)

Kopy 2016 (Отчет гидрогеология 2016-HydrologyREport2016).

LLC Miramine 2012 Resource Modelling and Estimation in Micromine for the Krasny Gold

Occurrence.

Micon International Co Ltd 2018 Mineral Resource and Ore Reserves Estimate of the Krasny Gold Deposit and the Vostochny Mineral Occurrence, Irkutsk region, Russian Federation. Report

prepared for Kopy Goldfields AB, 30 August 2018.

MSMI 2018, Geomechanical substantiation of optimal stability parameters of the pit slopes of the Krasny deposit located in the Bodaibo district of Irkutsk region. (Геомеханическое

обоснование оптимальных параметров устойчивости бортов и уступов в условиях карьера, при открытой отработке месторождения «Красное», расположенного в Бодайбинском



районе Иркутской области, Исполнитель, доцент кафедры геологии Московского

Государственного Горного Института канд. тех. наук Пуневский С.А).

Read, J. R. L., Stacey, P. F., (2009) “Guidelines for Open Pit Slope Design”, CSIRO Publishing,

Collingwood, VIC, Australia.

Report on the geological structure of the central part of the “Krasny” site for the development

of temporary exploration standards and calculation of gold reserves for the development to develop a feasibility study for open pit mining, 01/01/2015. (Отчет о геологическом строении

центрального участка месторождения «Красное» с разработкой ТЭО временных разведочных кондиций для открытой отработки руд и подсчетом запасов золота по

состоянию на 01.01.2015 г. / ООО «Красный», ООО НПФ «Геопрогноз», 2015 Проведены

расчеты устойчивости откосов карьеров).

Technical report on the results of laboratory research "Definition division of physio-mechanical

properties of underlying rocks from the Krasny site to obtain baseline data for assessing the stability of the pit walls. (Технический отчет по результатам лабораторных исследований

«Опре-деление физико-механических свойств вмещающих пород с участка«Красный» с целью получения исходных данных, предназначенных для оценки устойчивости бортов

карьера» / ИРНИТУ, 2015). (INRTU, 2015a).

Report on the geological structure of the central part of the “Krasny” site for the development

of temporary exploration standards and calculation of gold reserves for the development to

develop a feasibility study for open pit mining, 01/01/2015. (Отчет о геологическом строении центрального участка месторождения «Красное» с разработкой ТЭО временных

разведочных кондиций для открытой отработки руд и подсчетом запасов золота по состоянию на 01.01.2015 г. / ООО «Красный», ООО НПФ «Геопрогноз», 2015 Проведены

расчеты устойчивости откосов карьеров). (INRTU, 2015b).

Kopy 2016 Hydrology Report (Отчет гидрогеология 2016). (Kopy, 2016).

Moscow State Mining Institute (MSMI) 2018, Geomechanical substantiation of optimal stability parameters of the pit slopes of the Krasny deposit located in the Bodaibo district of Irkutsk

region. (Геомеханическое обоснование оптимальных параметров устойчивости бортов и

уступов в условиях карьера, при открытой отработке месторождения «Красное», расположенного в Бодайбинском районе Иркутской области, Исполнитель, доцент кафедры

геологии Московского Государственного Горного Института канд. тех. наук Пуневский

С.А). (MSMI, 2018).

Micon International Co Ltd 2018 Mineral Resource and Ore Reserves Estimate of the Krasny Gold Deposit and the Vostochny Mineral Occurrence, Irkutsk region, Russian Federation. Report

prepared for Kopy Goldfields AB, 30 August 2018. (Micon International, 2018).


amcconsultants.com Appendix A – 1

Appendix A

Krasny pit optimization results



Krasny Preliminary Pit Optimization Results – KNY8 - MII Only

Evaluated $ 1250/oz Au, 10% Dilution 5% Ore loss Applied in Whittle

6% Discount Rate, 18 Mtpa Total Material Movement, 1.0 Mtpa Plant Throughput Rate, No VRA Limit

Total

Waste

Tonnes

Total Rock

Tonnes

Strip

Ratio

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Processing

Cost


Surplus

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce



1 0.40 825 2.2 1.42 1.19 8.3 10.6 3.7 6.5 7 65 851 -28 -15 106 64 57 57 655

2 0.42 825 2.4 1.41 1.17 9.0 11.4 3.7 6.5 6 71 859 -31 -16 115 68 61 61 732

3 0.44 825 4.8 1.23 1.01 13.8 18.6 2.9 5.4 4 119 919 -59 -26 194 110 93 90 774

4 0.46 825 6.2 1.23 1.03 20.7 26.9 3.3 6.0 8 157 939 -76 -37 256 142 115 109 771

5 0.48 820 6.7 1.22 1.02 22.9 29.6 3.4 6.1 7 169 946 -83 -41 276 152 122 115 802

6 0.50 820 7.1 1.22 1.02 24.5 31.5 3.5 6.2 8 178 953 -87 -44 289 159 126 118 837

7 0.52 820 7.1 1.22 1.02 24.8 31.9 3.5 6.2 7 180 955 -88 -44 292 160 127 119 851

8 0.54 595 21.1 1.57 1.37 209.6 230.7 9.9 15.1 20 713 1,084 -276 -318 1,161 566 205 186 867

9 0.56 595 21.4 1.57 1.37 212.7 234.1 9.9 15.1 19 722 1,085 -280 -323 1,175 572 206 185 897

10 0.58 590 21.6 1.57 1.37 214.8 236.4 10.0 15.1 18 728 1,086 -282 -326 1,185 576 207 184 927

11 0.60 590 21.7 1.57 1.37 217.5 239.2 10.0 15.2 27 734 1,087 -284 -330 1,194 580 208 183 960

12 0.62 590 22.3 1.57 1.37 225.4 247.7 10.1 15.3 20 754 1,093 -292 -342 1,226 592 210 182 1,005

13 0.64 585 24.8 1.60 1.40 275.3 300.1 11.1 16.7 29 860 1,120 -327 -414 1,398 657 220 167 1,013

14 0.66 585 25.1 1.61 1.40 280.5 305.6 11.2 16.8 29 870 1,123 -330 -422 1,415 663 221 163 1,054

15 0.68 585 25.1 1.61 1.40 281.1 306.2 11.2 16.8 29 871 1,124 -331 -423 1,417 664 221 163 1,080

16 0.70 580 26.0 1.62 1.42 302.6 328.7 11.6 17.4 34 910 1,138 -343 -454 1,481 684 224 152 1,116

17 0.72 575 26.3 1.62 1.42 308.7 335.0 11.8 17.6 38 921 1,142 -347 -462 1,498 689 225 148 1,150

18 0.74 575 26.3 1.62 1.42 309.7 336.0 11.8 17.6 31 923 1,143 -347 -464 1,501 690 225 147 1,199

19 0.76 575 26.4 1.62 1.42 311.7 338.1 11.8 17.7 34 926 1,144 -348 -467 1,506 691 225 146 1,218

20 0.78 575 26.5 1.62 1.42 313.5 340.0 11.8 17.7 38 929 1,146 -349 -469 1,511 692 225 144 1,238

21 0.80 575 26.5 1.62 1.42 314.0 340.5 11.9 17.7 46 929 1,146 -350 -470 1,512 692 225 144 1,287

22 0.82 560 27.1 1.62 1.42 327.1 354.2 12.1 18.0 32 950 1,158 -357 -489 1,545 699 226 136 1,313

23 0.84 560 27.2 1.62 1.42 329.9 357.1 12.1 18.1 32 954 1,161 -359 -493 1,552 700 226 134 1,354

24 0.86 560 27.2 1.62 1.42 330.5 357.7 12.1 18.1 27 955 1,161 -359 -494 1,553 700 226 134 1,374

25 0.88 560 27.3 1.62 1.42 331.3 358.6 12.2 18.2 46 956 1,162 -360 -495 1,555 700 226 133 1,420

26 0.90 560 27.3 1.62 1.42 332.3 359.6 12.2 18.2 24 957 1,163 -361 -496 1,557 701 226 132 1,444

27 0.92 560 27.5 1.62 1.42 337.3 364.8 12.3 18.3 49 964 1,168 -363 -503 1,567 701 226 128 1,484

28 0.94 560 27.6 1.62 1.42 339.4 366.9 12.3 18.4 33 966 1,170 -364 -506 1,572 702 226 126 1,512

29 0.96 560 27.6 1.62 1.42 342.0 369.6 12.4 18.5 45 969 1,173 -365 -510 1,577 702 226 124 1,548

30 0.98 560 27.7 1.62 1.42 343.9 371.6 12.4 18.5 34 972 1,175 -366 -513 1,581 702 226 122 1,589

31 1.00 560 27.8 1.62 1.42 344.6 372.4 12.4 18.5 32 973 1,176 -366 -514 1,582 702 226 122 1,614

32 1.02 560 27.8 1.62 1.42 346.4 374.2 12.5 18.6 45 975 1,178 -367 -516 1,585 702 226 120 1,639

33 1.04 555 28.1 1.62 1.42 353.7 381.7 12.6 18.8 41 983 1,186 -370 -527 1,599 702 226 115 1,677

34 1.06 555 28.2 1.62 1.42 356.2 384.4 12.6 18.8 30 986 1,190 -372 -531 1,604 701 226 113 1,716

35 1.08 555 29.2 1.61 1.41 384.8 414.0 13.2 19.5 39 1,017 1,223 -385 -571 1,654 698 225 85 1,741

36 1.10 550 29.4 1.61 1.41 389.1 418.5 13.3 19.7 44 1,022 1,227 -387 -577 1,662 697 225 82 1,763

37 1.12 550 29.6 1.61 1.41 395.0 424.6 13.4 19.8 46 1,028 1,234 -389 -586 1,671 696 225 77 1,802

38 1.14 550 29.6 1.61 1.41 395.5 425.1 13.4 19.8 49 1,028 1,234 -389 -587 1,672 696 225 77 1,840

39 1.16 550 29.6 1.61 1.41 395.5 425.1 13.4 19.8 34 1,028 1,234 -389 -587 1,672 696 225 77 1,883

40 1.18 550 29.6 1.61 1.41 396.8 426.4 13.4 19.9 43 1,029 1,236 -390 -588 1,674 696 225 76 1,905

41 1.20 550 29.8 1.61 1.41 405.2 435.1 13.6 20.1 54 1,037 1,245 -393 -600 1,687 693 225 69 1,932

42 1.22 550 29.9 1.61 1.41 406.5 436.3 13.6 20.2 47 1,038 1,247 -393 -602 1,689 693 225 68 1,976

43 1.24 550 29.9 1.60 1.41 407.2 437.1 13.6 20.2 35 1,039 1,248 -394 -603 1,690 693 225 67 2,009

44 1.26 550 30.0 1.60 1.41 408.4 438.4 13.6 20.2 36 1,040 1,249 -394 -605 1,692 692 225 66 2,037

45 1.28 550 30.1 1.60 1.41 415.5 445.7 13.8 20.4 62 1,046 1,257 -397 -615 1,701 690 225 59 2,064

46 1.30 545 30.1 1.60 1.41 416.0 446.2 13.8 20.4 30 1,046 1,258 -397 -616 1,702 689 225 59 2,090


Factor

Bench


Incremental

Mining Cost

per Tonnes of

Ore



Krasny Preliminary Pit Optimization Results - KNY8 - MII Only



Total

Waste

Tonnes

Total Rock

Tonnes

Strip

Ratio

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Processing

Cost


Surplus

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce



1 0.40 825 5.1 1.21 1.00 14.3 19.4 2.8 5.3 5 125 792 -49 -27 203 127 113 113 609

2 0.42 820 6.5 1.22 1.02 21.9 28.4 3.4 6.0 9 165 813 -64 -39 268 165 143 142 678

3 0.44 820 6.8 1.22 1.02 23.1 29.9 3.4 6.0 7 171 818 -67 -41 279 171 148 147 715

4 0.46 820 7.1 1.21 1.02 24.7 31.8 3.5 6.1 8 180 824 -70 -44 292 178 154 152 737

5 0.48 820 8.3 1.19 1.00 30.4 38.7 3.7 6.4 8 206 849 -81 -53 335 201 171 168 782

6 0.50 595 21.2 1.56 1.36 209.9 231.1 9.9 15.0 21 715 980 -220 -319 1,163 624 360 364 795

