117631031-022-r-rev1-anthill resource estimate 2012 · and complete the resource estimate using cae...

4 December 2012

ANTHILL COPPER DEPOSIT

Mineral Resource Estimate 2012

RE

PO

RT

Report Number. 117631031-22 Rev1

Distribution:

Qi Deng

Submitted to: Qi Deng CST Minerals Lady Annie Pty Ltd

ANTHILL MINERAL RESOURCE AND RESERVE ESTIMATE 2012

4 December 2012 Report No. 117631031-22 Rev1

Record of Issue

Company Client Contact Version Date Issued Method of Delivery

CST Minerals Lady Annie Pty Ltd

Qi Deng

Jay Klopper

Michael Feldman

Joseph Fellows

Rev0 4/12/12 email

CST Minerals Lady Annie Pty Ltd

Joseph Fellows Rev1 20/12/12 email



Study Limitations

This Document has been provided by Golder Associates Pty Ltd (“Golder”) subject to the following limitations:

This Document has been prepared for the particular purpose outlined in Golder’s proposal and no responsibility is accepted for the use of this Document, in whole or in part, in other contexts or for any other purpose.

The scope and the period of Golder’s Services are as described in Golder’s proposal, and are subject to restrictions and limitations. Golder did not perform a complete assessment of all possible conditions or circumstances that may exist at the site referenced in the Document. If a service is not expressly indicated, do not assume it has been provided. If a matter is not addressed, do not assume that any determination has been made by Golder in regards to it.

Conditions may exist which were undetectable given the limited nature of the enquiry Golder was retained to undertake with respect to the site. Variations in conditions may occur between investigatory locations, and there may be special conditions pertaining to the site which have not been revealed by the investigation and which have not therefore been taken into account in the Document. Accordingly, additional studies and actions may be required.

In addition, it is recognised that the passage of time affects the information and assessment provided in this Document. Golder’s opinions are based upon information that existed at the time of the production of the Document. It is understood that the Services provided allowed Golder to form no more than an opinion of the actual conditions of the site at the time the site was visited and cannot be used to assess the effect of any subsequent changes in the quality of the site, or its surroundings, or any laws or regulations.

Any assessments made in this Document are based on the conditions indicated from published sources and the investigation described. No warranty is included; either expressly or implied, that the actual conditions will conform exactly to the assessments contained in this Document.

Where data supplied by the client or other external sources, including previous site investigation data, have been used, it has been assumed that the information is correct unless otherwise stated. No responsibility is accepted by Golder for incomplete or inaccurate data supplied by others.

Golder may have retained subconsultants affiliated with Golder to provide Services for the benefit of Golder. To the maximum extent allowed by law, the Client acknowledges and agrees it will not have any direct legal recourse to, and waives any claim, demand, or cause of action against, Golder’s affiliated companies, and their employees, officers and directors.

This Document is provided for sole use by the Client and is confidential to it and its professional advisers. No responsibility whatsoever for the contents of this Document will be accepted to any person other than the Client. Any use which a third party makes of this Document, or any reliance on or decisions to be made based on it, is the responsibility of such third parties. Golder accepts no responsibility for damages, if any, suffered by any third party as a result of decisions made or actions based on this Document.


4 December 2012 Report No. 117631031-22 Rev1 1

Table of Contents

1.0 SUMMARY ................................................................................................................................................................. 4

RESOURCE ASSUMPTIONS AND METHODOLOGY....................................................................................................... 4

MINERAL RESOURCE STATEMENT ................................................................................................................................ 5

MINE PLANNING ASSUMPTIONS .................................................................................................................................... 8

IN-PIT MINERAL RESORUCE STATEMENT .................................................................................................................... 9

2.0 INTRODUCTION ...................................................................................................................................................... 10

2.1 Scope of Work ............................................................................................................................................ 10

2.2 Effective Dates ............................................................................................................................................ 10

2.3 Site Visits .................................................................................................................................................... 10

2.4 Data Audits ................................................................................................................................................. 11

2.5 Software ..................................................................................................................................................... 11

2.6 Modelling Framework ................................................................................................................................. 11

3.0 DRILL HOLE DATA ................................................................................................................................................. 13

3.1 Drilling ......................................................................................................................................................... 13