7 0.52 590 21.5 1.57 1.37 213.8 235.3 9.9 15.1 19 726 982 -223 -325 1,181 633 364 366 830

8 0.54 590 21.6 1.57 1.37 214.9 236.5 10.0 15.1 20 729 982 -224 -326 1,186 635 365 367 856

9 0.56 590 21.7 1.57 1.37 217.6 239.3 10.0 15.2 27 735 984 -226 -330 1,195 639 366 368 893

10 0.58 590 22.7 1.57 1.37 231.6 254.3 10.2 15.5 22 768 993 -236 -351 1,249 662 376 367 930

11 0.60 585 24.9 1.60 1.40 274.8 299.7 11.1 16.6 29 859 1,019 -260 -414 1,398 724 400 373 946

12 0.62 585 25.1 1.60 1.40 280.5 305.6 11.2 16.8 33 870 1,022 -262 -422 1,416 732 402 372 986

13 0.64 585 25.2 1.60 1.40 281.4 306.6 11.2 16.8 28 872 1,023 -263 -423 1,419 733 403 372 1,021

14 0.66 580 26.1 1.62 1.41 303.0 329.1 11.6 17.4 34 911 1,037 -273 -454 1,483 755 411 366 1,050

15 0.68 575 26.3 1.62 1.42 308.8 335.1 11.7 17.6 39 921 1,041 -276 -462 1,498 761 413 363 1,088

16 0.70 575 26.3 1.62 1.42 309.3 335.6 11.7 17.6 25 922 1,042 -276 -463 1,500 761 413 362 1,121

17 0.72 575 26.4 1.62 1.42 311.7 338.1 11.8 17.7 35 926 1,044 -277 -467 1,506 763 414 362 1,145

18 0.74 575 26.5 1.62 1.42 313.7 340.2 11.8 17.7 36 929 1,045 -278 -469 1,512 764 414 360 1,177

19 0.76 560 27.0 1.62 1.42 323.8 350.9 12.0 17.9 30 945 1,055 -283 -484 1,538 771 417 358 1,232

20 0.78 560 27.2 1.62 1.42 328.6 355.8 12.1 18.0 33 953 1,059 -285 -491 1,549 773 417 355 1,245

21 0.80 560 27.2 1.62 1.42 329.5 356.7 12.1 18.1 46 954 1,060 -285 -492 1,551 774 418 355 1,282

22 0.82 560 27.3 1.62 1.42 330.6 357.8 12.1 18.1 42 955 1,061 -286 -494 1,554 774 418 354 1,303

23 0.84 560 27.4 1.62 1.42 332.3 359.6 12.2 18.1 32 958 1,063 -286 -496 1,558 775 418 353 1,350

24 0.86 560 27.4 1.62 1.42 332.8 360.1 12.2 18.2 30 958 1,063 -287 -497 1,559 775 418 353 1,389

25 0.88 560 27.6 1.62 1.42 339.2 366.7 12.3 18.4 44 966 1,069 -289 -506 1,572 777 419 349 1,421

26 0.90 560 27.6 1.62 1.42 339.4 367.0 12.3 18.4 34 967 1,070 -289 -506 1,572 777 419 349 1,448

27 0.92 560 27.7 1.62 1.42 342.4 370.1 12.4 18.4 40 970 1,073 -290 -511 1,578 777 419 345 1,476

28 0.94 560 27.8 1.62 1.42 343.8 371.5 12.4 18.5 31 972 1,075 -291 -513 1,581 778 419 344 1,505

29 0.96 560 27.8 1.62 1.42 345.2 373.0 12.4 18.5 41 974 1,076 -291 -515 1,584 778 419 343 1,534

30 0.98 560 27.9 1.62 1.42 348.6 376.6 12.5 18.6 36 978 1,080 -293 -520 1,590 778 419 340 1,572

31 1.00 555 28.2 1.62 1.41 356.1 384.4 12.6 18.8 39 986 1,089 -295 -530 1,604 778 419 333 1,608

32 1.02 555 29.3 1.61 1.41 384.8 414.1 13.2 19.5 39 1,017 1,121 -306 -571 1,655 777 419 307 1,653

33 1.04 550 29.4 1.61 1.41 388.9 418.3 13.2 19.6 42 1,022 1,126 -307 -577 1,662 777 418 303 1,679

34 1.06 550 29.5 1.61 1.41 392.4 422.0 13.3 19.7 48 1,025 1,130 -308 -582 1,668 777 418 299 1,711

35 1.08 550 29.6 1.61 1.41 395.0 424.6 13.4 19.8 44 1,028 1,132 -309 -586 1,672 777 418 296 1,731

36 1.10 550 29.6 1.61 1.41 395.5 425.1 13.4 19.8 51 1,028 1,133 -309 -587 1,673 776 418 296 1,766

37 1.12 550 29.6 1.60 1.41 396.1 425.7 13.4 19.8 32 1,029 1,134 -310 -587 1,674 776 418 295 1,796

38 1.14 550 29.8 1.60 1.41 401.3 431.0 13.5 20.0 51 1,034 1,139 -311 -595 1,681 775 418 290 1,846

39 1.16 550 29.9 1.60 1.41 405.2 435.1 13.6 20.1 59 1,037 1,144 -312 -600 1,687 774 418 286 1,861

40 1.18 550 30.0 1.60 1.40 407.7 437.7 13.6 20.2 40 1,040 1,147 -313 -604 1,691 774 417 284 1,899

41 1.20 550 30.0 1.60 1.40 408.3 438.3 13.6 20.2 34 1,040 1,148 -313 -605 1,692 774 417 283 1,937

42 1.22 545 30.0 1.60 1.40 409.0 439.0 13.6 20.2 33 1,041 1,148 -314 -606 1,693 773 417 283 1,968

43 1.24 545 30.2 1.60 1.40 416.0 446.2 13.8 20.4 63 1,047 1,156 -315 -616 1,702 771 417 276 1,989

44 1.28 545 30.2 1.60 1.40 417.0 447.2 13.8 20.4 67 1,047 1,158 -316 -617 1,704 771 416 275 2,043

45 1.30 545 30.2 1.60 1.40 417.9 448.1 13.8 20.5 60 1,048 1,159 -316 -618 1,705 771 416 275 2,094

46 1.32 545 30.2 1.60 1.40 417.9 448.1 13.8 20.5 57 1,048 1,159 -316 -618 1,705 771 416 274 2,139


Pit Shell Revenue

Factor

Bench Total Ore Incremental

Mining Cost

per Tonnes of

Ore



Krasny Preliminary Pit Optimization Results - KNY8 - MII Only



Total

Waste

Tonnes

Total Rock

Tonnes

Strip

Ratio

Mining Cost

per Tonnes

of Ore

Recovered

Ounces

Cost per

Ounce

Processing

Cost


Surplus

Discounted

Surplus -

Best Case

Discounted

Surplus -

Worst Case

Incremental

Cost per

Ounce



1 0.40 820 6.7 1.22 1.02 22.2 28.9 3.3 6.0 6 168 751 -57 -40 273 176 159 159 578

2 0.42 820 7.1 1.21 1.01 24.1 31.2 3.4 6.1 8 177 758 -60 -43 289 185 166 166 678

3 0.44 820 7.3 1.21 1.01 25.1 32.4 3.5 6.1 8 182 763 -62 -45 296 189 170 170 709

4 0.46 820 8.4 1.19 1.00 30.9 39.3 3.7 6.5 8 208 786 -72 -54 339 213 189 187 730

5 0.48 595 21.3 1.56 1.36 210.5 231.7 9.9 15.0 21 717 930 -193 -320 1,166 653 460 460 760

6 0.50 590 21.5 1.57 1.37 213.8 235.3 9.9 15.1 20 726 931 -195 -325 1,181 661 464 464 795

7 0.52 590 21.6 1.57 1.37 215.4 237.1 10.0 15.1 20 730 932 -196 -327 1,188 664 467 465 825

8 0.54 590 21.8 1.57 1.37 217.6 239.4 10.0 15.2 28 735 933 -197 -330 1,196 668 469 466 866

9 0.56 590 22.7 1.57 1.37 231.9 254.7 10.2 15.5 22 769 943 -206 -351 1,250 693 484 474 893

10 0.58 585 24.9 1.60 1.40 274.6 299.5 11.0 16.6 29 859 969 -227 -413 1,397 757 519 500 913

11 0.60 585 25.1 1.60 1.40 280.5 305.6 11.2 16.8 33 870 972 -229 -422 1,416 765 523 502 954

12 0.62 585 25.3 1.60 1.40 282.7 307.9 11.2 16.8 24 875 974 -230 -425 1,423 768 525 502 996

13 0.64 580 26.1 1.62 1.41 303.1 329.2 11.6 17.4 35 912 988 -239 -454 1,483 790 536 506 1,018

14 0.66 575 26.3 1.62 1.42 308.8 335.1 11.7 17.6 40 921 992 -241 -462 1,499 796 539 505 1,057

15 0.68 575 26.3 1.62 1.42 309.4 335.8 11.7 17.6 27 922 993 -241 -463 1,500 796 539 505 1,087

16 0.70 575 26.5 1.62 1.42 313.1 339.6 11.8 17.7 36 928 996 -242 -469 1,510 799 541 503 1,122

17 0.72 575 26.5 1.62 1.42 313.7 340.2 11.8 17.7 36 929 996 -243 -469 1,512 800 541 503 1,154

18 0.74 560 27.1 1.62 1.42 324.5 351.6 12.0 17.9 29 947 1,006 -247 -485 1,540 807 545 501 1,193

19 0.76 560 27.2 1.62 1.42 328.6 355.8 12.1 18.0 38 953 1,010 -249 -491 1,550 810 547 498 1,209

20 0.78 560 27.2 1.62 1.42 329.6 356.8 12.1 18.1 41 954 1,011 -249 -492 1,552 810 547 498 1,252

21 0.80 560 27.3 1.62 1.42 331.1 358.4 12.1 18.1 36 956 1,012 -250 -495 1,555 811 547 497 1,278

22 0.82 560 27.4 1.62 1.42 332.3 359.6 12.2 18.1 38 958 1,013 -250 -496 1,558 811 548 496 1,320

23 0.84 560 27.4 1.62 1.42 332.8 360.1 12.2 18.2 30 958 1,014 -250 -497 1,559 812 548 496 1,345

24 0.86 560 27.6 1.62 1.42 339.2 366.7 12.3 18.4 44 966 1,020 -252 -506 1,572 813 549 493 1,386

25 0.88 560 27.6 1.62 1.42 340.0 367.6 12.3 18.4 32 967 1,021 -253 -507 1,574 814 549 493 1,418

26 0.90 560 27.8 1.62 1.42 343.3 371.1 12.4 18.5 36 972 1,025 -254 -512 1,580 814 549 491 1,445

27 0.92 560 27.8 1.62 1.42 344.7 372.5 12.4 18.5 42 973 1,026 -254 -514 1,583 815 549 490 1,485

28 0.94 560 27.9 1.62 1.42 347.8 375.7 12.5 18.6 33 977 1,030 -255 -518 1,589 815 549 489 1,519

29 0.96 560 28.1 1.62 1.41 350.5 378.6 12.5 18.6 33 980 1,033 -256 -522 1,594 815 550 487 1,553

30 0.98 555 28.2 1.62 1.41 356.7 384.9 12.6 18.8 45 987 1,040 -258 -531 1,605 816 550 485 1,573

31 1.00 555 29.3 1.61 1.41 384.8 414.1 13.2 19.5 40 1,017 1,072 -267 -571 1,655 816 550 466 1,611

32 1.02 550 29.4 1.61 1.41 388.9 418.3 13.2 19.6 42 1,022 1,076 -268 -577 1,662 816 550 463 1,638

33 1.06 550 29.6 1.61 1.41 395.0 424.6 13.4 19.8 47 1,028 1,083 -270 -586 1,672 816 549 457 1,680

34 1.08 550 29.6 1.60 1.41 396.1 425.7 13.4 19.8 38 1,029 1,084 -270 -587 1,674 816 549 456 1,736

35 1.10 550 29.6 1.60 1.41 396.2 425.8 13.4 19.8 42 1,029 1,084 -270 -588 1,674 816 549 456 1,784

36 1.12 550 29.8 1.60 1.41 401.3 431.0 13.5 20.0 51 1,034 1,090 -272 -595 1,681 815 549 451 1,807

37 1.14 550 29.9 1.60 1.40 407.2 437.1 13.6 20.2 52 1,039 1,097 -273 -603 1,690 814 548 446 1,833

38 1.16 550 30.0 1.60 1.40 408.3 438.3 13.6 20.2 34 1,040 1,098 -274 -605 1,692 813 548 445 1,872

39 1.18 545 30.0 1.60 1.40 408.8 438.8 13.6 20.2 30 1,041 1,099 -274 -606 1,693 813 548 444 1,908

40 1.20 545 30.0 1.60 1.40 409.0 439.0 13.6 20.2 55 1,041 1,099 -274 -606 1,693 813 548 444 1,934

41 1.22 545 30.2 1.60 1.40 416.0 446.2 13.8 20.4 63 1,047 1,107 -275 -616 1,702 811 547 438 1,953

42 1.24 545 30.2 1.60 1.40 417.0 447.2 13.8 20.4 68 1,047 1,108 -276 -617 1,704 811 547 437 2,007

43 1.26 545 30.2 1.60 1.40 417.5 447.7 13.8 20.5 52 1,048 1,109 -276 -618 1,704 811 547 437 2,040

44 1.28 545 30.2 1.60 1.40 417.9 448.1 13.8 20.5 79 1,048 1,109 -276 -618 1,705 811 547 436 2,079

45 1.30 545 30.2 1.60 1.40 417.9 448.1 13.8 20.5 57 1,048 1,109 -276 -618 1,705 811 547 436 2,098

46 1.32 545 30.2 1.60 1.40 418.4 448.6 13.8 20.5 83 1,048 1,110 -276 -619 1,705 811 547 436 2,128


Pit Shell Revenue

Factor

Bench Total Ore Incremental

Mining Cost

per Tonnes of

Ore



Krasny - 6% Discount Rate, 18 Mtpa Total Material Movement, 1.0 Mtpa Plant Throughput Rate Krasny - 6% Discount Rate, 35 Mtpa Total Material Movement, 2.0 Mtpa Plant Throughput Rate

6% Discount Rate, 60 Mtpa Total Material Movement, 3.0 Mtpa Plant Throughput Rate

0

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Revenue Factor



amcconsultants.com Appendix B – 1

Appendix B

Krasny preliminary financial mining models



Scenario one

Krasny Deposit Production Schedule - MI Open Pit RF1 Ultimate Pit

3.0 Mtpa TMM Limit, 0.4 Mtpa Plant Limit, 2 Stage - Pit Shell 10, 30

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Total Ore

Total Ore Mining kt 6,306 333 400 400 400 400 400 400 400 400 400 400 400 400 400 400 375

Total Gold Grade in Ore g/t 1.20 1.26 1.10 1.15 1.18 1.16 1.08 1.18 1.14 1.03 0.94 1.17 1.33 1.54 1.36 1.28 1.34

Total Gold in Ore kg 7,566 421 437 459 471 462 432 471 454 413 376 466 531 615 543 511 503

Waste Stripping

Waste Mining kt 31,540 2,667 2,600 2,600 2,600 2,600 2,600 2,600 2,600 2,558 2,324 1,386 1,344 1,162 867 584 446

Stripping Ratio W:O 5.0 8.0 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.4 5.8 3.5 3.4 2.9 2.2 1.5 1.2

Processing

Total Ore Processing kt 6,306 333 400 400 400 400 400 400 400 400 400 400 400 400 400 400 375

Total Gold Grade g/t 1.20 1.26 1.10 1.15 1.18 1.16 1.08 1.18 1.14 1.03 0.94 1.17 1.33 1.54 1.36 1.28 1.34

Recovered Gold Grade g/t 0.98 0.85 0.89 0.93 0.92 0.87 0.96 0.95 0.90 0.81 1.01 1.17 1.36 1.20 1.13 1.19

Total Gold in Ore kg 7,566 421 437 459 471 462 432 471 454 413 376 466 531 615 543 511 503

Gold Recovery % 83.9 77.5 77.5 77.7 78.5 79.4 80.4 81.6 84.0 87.0 86.6 86.8 87.8 88.2 88.3 88.4 88.5

Total Gold Extracted kg 6,346 326 339 357 370 367 347 385 382 359 326 404 466 543 480 452 445

Total Gold Extracted koz 204.0 10.5 10.9 11.5 11.9 11.8 11.2 12.4 12.3 11.5 10.5 13.0 15.0 17.5 15.4 14.5 14.3

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 255,046 13,092 13,631 14,338 14,855 14,731 13,960 15,461 15,336 14,436 13,085 16,252 18,744 21,814 19,274 18,149 17,886

Royalty US$'000 16,578 851 886 932 966 958 907 1,005 997 938 851 1,056 1,218 1,418 1,253 1,180 1,163

Refining and Transportation US$'000 635 33 34 36 37 37 35 38 38 36 33 40 47 54 48 45 45

Revenue US$'000 237,833 12,209 12,711 13,371 13,852 13,737 13,018 14,418 14,301 13,461 12,202 15,155 17,479 20,342 17,974 16,924 16,679

Operating Costs

Ore Mining US$'000 11,476 606 727 727 727 728 728 728 728 728 728 728 728 728 728 728 682

Waste Stripping US$'000 43,525 3,681 3,589 3,589 3,589 3,588 3,588 3,588 3,588 3,530 3,208 1,913 1,854 1,604 1,196 805 615

Total Mining US$'000 55,001 4,286 4,316 4,316 4,316 4,316 4,316 4,316 4,316 4,258 3,936 2,641 2,582 2,332 1,924 1,533 1,298

Processing US$'000 48,239 2,546 3,056 3,056 3,057 3,058 3,058 3,059 3,060 3,060 3,060 3,060 3,060 3,060 3,060 3,060 2,868

Transport to plant US$'000 14,692 775 931 931 931 931 931 932 932 932 932 932 932 932 932 932 874

G & A US$'000 35,375 1,867 2,241 2,241 2,242 2,242 2,243 2,243 2,244 2,244 2,244 2,244 2,244 2,244 2,244 2,244 2,103

Cashflow

Net Revenue US$'000 84,526 2,735 2,167 2,826 3,307 3,189 2,470 3,867 3,749 2,968 2,031 6,279 8,661 11,774 9,813 9,155 9,536

Undiscounted cashflow US$'000 84,526 2,735 2,167 2,826 3,307 3,189 2,470 3,867 3,749 2,968 2,031 6,279 8,661 11,774 9,813 9,155 9,536

Cumulative Undiscounted cashflow US$'000 2,735 4,902 7,728 11,034 14,224 16,694 20,561 24,310 27,278 29,308 35,587 44,248 56,022 65,835 74,990 84,526

Discounted cashflow 6% US$'000 46,486 2,580 1,929 2,373 2,619 2,383 1,741 2,572 2,352 1,757 1,134 3,308 4,304 5,520 4,340 3,820 3,754

Cumulative Discounted cashflow 6% US$'000 2,580 4,508 6,881 9,501 11,884 13,625 16,197 18,549 20,306 21,440 24,747 29,051 34,572 38,912 42,732 46,486

YearsParameter Units Total

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Scenario two

Krasny Deposit Production Schedule - MI Open Pit Only RF1 Ultimate Pit

6.0 Mtpa TMM Limit, 1.0 Mtpa Plant Limit, 3 Stage - Pit Shell 2, 7, 31

2020 2021 2022 2023 2024 2025 2026 2027

1 2 3 4 5 6 7 8

Total Ore

Total Ore Mining kt 7,287 802 1,000 999 1,000 948 1,000 1,000 540

Total Gold Grade in Ore g/t 1.10 1.36 0.91 1.00 1.11 1.11 1.06 1.21 1.15

Total Gold in Ore kg 8,051 1,093 913 995 1,109 1,047 1,064 1,209 622

Waste Stripping

Waste Mining kt 32,772 5,198 5,000 5,001 5,000 5,052 4,858 2,006 656

Stripping Ratio W:O 4.5 6.5 5.0 5.0 5.0 5.3 4.9 2.0 1.2

Processing

Total Ore Processing kt 7,287 802 1,000 999 1,000 948 1,000 1,000 540

Total Gold Grade g/t 1.10 1.36 0.91 1.00 1.11 1.11 1.06 1.21 1.15

Recovered Gold Grade g/t 1.06 0.71 0.81 0.93 0.96 0.93 1.07 1.02

Total Gold in Ore kg 8,051 1,093 913 995 1,109 1,047 1,064 1,209 622

Gold Recovery % 83.9 77.5 78.0 81.1 83.9 87.1 87.4 88.3 88.5

Total Gold Extracted kg 6,755 846 712 807 930 912 930 1,068 551

Total Gold Extracted koz 217.2 27.2 22.9 26.0 29.9 29.3 29.9 34.3 17.7

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 271,492 34,018 28,604 32,439 37,362 36,636 37,375 42,921 22,136

Royalty US$'000 17,647 2,211 1,859 2,109 2,429 2,381 2,429 2,790 1,439

Refining and Transportation US$'000 676 85 71 81 93 91 93 107 55

Revenue US$'000 253,170 31,722 26,674 30,250 34,840 34,164 34,853 40,025 20,642

Operating Costs

Ore Mining US$'000 13,263 1,459 1,819 1,818 1,819 1,725 1,820 1,820 983

Waste Stripping US$'000 45,225 7,174 6,900 6,901 6,901 6,972 6,703 2,768 905

Total Mining US$'000 58,488 8,633 8,720 8,720 8,720 8,697 8,523 4,588 1,888

Processing US$'000 41,031 4,513 5,628 5,625 5,628 5,336 5,630 5,630 3,040

Transport to plant US$'000 12,497 1,375 1,714 1,713 1,714 1,625 1,715 1,715 926

G & A US$'000 30,090 3,310 4,128 4,125 4,127 3,913 4,129 4,129 2,230

Cashflow

Net Revenue US$'000 111,063 13,892 6,484 10,068 14,650 14,594 14,855 23,963 12,558

Undiscounted cashflow US$'000 111,063 13,892 6,484 10,068 14,650 14,594 14,855 23,963 12,558

Cumulative Undiscounted cashflow US$'000 13,892 20,376 30,444 45,094 59,688 74,543 98,505 111,063

Discounted cashflow 6% US$'000 84,127 13,106 5,770 8,453 11,604 10,905 10,472 15,937 7,879

Cumulative Discounted cashflow 6% US$'000 13,106 18,876 27,329 38,934 49,839 60,311 76,248 84,127


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2020 2021 2022 2023 2024 2025 2026 2027

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Scenario three

Krasny Deposit Production Schedule - MII Open Pit Only RF1 Ultimate Pit


2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Total Ore

Total Ore Mining kt 27,755 289 999 999 999 999 999 999 1,000 999 999 995 698 996 998 998 998 999 999 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 792