4.0 ANTHILL RESOURCE ESTIMATE ......................................................................................................................... 16

4.1 Geological Interpretation ............................................................................................................................. 16

4.2 Data Preparation ......................................................................................................................................... 19

4.2.1 Default grades ....................................................................................................................................... 19

4.2.2 Resource Domains................................................................................................................................ 19

4.2.2.1 Mineralisation domains ...................................................................................................................... 19

4.2.2.2 Oxidation Domains ............................................................................................................................ 19

4.2.2.3 Domain Boundary Analysis ................................................................................................................ 20

4.2.1 Compositing .......................................................................................................................................... 21

4.2.2 Top Cuts ............................................................................................................................................... 25

4.3 Variograms ................................................................................................................................................. 25

4.4 Block Modelling ........................................................................................................................................... 26

4.5 Grade Estimation ........................................................................................................................................ 27

4.6 Model Validation ......................................................................................................................................... 28

4.7 Classification............................................................................................................................................... 29

4.8 Previous Mineral Resource Estimate .......................................................................................................... 29



4.9 Mineral Resource Statement ...................................................................................................................... 30

5.0 MINE PLANNING .................................................................................................................................................... 34

5.1 Block Model ................................................................................................................................................ 34

5.2 Whittle Optimisation .................................................................................................................................... 34

5.2.1 Pit Optimisation Block Model ................................................................................................................ 34

5.3 Economic Parameters ................................................................................................................................ 35

5.3.1 Mining Costs and Parameters ............................................................................................................... 36

5.3.2 Processing Costs and Parameters ........................................................................................................ 36

5.4 Pit Slope Angles ......................................................................................................................................... 38

5.5 Pit Optimisation Results .............................................................................................................................. 38

6.0 PIT DESIGN ............................................................................................................................................................. 41

6.1 Mine Design Parameters ............................................................................................................................ 41

6.2 Mining Methodology .................................................................................................................................... 41

6.3 Processing Methodology ............................................................................................................................ 41

6.4 Mine Design ................................................................................................................................................ 41

6.5 Mineral Inventory ........................................................................................................................................ 43

7.0 IN-PIT MINERAL RESORUCES .............................................................................................................................. 44

TABLES

Table 1-1: Anthill Mineral Resource .................................................................................................................................... 5

Table 1-3: Anthill In-pit Mineral Resources with Dilution and Mining Loss .......................................................................... 9

Table 4-1: Anthill Proportion of Assayed and Unassayed samples within Mineralised Envelope ...................................... 19

Table 4-2: Anthill Pearson Correlation Coefficients for Resource Domain Samples ......................................................... 24

Table 4-3: Anthill Length Weighted Sample Statistics for the Copper Mineralisation Domain ........................................... 25

Table 4-4: Anthill Top Cuts by Domains ............................................................................................................................ 25

Table 4-5: Anthill Variogram Models ................................................................................................................................. 26

Table 4-6: Anthill Block Model Framework ........................................................................................................................ 27

Table 4-7: Anthill Model Fields .......................................................................................................................................... 27

Table 4-8: Anthill Default Grades by Domain .................................................................................................................... 28

Table 4-9: Anthill Global Mean and Variance Comparison for mineralised domain ........................................................... 29

Table 5-4: Economic Parameters ...................................................................................................................................... 35

Table 5-5: Mining Costs .................................................................................................................................................... 36

Table 5-6: Mining Recovery and Dilution........................................................................................................................... 36

Table 5-7: Processing Costs ............................................................................................................................................. 37

Table 5-8: Residual Copper .............................................................................................................................................. 37



Table 5-9: Production Constraints ..................................................................................................................................... 38

Table 6-1: Pit Design Parameters ..................................................................................................................................... 41

Table 6-2: Additional Variables ......................................................................................................................................... 42

Table 6-3: Anthill In-Pit Mineral Inventory without Dilution or Mining Loss ........................................................................ 43

Table 7-1: Anthill iIn-pPit Mineral Resources with Dilution and Mining Loss ..................................................................... 44

FIGURES

Figure 1: Anthill Location Plan of Drilling and Mineralisation Interpretation ....................................................................... 14

Figure 2: Anthill Summary of Resource Drilling by Drilling Method ................................................................................... 14