Total Gold Grade in Ore g/t 1.62 1.19 1.01 1.06 1.00 0.91 0.97 1.08 1.41 1.64 1.32 1.13 0.78 1.52 1.92 2.17 1.85 1.54 1.43 1.70 1.71 1.73 1.73 1.69 1.90 2.33 3.39 2.60 2.03 1.70

Total Gold in Ore kg 44,974 345 1,006 1,055 999 909 965 1,082 1,411 1,643 1,320 1,126 548 1,516 1,911 2,163 1,851 1,542 1,427 1,702 1,709 1,731 1,728 1,686 1,896 2,329 3,393 2,597 2,034 1,349

Waste Stripping

Waste Mining kt 344,632 17,711 17,001 17,001 17,001 17,001 17,001 17,001 17,000 17,001 17,001 17,005 17,302 17,004 17,002 17,002 17,002 17,001 17,001 16,999 3,497 2,354 2,112 2,000 2,105 2,190 1,070 2,782 2,057 429

Stripping Ratio W:O 12.4 61.2 17.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 17.1 24.8 17.1 17.0 17.0 17.0 17.0 17.0 17.0 3.5 2.4 2.1 2.0 2.1 2.2 1.1 2.8 2.1 0.5

Processing

Total Ore Processing kt 27,755 289 999 999 999 999 999 999 1,000 999 999 995 698 996 998 998 998 999 999 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 792

Total Gold Grade g/t 1.62 1.19 1.01 1.06 1.00 0.91 0.97 1.08 1.41 1.64 1.32 1.13 0.78 1.52 1.92 2.17 1.85 1.54 1.43 1.70 1.71 1.73 1.73 1.69 1.90 2.33 3.39 2.60 2.03 1.70

Recovered Gold Grade g/t 0.92 0.78 0.83 0.81 0.76 0.82 0.95 1.24 1.45 1.17 1.00 0.69 1.35 1.70 1.92 1.64 1.37 1.26 1.51 1.51 1.53 1.53 1.49 1.68 2.06 3.00 2.30 1.80 1.51

Total Gold in Ore kg 44,974 345 1,006 1,055 999 909 965 1,082 1,411 1,643 1,320 1,126 548 1,516 1,911 2,163 1,851 1,542 1,427 1,702 1,709 1,731 1,728 1,686 1,896 2,329 3,393 2,597 2,034 1,349

Gold Recovery % 87.5 77.5 77.8 78.8 81.0 83.3 85.1 87.2 87.9 88.2 88.4 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.4 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 39,373 267 782 831 809 757 821 944 1,240 1,449 1,168 997 485 1,342 1,692 1,915 1,638 1,366 1,262 1,506 1,513 1,532 1,530 1,492 1,678 2,062 3,003 2,299 1,800 1,194

Total Gold Extracted koz 1,265.9 8.6 25.2 26.7 26.0 24.3 26.4 30.3 39.9 46.6 37.5 32.0 15.6 43.1 54.4 61.6 52.7 43.9 40.6 48.4 48.6 49.3 49.2 48.0 53.9 66.3 96.5 73.9 57.9 38.4

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 1,582,347 10,747 31,439 33,408 32,530 30,430 32,997 37,925 49,829 58,233 46,922 40,061 19,481 53,923 67,984 76,956 65,842 54,878 50,721 60,524 60,805 61,569 61,488 59,961 67,436 82,868 120,686 92,393 72,339 47,971

Royalty US$'000 102,853 699 2,044 2,172 2,114 1,978 2,145 2,465 3,239 3,785 3,050 2,604 1,266 3,505 4,419 5,002 4,280 3,567 3,297 3,934 3,952 4,002 3,997 3,897 4,383 5,386 7,845 6,006 4,702 3,118

Refining and Transportation US$'000 3,937 27 78 83 81 76 82 94 124 145 117 100 48 134 169 191 164 137 126 151 151 153 153 149 168 206 300 230 180 119

Revenue US$'000 1,475,557 10,022 29,318 31,153 30,334 28,377 30,770 35,366 46,467 54,303 43,756 37,357 18,166 50,284 63,396 71,762 61,398 51,174 47,298 56,439 56,701 57,413 57,339 55,914 62,885 77,276 112,541 86,158 67,457 44,733

Operating Costs

Ore Mining US$'000 50,514 527 1,818 1,818 1,819 1,818 1,818 1,817 1,820 1,819 1,818 1,811 1,271 1,813 1,816 1,816 1,817 1,818 1,819 1,820 1,820 1,820 1,820 1,820 1,820 1,820 1,820 1,820 1,820 1,441

Waste Stripping US$'000 475,592 24,441 23,461 23,461 23,461 23,461 23,462 23,462 23,460 23,461 23,462 23,467 23,876 23,465 23,463 23,463 23,462 23,461 23,461 23,458 4,826 3,248 2,915 2,760 2,905 3,022 1,476 3,839 2,838 593

Total Mining US$'000 526,106 24,967 25,280 25,280 25,280 25,280 25,279 25,279 25,280 25,280 25,279 25,278 25,147 25,278 25,279 25,279 25,279 25,280 25,280 25,278 6,646 5,068 4,735 4,580 4,725 4,842 3,296 5,659 4,658 2,033

Processing US$'000 156,270 1,630 5,625 5,626 5,626 5,624 5,624 5,623 5,630 5,627 5,623 5,601 3,933 5,608 5,619 5,618 5,621 5,624 5,626 5,630 5,630 5,630 5,630 5,630 5,630 5,630 5,630 5,630 5,630 4,457

Transport to plant US$'000 47,596 496 1,713 1,713 1,714 1,713 1,713 1,713 1,715 1,714 1,713 1,706 1,198 1,708 1,711 1,711 1,712 1,713 1,714 1,715 1,715 1,715 1,715 1,715 1,715 1,715 1,715 1,715 1,715 1,357

G & A US$'000 114,598 1,195 4,125 4,125 4,126 4,125 4,124 4,123 4,129 4,126 4,124 4,108 2,884 4,113 4,121 4,120 4,122 4,124 4,126 4,129 4,129 4,129 4,129 4,129 4,129 4,129 4,129 4,129 4,129 3,268

Cashflow

Net Revenue US$'000 630,987 -18,266 -7,426 -5,591 -6,412 -8,365 -5,971 -1,372 9,713 17,557 7,016 664 -14,996 13,576 26,666 35,033 24,663 14,433 10,552 19,687 38,581 40,871 41,129 39,860 46,685 60,959 97,770 69,024 51,325 33,618

Undiscounted cashflow US$'000 630,987 -18,266 -7,426 -5,591 -6,412 -8,365 -5,971 -1,372 9,713 17,557 7,016 664 -14,996 13,576 26,666 35,033 24,663 14,433 10,552 19,687 38,581 40,871 41,129 39,860 46,685 60,959 97,770 69,024 51,325 33,618

Cumulative Undiscounted cashflow US$'000 -18,266 -25,692 -31,283 -37,694 -46,059 -52,030 -53,402 -43,689 -26,132 -19,116 -18,451 -33,447 -19,871 6,795 41,828 66,492 80,925 91,477 111,163 149,745 190,616 231,745 271,605 318,291 379,250 477,020 546,044 597,369 630,987

Discounted cashflow 6% US$'000 150,049 -17,232 -6,609 -4,694 -5,079 -6,251 -4,209 -912 6,094 10,392 3,918 350 -7,452 6,365 11,794 14,618 9,709 5,360 3,697 6,507 12,030 12,022 11,414 10,435 11,530 14,203 21,491 14,313 10,041 6,204

Cumulative Discounted cashflow 6% US$'000 -17,232 -23,841 -28,535 -33,614 -39,865 -44,074 -44,986 -38,892 -28,500 -24,582 -24,232 -31,685 -25,320 -13,526 1,093 10,801 16,161 19,858 26,365 38,395 50,417 61,831 72,266 83,796 98,000 119,491 133,804 143,845 150,049


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Scenario four

Krasny Deposit Production Schedule - MI Open Pit RF1 Ultimate Pit + MSO COG 3.0


2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Total Ore

Total Ore Mining kt 10,582 802 1,000 999 1,000 948 1,000 1,000 540 365 487 487 487 487 487 487 10


Total Gold in Ore kg 20,870 1,093 913 995 1,109 1,047 1,064 1,209 622 1,493 1,791 1,709 1,856 2,061 2,048 1,829 32

Waste Stripping

Waste Mining kt 32,772 5,198 5,000 5,001 5,000 5,052 4,858 2,006 656


Processing

Total Ore Processing kt 10,582 802 1,000 999 1,000 948 1,000 1,000 540 365 487 487 487 487 487 487 10


Recovered Gold Grade g/t 1.06 0.71 0.81 0.93 0.96 0.93 1.07 1.02 3.62 3.26 3.11 3.37 3.75 3.72 3.33 2.94

Total Gold in Ore kg 20,870 1,093 913 995 1,109 1,047 1,064 1,209 622 1,493 1,791 1,709 1,856 2,061 2,048 1,829 32

Gold Recovery % 86.7 77.5 78.0 81.1 83.9 87.1 87.4 88.3 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 18,100 846 712 807 930 912 930 1,068 551 1,321 1,585 1,512 1,643 1,824 1,812 1,619 28


Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 727,420 34,018 28,604 32,439 37,362 36,636 37,375 42,921 22,136 53,104 63,714 60,771 66,010 73,312 72,840 65,049 1,126

Royalty US$'000 47,282 2,211 1,859 2,109 2,429 2,381 2,429 2,790 1,439 3,452 4,141 3,950 4,291 4,765 4,735 4,228 73

Refining and Transportation US$'000 1,810 85 71 81 93 91 93 107 55 132 159 151 164 182 181 162 3

Revenue US$'000 678,327 31,722 26,674 30,250 34,840 34,164 34,853 40,025 20,642 49,520 59,414 56,670 61,555 68,364 67,924 60,659 1,050

Operating Costs

Ore Mining US$'000 243,900 1,459 1,819 1,818 1,819 1,725 1,820 1,820 983 25,552 34,070 34,070 34,070 34,070 34,070 34,070 666

Waste Stripping US$'000 45,225 7,174 6,900 6,901 6,901 6,972 6,703 2,768 905 0 0 0 0 0 0 0 0

Total Mining US$'000 289,125 8,633 8,720 8,720 8,720 8,697 8,523 4,588 1,888 25,552 34,070 34,070 34,070 34,070 34,070 34,070 666

Processing US$'000 139,876 4,513 5,628 5,625 5,628 5,336 5,630 5,630 3,040 10,951 14,601 14,601 14,601 14,601 14,601 14,601 286

Transport to plant US$'000 12,497 1,375 1,714 1,713 1,714 1,625 1,715 1,715 926

G & A US$'000 30,090 3,310 4,128 4,125 4,127 3,913 4,129 4,129 2,230

Cashflow

Net Revenue US$'000 206,739 13,892 6,484 10,068 14,650 14,594 14,855 23,963 12,558 13,017 10,743 7,999 12,884 19,693 19,253 11,988 99

Undiscounted cashflow US$'000 206,739 13,892 6,484 10,068 14,650 14,594 14,855 23,963 12,558 13,017 10,743 7,999 12,884 19,693 19,253 11,988 99

Cumulative Undiscounted cashflow US$'000 13,892 20,376 30,444 45,094 59,688 74,543 98,505 111,063 124,080 134,823 142,822 155,706 175,399 194,653 206,641 206,739

Discounted cashflow 0% US$'000 131,237 13,106 5,770 8,453 11,604 10,905 10,472 15,937 7,879 7,705 5,999 4,214 6,403 9,233 8,516 5,002 39

Cumulative Discounted cashflow 0% US$'000 13,106 18,876 27,329 38,934 49,839 60,311 76,248 84,127 91,831 97,830 102,044 108,447 117,680 126,196 131,198 131,237

YearsTotalUnitsParameter

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Scenario five



2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Total Ore

Total Ore Mining kt 28,220 290 1,999 1,999 2,000 2,000 1,339 1,427 2,000 1,997 1,999 2,000 2,000 2,000 2,000 2,000 1,171 0

Total Gold Grade in Ore g/t 1.62 1.19 1.02 0.96 1.02 1.48 1.42 0.89 1.72 1.99 1.52 1.71 1.71 1.75 2.49 2.71 1.66 1.22

Total Gold in Ore kg 45,589 345 2,047 1,919 2,046 2,952 1,898 1,265 3,435 3,973 3,042 3,416 3,416 3,492 4,982 5,412 1,948 0

Waste Stripping

Waste Mining kt 356,135 25,398 33,001 33,001 33,000 33,000 33,661 33,573 33,000 33,003 27,591 19,287 4,703 4,280 4,650 4,124 861 1

Stripping Ratio W:O 12.6 87.5 16.5 16.5 16.5 16.5 25.1 23.5 16.5 16.5 13.8 9.6 2.4 2.1 2.3 2.1 0.7 2.7

Processing

Total Ore Processing kt 28,220 290 1,999 1,999 2,000 2,000 1,339 1,427 2,000 1,997 1,999 2,000 2,000 2,000 2,000 2,000 1,171 0

Total Gold Grade g/t 1.62 1.19 1.02 0.96 1.02 1.48 1.42 0.89 1.72 1.99 1.52 1.71 1.71 1.75 2.49 2.71 1.66 1.22

Recovered Gold Grade g/t 0.92 0.80 0.79 0.88 1.30 1.25 0.78 1.52 1.76 1.35 1.51 1.51 1.55 2.20 2.40 1.47 1.08

Total Gold in Ore kg 45,589 345 2,047 1,919 2,046 2,952 1,898 1,265 3,435 3,973 3,042 3,416 3,416 3,492 4,982 5,412 1,948 0

Gold Recovery % 87.5 77.6 78.2 82.0 86.1 88.0 88.4 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 39,911 268 1,601 1,573 1,762 2,598 1,679 1,119 3,041 3,516 2,692 3,024 3,024 3,092 4,408 4,790 1,723 0

Total Gold Extracted koz 1,283.2 8.6 51.5 50.6 56.6 83.5 54.0 36.0 97.8 113.0 86.6 97.2 97.2 99.4 141.7 154.0 55.4 0.0

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 1,603,966 10,764 64,358 63,232 70,803 104,394 67,457 44,968 122,229 141,312 108,207 121,530 121,530 124,263 177,150 192,502 69,253 13

Royalty US$'000 104,258 700 4,183 4,110 4,602 6,786 4,385 2,923 7,945 9,185 7,033 7,899 7,899 8,077 11,515 12,513 4,501 1

Refining and Transportation US$'000 3,991 27 160 157 176 260 168 112 304 352 269 302 302 309 441 479 172 0

Revenue US$'000 1,495,717 10,037 60,015 58,965 66,025 97,349 62,904 41,934 113,980 131,775 100,905 113,328 113,328 115,876 165,195 179,511 64,580 12

Operating Costs

Ore Mining US$'000 51,360 528 3,639 3,639 3,640 3,639 2,436 2,598 3,639 3,634 3,638 3,640 3,640 3,640 3,640 3,640 2,131 1

Waste Stripping US$'000 491,466 35,050 45,541 45,541 45,540 45,540 46,453 46,330 45,541 45,545 38,076 26,617 6,490 5,906 6,417 5,690 1,188 1

Total Mining US$'000 542,826 35,578 49,180 49,180 49,180 49,180 48,889 48,928 49,180 49,179 41,714 30,257 10,130 9,546 10,057 9,330 3,319 2

Processing US$'000 126,119 1,297 8,935 8,935 8,937 8,937 5,982 6,378 8,937 8,924 8,933 8,938 8,938 8,938 8,938 8,938 5,232 1

Transport to plant US$'000 38,413 395 2,721 2,721 2,722 2,722 1,822 1,943 2,722 2,718 2,721 2,722 2,722 2,722 2,722 2,722 1,593 0

G & A US$'000 92,487 951 6,552 6,552 6,554 6,554 4,387 4,678 6,553 6,544 6,551 6,555 6,555 6,555 6,555 6,555 3,837 1

Cashflow

Net Revenue US$'000 695,872 -28,183 -7,374 -8,423 -1,368 29,956 1,824 -19,993 46,588 64,411 40,986 64,856 84,983 88,115 136,923 151,965 50,599 7

Undiscounted cashflow US$'000 695,872 -28,183 -7,374 -8,423 -1,368 29,956 1,824 -19,993 46,588 64,411 40,986 64,856 84,983 88,115 136,923 151,965 50,599 7

Cumulative Undiscounted cashflow US$'000 -28,183 -35,557 -43,980 -45,348 -15,392 -13,568 -33,561 13,028 77,438 118,424 183,280 268,263 356,378 493,300 645,265 695,864 695,872

Discounted cashflow 6% US$'000 320,911 -26,588 -6,562 -7,072 -1,084 22,385 1,286 -13,297 29,230 38,125 22,886 34,165 42,234 41,312 60,561 63,410 19,918 3

Cumulative Discounted cashflow 6% US$'000 -26,588 -33,150 -40,223 -41,306 -18,921 -17,635 -30,932 -1,702 36,423 59,309 93,474 135,708 177,020 237,581 300,991 320,909 320,911


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Scenario six



2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032

1 2 3 4 5 6 7 8 9 10 11 12 13

Total Ore

Total Ore Mining kt 29,263 140 3,000 2,999 3,000 1,928 2,257 3,000 3,000 3,000 3,000 2,819 1,119 0

Total Gold Grade in Ore g/t 1.61 1.14 1.03 0.98 1.40 1.09 1.58 1.90 1.70 1.65 1.99 2.62 1.65 1.36

Total Gold in Ore kg 47,017 159 3,093 2,924 4,187 2,109 3,573 5,709 5,109 4,947 5,979 7,384 1,842 0

Waste Stripping

Waste Mining kt 384,795 26,073 56,580 57,001 57,000 58,072 57,249 34,600 18,596 6,788 6,477 5,575 783 1

Stripping Ratio W:O 13.1 186.0 18.9 19.0 19.0 30.1 25.4 11.5 6.2 2.3 2.2 2.0 0.7 3.2

Processing

Total Ore Processing kt 29,263 140 3,000 2,999 3,000 1,928 2,257 3,000 3,000 3,000 3,000 2,819 1,119 0

Total Gold Grade g/t 1.61 1.14 1.03 0.98 1.40 1.09 1.58 1.90 1.70 1.65 1.99 2.62 1.65 1.36

Recovered Gold Grade g/t 0.88 0.81 0.83 1.23 0.97 1.40 1.68 1.51 1.46 1.76 2.32 1.46 1.20

Total Gold in Ore kg 47,017 159 3,093 2,924 4,187 2,109 3,573 5,709 5,109 4,947 5,979 7,384 1,842 0

Gold Recovery % 87.6 77.5 79.0 84.9 88.1 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 41,174 123 2,442 2,483 3,689 1,866 3,162 5,052 4,521 4,377 5,292 6,535 1,630 0

Total Gold Extracted koz 1,323.8 4.0 78.5 79.8 118.6 60.0 101.7 162.4 145.4 140.7 170.1 210.1 52.4 0.0

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 1,654,732 4,958 98,133 99,805 148,274 75,011 127,090 203,032 181,692 175,905 212,677 262,641 65,497 18

Royalty US$'000 107,558 322 6,379 6,487 9,638 4,876 8,261 13,197 11,810 11,434 13,824 17,072 4,257 1

Refining and Transportation US$'000 4,117 12 244 248 369 187 316 505 452 438 529 654 163 0

Revenue US$'000 1,543,057 4,623 91,510 93,069 138,267 69,949 118,513 189,330 169,430 164,033 198,324 244,916 61,077 16

Operating Costs

Ore Mining US$'000 53,258 255 5,460 5,459 5,459 3,509 4,108 5,460 5,460 5,460 5,460 5,131 2,036 1

Waste Stripping US$'000 531,017 35,980 78,081 78,661 78,661 80,139 79,004 47,748 25,663 9,367 8,938 7,694 1,080 2

Total Mining US$'000 584,275 36,235 83,540 84,120 84,120 83,648 83,112 53,208 31,123 14,827 14,398 12,825 3,116 2

Processing US$'000 114,212 547 11,708 11,706 11,707 7,526 8,810 11,709 11,709 11,709 11,709 11,004 4,366 1

Transport to plant US$'000 34,786 167 3,566 3,565 3,566 2,292 2,683 3,566 3,566 3,566 3,566 3,352 1,330 0

G & A US$'000 83,756 401 8,586 8,585 8,585 5,519 6,461 8,587 8,587 8,587 8,587 8,070 3,202 1

Cashflow

Net Revenue US$'000 726,027 -32,727 -15,890 -14,907 30,289 -29,036 17,447 112,259 114,445 125,344 160,063 209,666 49,063 11

Undiscounted cashflow US$'000 726,027 -32,727 -15,890 -14,907 30,289 -29,036 17,447 112,259 114,445 125,344 160,063 209,666 49,063 11

Cummulative Undiscounted cashflow US$'000 -32,727 -48,617 -63,524 -33,236 -62,272 -44,825 67,434 181,879 307,223 467,286 676,952 726,016 726,027

Discounted cashflow 6% US$'000 401,930 -30,875 -14,142 -12,516 23,992 -21,698 12,299 74,659 71,804 74,191 89,379 110,449 24,383 5

Cumulative Discounted cashflow 6% US$'000 -30,875 -45,017 -57,533 -33,542 -55,239 -42,940 31,719 103,523 177,714 267,093 377,542 401,925 401,930


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amcconsultants.com Appendix C – 1

Appendix C

Vostochny preliminary financial models



Vostochny Deposit Production Schedule - MII Open Pit RF1 Ultimate Pit

8 Mtpa TMM Limit, 0.4 Mtpa Plant Limit, 4 Stage - Pit Shell 9, 14, 17, 31

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Total Ore

Total Ore Mining kt 6,955 362 354 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 240

Total Gold Grade in Ore g/t 1.45 1.39 2.11 1.42 1.23 1.42 1.68 1.51 1.60 1.31 1.37 1.63 1.37 1.14 1.29 1.30 1.35 1.57 1.46

Total Gold in Ore kg 10,068 505 748 566 491 566 670 602 641 524 549 651 548 454 517 520 540 627 350

Waste Stripping

Waste Mining kt 85,800 6,392 7,646 7,599 7,600 7,600 7,600 7,600 7,600 7,600 7,599 5,118 1,872 1,090 931 721 525 415 290

Stripping Ratio W:O 12.3 17.7 21.6 19.0 19.0 19.0 19.0 19.0 19.0 19.0 19.0 12.8 4.7 2.7 2.3 1.8 1.3 1.0 1.2

Processing

Total Ore Processing kt 6,955 362 354 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 240

Total Gold Grade g/t 1.45 1.39 2.11 1.42 1.23 1.42 1.68 1.51 1.60 1.31 1.37 1.63 1.37 1.14 1.29 1.30 1.35 1.57 1.46

Recovered Gold Grade g/t 1.13 1.83 1.20 1.08 1.23 1.47 1.33 1.42 1.16 1.21 1.44 1.21 1.00 1.14 1.15 1.19 1.39 1.29

Total Gold in Ore kg 10,068 505 748 566 491 566 670 602 641 524 549 651 548 454 517 520 540 627 350

Gold Recovery % 87.5 81.1 86.5 84.7 87.6 86.7 87.9 88.2 88.3 88.4 88.4 88.5 88.5 88.5 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 8,813 409 647 480 430 491 589 531 566 464 485 576 485 402 458 460 478 555 309

Total Gold Extracted koz 283.4 13.2 20.8 15.4 13.8 15.8 18.9 17.1 18.2 14.9 15.6 18.5 15.6 12.9 14.7 14.8 15.4 17.9 9.9

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 354,191 16,451 26,003 19,274 17,293 19,721 23,651 21,330 22,740 18,628 19,499 23,149 19,483 16,140 18,390 18,503 19,194 22,313 12,429

Royalty US$'000 23,022 1,069 1,690 1,253 1,124 1,282 1,537 1,386 1,478 1,211 1,267 1,505 1,266 1,049 1,195 1,203 1,248 1,450 808

Refining and Transportation US$'000 881 41 65 48 43 49 59 53 57 46 49 58 48 40 46 46 48 56 31

Revenue US$'000 330,288 15,341 24,248 17,974 16,126 18,390 22,055 19,891 21,206 17,371 18,183 21,586 18,168 15,050 17,149 17,254 17,899 20,807 11,590

Operating Costs

Ore Mining US$'000 12,658 659 645 728 727 728 728 728 728 728 728 728 728 728 728 728 728 728 436

Waste Stripping US$'000 118,403 8,821 10,551 10,487 10,489 10,488 10,488 10,488 10,488 10,488 10,487 7,063 2,584 1,504 1,285 995 724 573 400

Total Mining US$'000 131,062 9,479 11,196 11,215 11,216 11,216 11,216 11,216 11,216 11,216 11,215 7,791 3,312 2,232 2,013 1,723 1,452 1,301 836

Processing US$'000 53,206 2,769 2,711 3,060 3,056 3,060 3,058 3,060 3,059 3,059 3,060 3,060 3,060 3,060 3,060 3,060 3,060 3,060 1,834

Transport to plant US$'000 16,205 843 826 932 931 932 932 932 932 932 932 932 932 932 932 932 932 932 559

G & A US$'000 39,018 2,030 1,988 2,244 2,241 2,244 2,243 2,244 2,243 2,244 2,244 2,244 2,244 2,244 2,244 2,244 2,244 2,244 1,345

Cashflow

Net Revenue US$'000 90,797 219 7,528 522 -1,318 939 4,606 2,439 3,755 -80 732 7,559 8,621 6,582 8,901 9,295 10,210 13,269 7,016

Profit Tax US$'000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Undiscounted cashflow US$'000 90,797 219 7,528 522 -1,318 939 4,606 2,439 3,755 -80 732 7,559 8,621 6,582 8,901 9,295 10,210 13,269 7,016

Cummulative Undiscounted cashflow US$'000 219 7,747 8,269 6,951 7,890 12,496 14,936 18,691 18,611 19,343 26,902 35,523 42,105 51,006 60,301 70,511 83,780 90,797

Discounted cashflow -6% US$'000 45,162 206 6,700 439 -1,044 702 3,247 1,622 2,356 -47 409 3,982 4,284 3,086 3,937 3,878 4,019 4,928 2,458

Cummulative Discounted cashflow -6% US$'000 206 6,906 7,345 6,301 7,003 10,250 11,872 14,228 14,181 14,590 18,572 22,856 25,942 29,879 33,757 37,776 42,704 45,162

Units TotalParameter Years

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Vostochny Deposit Production Schedule - MII Open Pit RF1 Ultimate Pit

20 Mtpa TMM Limit, 1 Mtpa Plant Limit, 3 Stage - Pit Shell 9, 11, 31

Parameter

Units Total 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

1 2 3 4 5 6 7 8 9 10

Total Ore

Total Ore Mining kt 7,899 372 562 827 999 1,000 1,000 1,000 1,000 1,000 140

Total Gold Grade in Ore g/t 1.39 1.37 1.89 1.33 1.23 1.48 1.67 1.10 1.20 1.46 1.28

Total Gold in Ore kg 10,987 509 1,060 1,096 1,230 1,480 1,674 1,102 1,195 1,463 178

Waste Stripping

Waste Mining kt 99,304 6,653 19,438 19,173 19,001 19,000 9,346 3,098 2,006 1,404 184

Stripping Ratio W:O 12.6 17.9 34.6 23.2 19.0 19.0 9.3 3.1 2.0 1.4 1.3

Processing

Total Ore Processing kt 7,899 372 562 827 999 1,000 1,000 1,000 1,000 1,000 140

Total Gold Grade g/t 1.39 1.37 1.89 1.33 1.23 1.48 1.67 1.10 1.20 1.46 1.28

Recovered Gold Grade g/t 1.11 1.62 1.14 1.08 1.31 1.48 0.98 1.06 1.30 1.13

Total Gold in Ore kg 10,987 509 1,060 1,096 1,230 1,480 1,674 1,102 1,195 1,463 178

Gold Recovery % 87.6 81.1 86.0 86.2 88.1 88.4 88.5 88.5 88.5 88.5 88.5

Total Gold Extracted kg 9,627 413 912 945 1,083 1,308 1,481 975 1,058 1,295 158

Total Gold Extracted koz 309.5 13.3 29.3 30.4 34.8 42.0 47.6 31.3 34.0 41.6 5.1

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 386,895 16,586 36,635 37,967 43,538 52,562 59,519 39,184 42,519 52,044 6,342

Royalty US$'000 25,148 1,078 2,381 2,468 2,830 3,417 3,869 2,547 2,764 3,383 412

Refining and Transportation US$'000 963 41 91 94 108 131 148 98 106 130 16

Revenue US$'000 360,784 15,467 34,163 35,404 40,599 49,014 55,502 36,539 39,650 48,532 5,914

Operating Costs

Ore Mining US$'000 14,376 677 1,022 1,504 1,819 1,820 1,820 1,820 1,820 1,820 254

Waste Stripping US$'000 137,040 9,181 26,825 26,459 26,221 26,220 12,898 4,275 2,769 1,937 255

Total Mining US$'000 151,416 9,858 27,847 27,964 28,040 28,040 14,718 6,095 4,589 3,757 509

Processing US$'000 44,475 2,093 3,162 4,654 5,627 5,630 5,630 5,630 5,630 5,630 787

Transport to plant US$'000 13,546 638 963 1,417 1,714 1,715 1,715 1,715 1,715 1,715 240

G & A US$'000 32,615 1,535 2,319 3,413 4,126 4,129 4,129 4,129 4,129 4,129 577

Cashflow

Net Revenue US$'000 118,732 1,343 -129 -2,043 1,092 9,501 29,310 18,970 23,587 33,300 3,801

Profit Tax US$'000 0 0 0 0 0 0 0 0 0 0 0

Undiscounted cashflow US$'000 118,732 1,343 -129 -2,043 1,092 9,501 29,310 18,970 23,587 33,300 3,801

Cummulative Undiscounted cashflow US$'000 1,343 1,214 -830 263 9,764 39,074 58,044 81,631 114,931 118,732

Discounted cashflow -6% US$'000 77,312 1,267 -115 -1,715 865 7,100 20,663 12,616 14,799 19,710 2,123

Cummulative Discounted cashflow -6% US$'000 1,267 1,152 -564 302 7,401 28,064 40,680 55,479 75,189 77,312

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amcconsultants.com Appendix D – 1

Appendix D

Combined Krasny and Vostochny cash flow

analysis



Micon Krasny Production Schedule

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Total Ore

Total Ore Mining kt 7,342 433 578 578 575 572 570 570 570 571 571 568 570 557 61

Total Gold Grade in Ore g/t 1.09 1.02 1.00 1.01 1.01 1.08 1.13 1.12 1.14 1.12 1.11 1.16 1.15 1.10 1.13

Total Gold in Ore kg 7,999 440 580 581 580 615 643 640 652 639 634 658 658 611 68

Waste Stripping

Waste Mining kt 46,944 2,794 2,925 3,159 3,416 3,930 3,945 4,496 4,496 4,480 3,945 3,444 2,964 2,800 397

Stripping Ratio W:O 6.4 6.5 5.1 5.5 5.9 6.9 6.9 7.9 7.9 7.8 6.9 6.1 5.2 5.0 6.5

Processing

Total Ore Processing kt 7,342 300 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 242

Total Gold Grade g/t 1.09 1.26 1.24 1.24 1.25 1.33 1.39 1.39 1.41 1.39 1.38 1.43 1.43 1.35 0.58 0.48 0.48 0.49 0.49 0.49

Recovered Gold Grade g/t 0.91 1.02 1.02 1.02 1.04 1.10 1.16 1.17 1.19 1.15 1.14 1.20 1.26 1.19 0.52 0.42 0.42 0.40 0.38 0.38

Total Gold in Ore kg 7,999 377 497 497 499 531 557 555 565 554 550 573 574 541 234 193 192 195 196 119

Gold Recovery % 83.9% 81.0 82.0 82.0 83.0 83.0 83.0 84.0 84.0 83.0 83.0 84.0 88.0 88.0 89.0 88.0 88.0 81.0 78.0 78.0

Total Gold Extracted kg 6,708 306 406 407 412 440 464 464 473 462 458 483 506 478 207 170 169 158 152 92

Total Gold Extracted koz 215.7 9.8 13.1 13.1 13.2 14.1 14.9 14.9 15.2 14.9 14.7 15.5 16.3 15.4 6.7 5.5 5.4 5.1 4.9 3.0

Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 269,598 12,311 16,325 16,367 16,546 17,699 18,644 18,653 19,025 18,563 18,420 19,417 20,322 19,223 8,312 6,825 6,787 6,336 6,120 3,703

Royalty US$'000 16,176 739 980 982 993 1,062 1,119 1,119 1,142 1,114 1,105 1,165 1,219 1,153 499 409 407 380 367 222

Refining and Transportation US$'000 850 39 51 52 52 56 59 59 60 59 58 61 64 61 26 22 21 20 19 12

Revenue US$'000 252,572 11,533 15,294 15,333 15,501 16,581 17,466 17,475 17,823 17,390 17,257 18,191 19,039 18,009 7,787 6,394 6,359 5,936 5,734 3,469

Operating Costs

Ore Mining US$'000 9,723 567 756 756 756 756 756 756 756 756 756 755 757 757 83 0 0 0 0 0

Waste Stripping US$'000 68,839 4,081 4,823 5,009 5,194 5,565 5,565 5,936 5,936 5,936 5,565 5,194 4,823 4,638 575 0 0 0 0 0

Total Mining US$'000 78,562 4,648 5,579 5,765 5,950 6,321 6,321 6,692 6,692 6,692 6,321 5,949 5,580 5,395 658 0 0 0 0 0

Processing US$'000 56,160 2,295 3,059 3,059 3,059 3,059 3,059 3,059 3,059 3,059 3,059 3,057 3,062 3,063 3,059 3,059 3,059 3,059 3,059 1,851

Transport to plant US$'000 8,554 350 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 282

Ore Rehandling to plant US$'000 275 0 0 0 0 0 0 0 0 0 0 0 0 0 45 50 50 50 50 30

G & A US$'000 21,912 1,246 1,661 1,661 1,661 1,661 1,661 1,661 1,661 1,661 1,661 1,660 1,662 1,663 272 100 100 100 100 61

Cashflow

Net Revenue US$'000 87,109 2,994 4,529 4,382 4,365 5,074 5,959 5,597 5,945 5,512 5,750 7,059 8,269 7,422 3,287 2,719 2,684 2,261 2,059 1,245

Capital (Taken directly from Costs) US$'000 41,998

Undiscounted cashflow US$'000 87,109 39,004 4,529 4,382 4,365 5,074 5,959 5,597 5,945 5,512 5,750 7,059 8,269 7,422 3,287 2,719 2,684 2,261 2,059 1,245

Cumulative Undiscounted cashflow US$'000 -39,004 -34,475 -30,093 -25,728 -20,654 -14,695 -9,098 -3,153 2,359 8,109 15,168 23,437 30,859 34,146 36,865 39,549 41,810 43,869 45,114

Discounted cashflow 6% US$'000 13,215 -36,796 4,031 3,679 3,457 3,792 4,201 3,722 3,730 3,263 3,211 3,719 4,109 3,480 1,454 1,135 1,057 840 721 411

Cumulative Discounted cashflow 6% US$'000 -36,796 -32,765 -29,086 -25,629 -21,837 -17,636 -13,914 -10,184 -6,921 -3,711 8 4,117 7,597 9,051 10,185 11,242 12,082 12,803 13,215

Parameter Units Total Years



Combined Krasny MI Open Pit, Krasny Underground and Vostochny Production Schedule

Note – Analysis excludes Profit Tax

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Ore Mining

Krasny Ore Mining kt 7,287 802 1,000 999 1,000 948 1,000 1,000 540

Krasny Gold Grade in Ore g/t 1.10 1.36 0.91 1.00 1.11 1.11 1.06 1.21 1.15

Vostochnoye Ore Mining kt 4,030 361 362 429 432 513 513 513 513 394

Vostochnoye Gold Grade in Ore g/t 1.52 1.40 2.11 1.42 1.21 1.36 1.26 2.07 1.38 1.57

Krasny Underground Ore Mining kt 3,295 365 487 487 487 487 487 487 10

Krasny Underground Gold Grade in Ore g/t 3.89 4.09 3.68 3.51 3.81 4.24 4.21 3.76 3.33

Total Ore Mining kt 14,613 802 1,000 999 1,000 948 1,000 1,000 901 727 916 919 1,000 1,000 1,000 1,000 403


Total Gold in Ore kg 26,997 1,093 913 995 1,109 1,047 1,064 1,209 1,125 2,255 2,400 2,232 2,552 2,710 3,108 2,536 650

Waste Stripping

Krasny Waste Mining kt 32,772 5,198 5,000 5,001 5,000 5,052 4,858 2,006 656

Vostochnoye Waste Mining kt 42,811 4,322 7,272 7,571 7,568 7,486 6,470 1,477 484 162

Total Waste Mining kt 75,583 5,198 5,000 5,001 5,000 5,052 4,858 2,006 4,979 7,272 7,571 7,568 7,486 6,470 1,477 484 162


Processing

Total Ore Processing kt 14,613 802 1,000 999 1,000 948 1,000 1,000 901 727 916 919 1,000 1,000 1,000 1,000 403


Krasny Recovered Gold Grade g/t 0.93 1.06 0.71 0.81 0.93 0.96 0.93 1.07 1.02

Vostochnoye Recovered Gold Grade g/t 1.33 1.13 1.82 1.20 1.06 1.20 1.12 1.83 1.22 1.39

Krasny Underground Recovered Gold Grade g/t 3.44 3.62 3.26 3.11 3.37 3.75 3.72 3.33 2.94

Recovered Gold Grade g/t 1.60 1.06 0.71 0.81 0.93 0.96 0.93 1.07 1.06 2.73 2.29 2.15 2.26 2.40 2.75 2.25 1.43

Total Gold in Ore kg 26,997 1,093 913 995 1,109 1,047 1,064 1,209 1,125 2,255 2,400 2,232 2,552 2,710 3,108 2,536 650

Gold Recovery % 86.8 77.5 78.0 81.1 83.9 87.1 87.4 88.3 85.2 87.8 87.6 88.4 88.4 88.5 88.5 88.5 88.5

Total Gold Extracted kg 23,442 846 712 807 930 912 930 1,068 959 1,981 2,102 1,972 2,256 2,397 2,751 2,244 576


Revenue

Gold Price US$/oz 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250 1,250

Gold Value US$'000 942,096 34,018 28,604 32,439 37,362 36,636 37,375 42,921 38,547 79,602 84,460 79,265 90,647 96,341 110,548 90,201 23,129

Royalty US$'000 61,236 2,211 1,859 2,109 2,429 2,381 2,429 2,790 2,506 5,174 5,490 5,152 5,892 6,262 7,186 5,863 1,503

Refining and Transportation US$'000 2,344 85 71 81 93 91 93 107 96 198 210 197 226 240 275 224 58

Revenue US$'000 878,516 31,722 26,674 30,250 34,840 34,164 34,853 40,025 35,946 74,229 78,760 73,915 84,530 89,839 103,087 84,114 21,568

Operating Costs

Ore Mining US$'000 251,235 1,459 1,819 1,818 1,819 1,725 1,820 1,820 1,639 26,211 34,851 34,857 35,003 35,003 35,003 35,003 1,383

Waste Stripping US$'000 104,304 7,174 6,900 6,901 6,901 6,972 6,703 2,768 6,870 10,035 10,447 10,443 10,331 8,928 2,039 668 224

Total Mining US$'000 355,540 8,633 8,720 8,720 8,720 8,697 8,523 4,588 8,510 36,245 45,299 45,300 45,334 43,932 37,042 35,671 1,607

Processing US$'000 162,568 4,513 5,628 5,625 5,628 5,336 5,630 5,630 5,072 12,987 17,019 17,036 17,490 17,490 17,490 17,490 2,503

Transport to plant US$'000 19,409 1,375 1,714 1,713 1,714 1,625 1,715 1,715 1,545 620 736 742 880 880 880 880 675

G & A US$'000 46,730 3,310 4,128 4,125 4,127 3,913 4,129 4,129 3,719 1,493 1,773 1,786 2,118 2,118 2,118 2,118 1,626

Cashflow

Net Revenue US$'000 294,269 13,892 6,484 10,068 14,650 14,594 14,855 23,963 17,100 22,883 13,932 9,051 18,708 25,420 45,558 27,955 15,156

Profit Tax 0% US$'000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Capital (Taken directly from Costs) US$'000 107,436 65,574 41,862

Undiscounted cashflow US$'000 186,834 -51,681 6,484 10,068 14,650 14,594 14,855 23,963 -24,762 22,883 13,932 9,051 18,708 25,420 45,558 27,955 15,156

Cummulative Undiscounted cashflow US$'000 -51,681 -45,198 -35,130 -20,480 -5,886 8,969 32,932 8,170 31,053 44,986 54,037 72,745 98,165 143,722 171,677 186,834

Discounted cashflow 6% US$'000 83,939 -48,756 5,770 8,453 11,604 10,905 10,472 15,937 -15,536 13,544 7,780 4,768 9,297 11,918 20,150 11,665 5,966

Cumulative Discounted cashflow 6% US$'000 -48,756 -42,986 -34,532 -22,928 -12,023 -1,551 14,386 -1,150 12,395 20,174 24,943 34,240 46,158 66,308 77,972 83,939

Parameter Units Total Years


amcconsultants.com Appendix E – 1

Appendix E Memorandum: Krasny Scoping Study Mine

Production Scenarios and Key Financial

Outcomes

AMC Consultants Pty Ltd ABN 58 008 129 164


West Perth WA 6005

Australia

T +61 8 6330 1100

E [email protected]

W amcconsultants.com

MEMORANDUM

To: Mikhail Damrin, Chief Executive Officer, Kopy Goldfields AB

From: Adrian Jones, Principal Mining Engineer, AMC Consultants (Perth)

cc: Mark Chesher, Technical Director, AMC Consultants (Moscow)

Date: 29 May 2019

Subject: Krasny Scoping Study mine production scenarios and key financial outcomes

Dear Mikhail

The following summary highlights the mine production scenarios and key financial outcomes of

the Krasny Project Scoping Study activities.


Project (Project) Scoping Study (the Study).

Kopy’s brief was to proceed with the Study based on a resource model prepared by others. The

Study includes a review of the proposed approach to mine development options for the Krasny Project, a preliminary review of the resource model and Mineral Resource estimate, and an



The review activities have also considered the economic viability of the Vostochny exploration

area, with a preliminary review of resource model and an outline economic assessment of the


Krasny mining review

AMC undertook a review of the available mining reports to consider the deposit’s potential to be

developed into a viable economic mining operation. AMC have also performed a series of Project sensitivity analyses to investigate the potential opportunities to enhance the economic viability


Comparison of Krasnoe open pit optimization results

Details of Revenue Factor 1 (RF1) pit optimization output shells generated by AMC and the historical study work (Micon, 2018) for Measured, Indicated, and Inferred Mineral Resources

(MII) and Measured and Indicated Mineral Resources (MI) cases are summarized in Table I. The

RF1 pit shells generated by AMC and Micon are similar in size with a variance of 2% to 5% in total material. The AMC pit shells achieved a similar depth and contained 3% to 6% less ore

tonnage compared to Micon RF1 pit shells.

AMC218143 Krasny Scoping Study Memo 190624 2

Table I Comparison of AMC and Micon open pit optimization results


Figure I.

Figure I West east cross section of RF1 pit shells





It is worth noting that the project is characterized by large quantities of marginally economic grade ore, and relatively small fluctuations in the application of cut-off grade result in significant


Inspection of the Krasnoe grade-tonnage curve illustrates that around the cut-off grade of 0.4 g/t gold, which is the limit applied to the current Project Ore Reserve statement, there are sharp



artificially swell the ore inventory of the optimization outputs and may lead to negative impacts on the project financial results. The Krasnoe grade-tonnage curve graph is shown below in

Figure II.

AMC utilized a cut-off grade of between 0.5g/t gold to 5.0g/t gold for the calculation of underground inventories utilizing the Mineable Shape Optimizer (MSO). The open pit Whittle pit

optimizations utilized 0.4g/t gold cut-off, in order to be comparable to the previous iterations of work and align with the currently quoted 2018 Ore Reserve reporting by Micon. The combined


Factor

Total

Mining

Waste Ore Stripping

Ratio

Gold Gold Gold

g/t (Mt) (Mt) (Mt) (t:t) (kg) (oz) (g/t)

MII Micon 0.40 1 383.4 356.7 26.7 13.36 43,890 1,411 1.64

MII AMC 0.40 1 364.4 338.3 26.0 12.99 43,958 1,413 1.69

Variance -5.0 -5.1 -2.5 -2.8 0.2 0.2 2.9

MI Micon 0.40 1 38.6 31.9 6.7 4.76 7,659 246 1.14

MI AMC 0.40 1 37.8 31.5 6.3 5.00 7,565 243 1.20

Variance -2.0 -1.1 -5.9 5.0 -1.2 -1.2 5.2



open pit and underground production scenarios reported here by AMC, are based upon a higher



AMC recommends estimating a cutoff grade that more closely represents the calculated cutoff from operating costs and gold recoveries. This is likely to be higher in future studies and is likely


Figure II Grade tonnage curve

Krasnoe open pit optimization sensitivity

The sensitivity of the project open pit optimization results to variations in the major input

parameters was tested by changing the value of individual parameters while keeping all others

constant. Individual parameters changed include:

• Metal price.


• Mining cost.




Sensitivity analysis was completed for both Measured and Indicated (MI) and Measured,

Indicated and Inferred (MII) resource category scenarios. The RF1 pit shells were selected for

parameter variance to explore the sensitivity of output shell size and corresponding financial metrics. The applied variation range for the input parameters were ±50% for metal price,

processing cost and mining cost. +50% to +400% for production rate, ±5° for pit slopes and

-10% to +2% for recovery.

Changes in the undiscounted cash flow variance for each parameter have been plotted, where a steeper slope on any curve represents greater sensitivity to the parameter represented by that

curve.

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The sensitivity analysis demonstrates that the undiscounted cash flow is most sensitive to

changes in gold price. A 10% reduction in gold price results in a 27% decrease in undiscounted

cash flow. A 10% increase in processing cost results in an 8% decrease in cash flow.

The ore tonnage is sensitive to changes in gold price. A 10% reduction in gold price results in an 5% decrease in ore tonnage. A 10% increase in processing cost results in a 4% decrease in

ore tonnage.

AMC notes an average mining cost was applied in the open pit optimizations. The MII open pit

optimizations achieve a greater depth compared to the MI case. Application of an incremental mining cost will have a significant impact on the pit optimization due to the increased stripping

ratio of the larger MII open pit shells. The sensitivity analysis shows a 30% increase in mining

cost results in an 25% decrease in cash flow. AMC recommend more detailed work be undertaken, during future study activities, to more accurately determine the variable open pit

mining cost in the deeper MII open pit optimizations.


tonnes with results presented in Figure III for undiscounted cash flow sensitivity.

Figure III Krasnoe MII sensitivity - undiscounted cash flow

Krasnoe underground optimization

The underground potential was assessed and optimized using the MSO process in Datamine’s

5D Planner (5DP) software package. This process generates stope shapes at a range of variables including cut-off grades, floor to floor lift heights, stope widths and stope strike lengths. This

allows a relatively quick assessment of a deposit’s applicability for underground exploitation, the types of mining methodology that may be applied (together with geological and geotechnical

inputs) and a preliminary assessment of potential mining inventory.

AMC conducted two types of MSO assessments. The first MSO assessment was to determine the

suitability of the block model with the MSO process. This involved running MSO in multiple

scenarios with differing stope dimensions to ascertain any limiting or preferable variables. The

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results of this initial assessment showed that the block model was robust and that no limiting




minimum 1.5 m stope width as these stoping dimensions allow extraction by the most commonly used underground mining equipment. The MSO process was ran using these stoping dimensions


The MINPROP field was not utilized in the underground optimization component of this work.

This is due to the fact that the underground MSO shapes have external dilution added to their



Krasnoe production scheduling


production to the processing plant. The 2018 Mineral Resource and Ore Reserve report considered a nominal plant throughput rate of 0.4 Mtpa, which AMC considers to be very low for

the magnitude of the Krasny project. To present an easy comparison with the previous iterations

of study work, AMC has considered the same nominal plant throughput rate of 0.4 Mtpa, as well as presenting an additional analysis of 1.0 Mtpa, 2.0 Mtpa and 3.0 Mtpa throughputs, as a higher

production rate is likely to present more favourable economic outcomes.



consideration of underground mining. The six scenarios are defined as follows:




• Scenario 4 combined open pit and underground – 1.0 Mtpa plant throughput.



Krasnoe cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of each production scenario. The cumulative undiscounted cash flow is presented in Figure IV and

cumulative discounted cash flow is presented in Figure V. A discount rate of 6% was used. Cash flows for the Micon scenario was derived from the Micon report. The pre-production years,

capital, property tax and profit tax have been removed for comparison purposes.


Figure IV Cumulative undiscounted cash flow excluding capital

Figure V Cumulative discounted cash flow excluding capital

The outcomes of cash flow analysis show benefit in increasing the plant throughput rate from 0.4 Mtpa to 1.0 Mtpa. In the MI open pit scenario, the discounted value increased by 31%,

exclusive of capital expenditure. By increasing the ore production rate, value is realized much




MI open pit captures a significant portion of the mineralization near surface and the remaining portion of the orebody is at much greater depths. A significant amount of waste stripping is

required upfront, to expose the mineralization in latter cutbacks, to maintain ore production


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compared to the 1.0 Mtpa MII open pit. The transition to underground does not require immediate capital investment, as in the MII open pit scenario, as a portal can be established




AMC recommends future work should consider:

• Detailed ultimate pit and stage pit designs. Whittle pit shells provide guidance for developing an optimal ultimate pit. Consideration of access and practicality issues

associated with pit staging will often result in variances between design and pit shell.

Additional waste is likely to be brought forward in a production schedule based on pit


• Dilution and ore loss analysis. There are areas of the Krasny orebodies which contains narrow vein mineralization where the application of dilution and ore loss factors in Whittle

is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones that cannot be selectively mined to the level of accuracy suggested by these modifying






Exploration target – Vostochny


north-east of the Krasnoe deposit.

Vostochny pit optimization


resources.

Vostochny production scheduling

Preliminary production schedules were undertaken using the Milawa scheduler in Whittle. Milawa

was used to determine the required material movement rate to deliver steady-state ore production to the processing plant. AMC has considered a nominal plant throughput rate of


Vostochny cash flow analysis


production scenario. The cumulative undiscounted cash flow is presented in Figure VI and

cumulative discounted cash flow is presented in Figure VII.

The outcomes of cash flow analysis show a three-year period where the project is approximately cash flow neutral at a plant throughput rate of 1.0 Mtpa due to high material movement. There

is a difference of approximately US$32M in discounted cash flow between the 0.4 Mtpa and





Figure VI Cumulative undiscounted cash flow excluding capital

Figure VII Cumulative discounted cash flow excluding capital



developing an optimal ultimate pit. Consideration of access and practicality issues associated with pit staging will often result in variances between design and pit shell.

Additional waste is likely to be brought forward in a production schedule based on pit


• Dilution and ore loss analysis. There are areas of the Vostochny orebody, which contains

narrow vein mineralization, where the application of dilution and ore loss factors in Whittle is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones

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that cannot be selectively mined to the level of accuracy suggested by these modifying






Combined Krasnoe and Vostochny production scenario

AMC has evaluated a combined production scenario of the Krasnoe deposit and Vostochny mineral occurrence. This scenario can be considered as an extension of the Krasnoe open pit

and underground scenario, with development of the Vostochny open pit beginning in 2030. Development of the Vostochny open pit is intended to supplement the underground ore

production from Krasnoe, rather than being operated as a standalone mining operation. Ore sourced from Vostochny will aid in maintaining the utilization of the processing plant capacity of

1.0 Mtpa for the life of the combined Krasnoe and Vostochny mining operations.

The Krasnoe underground mine will provide a nominal 0.487 Mtpa of ore production for approximately nine years. Previous analysis of Vostochny showed that a total material movement

of 20 Mtpa was required to sustain ore production at 1.0 Mtpa without supplementation from external sources. This suggests that sustaining 1.0 Mtpa of ore production after completion of

Krasnoe underground would require significant capital investment due to the additional

requirements in mining capacity.

The annual head grade, ore and waste movements are summarized in Figure VIII. Ore production

from Vostochny begins in 2027 and ore production from Krasnoe underground begins in 2028.

Figure VIII Combined Krasnoe and Vostochny production profile

Combined Krasnoe and Vostochny cash flow analysis

AMC prepared a high-level financial model to determine the operating cash flows of the combined Krasnoe and Vostochny production scenario. The cumulative undiscounted cash flow is presented

in Figure IX and cumulative discounted cash flow is presented in Figure X. A discount rate of 6%

was used.

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Figure IX Cumulative undiscounted cash flow excluding capital

Figure X Cumulative discounted cash flow excluding capital

Combined Krasnoe and Vostochny cash flow comparison

AMC has used Micon’s assessment of capital costs in the 2018 Mineral Resource and Ore Reserve report to provide high-level indicative cash flows inclusive of capital costs for each production

scenario. Micon’s capital cost estimates were based on an operation with 0.4 Mtpa plant capacity

and 5 Mtpa mining capacity.

AMC has used the six-tenths rule to scale Micon’s capital estimates to cover the spectrum of processing and mining rates that have been presented. Different configurations of plant and

mining equipment would be more appropriate for larger scale operation. The scalability of mining

equipment has not been considered in this cash flow analysis and a capital cost schedule has not been produced. This rudimentary approach to the capital analysis provides a basic comparative

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The joint Krasnoe and Vostochny cumulative undiscounted cash flow including capital is

presented in Figure XI and cumulative discounted cash flow including capital is presented in

Figure XII.

Figure XI Undiscounted cash flow including capital

Figure XII Discounted cash flow including capital

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Krasnoe and Vostochny combined production scenario summary

Inclusion of gold resources from the Vostochny deposit may extend the mine life and strengthen economics of the project. One production scenario to achieve this might involve a plant

throughput of 1 Mt per year for an initial 12 years of operation focusing primarily on the Krasnoe Upper structure. A total of 380,000 ounces of gold could be produced at this stage. In parallel,

exploration at the Krasnoe Lower structure and Vostochny could proceed to allow the application of the Modifying Factors via a PFS or FS to convert Mineral Resources to Ore Reserves and

prepare for production.

Starting from year 11 and until the end of mine life, Vostochny open pit mine could then produce

on average 500,000 tpa of plant feed totaling approximately 200,000 ounces of gold. An

additional 500,000 tpa could be sourced from a Krasnoe underground operation, with total

production in excess of 400,000 ounces of gold at full capacity until around year 20.

Although this mining scenario does not provide the highest NPV, it offers the shortest pay-back period, the highest IRR and also modest up-front CAPEX to commence gold production. This

production scenario could be launched with limited further exploration needed to complete FS.

Krasnoe and Vostochny production scenario summary

The four production scenarios, that demonstrate the key outcomes of the Krasnoe scoping study outputs, are the 0.4 Mtpa open pit (comparable to the Micon 2018 Ore Reserve statement

report), the 1 Mtpa combined open pit and underground operations scenario, and an increased

production rate of 3 Mtpa open pit only Krasnoe scenario. A final scenario consisting of the mining of the Krasnoe open pit, followed by the mining of a combination of Krasnoe underground

operation and parallel mining of the Vostochny open pit, at a production rate of 1 Mtpa. Table II

illustrates the summary results of the four key production scenarios.

Table II Key Krasnoe and Vostochny production scenarios

Production Scenario 0.4 Mtpa

Open Pit**

1 Mtpa Open

pit and

Underground

3 Mtpa

Open Pit**

1 Mtpa Krasnoe

Open pit and

Underground

with Vostochny

Pre-tax NPV at 6% discount rate, MUSD 16 62 301 104

Pre-tax IRR, % 11 23 20 26

LOM, years 16 15 12 16

Mill capacity pa, Mt 0.4 1.0 3.0 1.0

Average gold grade, g/t 1.2 2.0 1.6 1.8

Total CAPEX, MUSD 38 105 150 107

Average open pit stripping ratio, t/t 5.0 4.5 13 7

Average LOM annual gold production, kOz 13 39 110 47

Average operating costs, USD/oz 860 1,100 930 1,100

Pre-tax undiscounted pay-back period, years 11 5 8 5

** Indicates options that include production from Krasnoe open pit only.

For the current presentation of resource modelling, mineral processing and economics inputs; AMC considers the mining of the Krasnoe open pit followed by the parallel mining of the Krasnoe

underground and Vostochny open pit production scenarios, at a production rate of 1.0 Mtpa, to

produce the highest combined project value balanced, against cash flow risk, which equates to the highest pre-tax internal rate of return (IRR) for the Krasnoe and Vostochny production

scenarios.

Combined Krasnoe and Vostochny sensitivity analysis summary

A project cash flow sensitivity has been calculated for various key parameters for the mining of the Krasnoe open pit followed by the parallel mining of the Krasnoe underground and Vostochny


open pit production scenarios. Table III shows the results of the sensitivity analysis performed

for variance of gold price, discount rate and percentage gold grade.

Table III Krasnoe and Vostochny base case sensitivity analysis


Gold price (USD/Oz) 1,200 1,250 1,300 1,350 1,400


IRR (%) 19 22 26 29 32


DCF, pre-tax (MUSD) 118.2 104.2 91.9 80.9 71.2


DCF, pre-tax (MUSD) 51.6 77.9 104.2 130.6 156.9

IRR (%) 16 21 26 30 34






• Dilution and ore loss analysis. There are areas of Krasnoe and Vostochny orebodies which contain narrow vein mineralization where the application of dilution and ore loss factors in

Whittle is not appropriate. Some areas of the pit optimization are being driven by narrow ore zones that cannot be selectively mined to the level of accuracy suggested by these




pit scenarios.


scenarios.



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