Figure 3: Anthill Summary of Resource Drilling Meters by Drilling Method and Year Drilled ............................................. 15

Figure 4: Anthill Number of Drill Holes by Survey Method................................................................................................. 15

Figure 5: Anthill Oblique View (looking north northeast) of Drill Holes and Mineralisation Wireframe Interpretation ......... 16

Figure 6: Anthill Oblique View (looking north northeast) of Drill Holes and Top of Fresh Surface Wireframe ................... 17

Figure 7: Anthill Global Grade Distribution for Copper, Calcium, Magnesium and Density ............................................... 18

Figure 8: Anthill Grade Trend Plots across the Oxide-Transitional and Transitional-Sulphide Contacts ........................... 20

Figure 9: Anthill Grade Trend Plots across the Copper Domain Boundary ....................................................................... 21

Figure 10: Anthill Histogram of Drill Hole Sample Length and Box Plot of Length by Year Drilled .................................... 22

Figure 11: Anthill Log-Probability Plots of Copper, Calcium, Magnesium and Density for 3 m Drill Hole Composites by Copper Domain (CUDOM)........................................................................................................................... 22

Figure 12: Anthill Log-Probability Plots of Copper, Calcium and Magnesium and Density for 3 m Drill Hole Composites by Oxide Domain (OXIDE) ........................................................................................................... 23

Figure 13: Anthill Box Plots of Copper, Calcium and Magnesium and density for 3 m Drill Hole Composites by oxide domain (OXIDE) ..................................................................................................................................... 24

Figure 14: Anthill Variograms for horizontal mineralisation ............................................................................................... 26

Figure 15: Anthill Variogram models for vertical mineralisation (unfolded using wireframes) ............................................ 26

Figure 16 Anthill Swath Plots for Copper in the x and y Directions ................................................................................... 29

Figure 17: Mining Costs by Depth ..................................................................................................................................... 36

Figure 18: Anthill Marginal Copper Cut-off Grade vs. Calcium .......................................................................................... 38

Figure 19: Whittle Optimal Pit Shells Anthill ...................................................................................................................... 40

Figure 20: Anthill East Whittle Pit Section 7 758 900N ...................................................................................................... 40

Figure 21: Anthill West Whittle Pit Section 7 758 900N ..................................................................................................... 40

Figure 22: Anthill Pit Plan View ......................................................................................................................................... 42

Figure 23: Anthill East Section 7 758 900N ....................................................................................................................... 42

Figure 24: Anthill West Section 7 758 900N ...................................................................................................................... 43



1.0 SUMMARY The Lady Annie project is situated in northwest Queensland, Australia and is approximately 120 km to the north of the town of Mt Isa. copper deposits within the area are hosted by a sedimentary sequence of siltstone, sandstone and dolomitic sandstone and minor quartzite. Mineralisation is structurally controlled and occurs predominately as malachite with minor azurite, chrysocolla, cuprite and rare native copper within the oxidised sediments. The Anthill copper deposit is situated approximately 40 km south of the Mt Kelly plant.

The Anthill mineral resource estimates are based on drilling and interpretations of the geology and mineralisation by on site CST Minerals Lady Annie Pty Ltd (CST) geologists.

Golder Associates Pty Ltd (Golder) where engaged by CST to review the data and geology interpretations and complete the resource estimate using CAE Datamine Studio software.

Resource Assumptions and Methodology

This mineral resource estimates are based on a number of factors and assumptions:

� Only reverse circulation and diamond drill hole data were used for estimating the mineral resource.

� AMG grid coordinates has been used for the evaluation.

� Datamine mining software was used for building the block model and grade estimation and reporting.

� Copper mineralisation envelopes were interpreted by CST in two-dimensional cross-sections and then wireframed to produce three dimensional solid models. A nominal 0.2% Cu lower threshold was used to define the copper mineralisation envelopes. Additional surfaces defining the orientation of the mineralisation was also modelled by CST for use in building the local anisotropy model for grade estimation.

� Detailed topographic pre-mining surface covering the deposit was supplied by CST.

� Oxidation domains were interpreted by CST from geological logging, calcium-magnesium grades and copper sequential assays. They include oxide, transitional and fresh material which broadly defines the degree of oxidation of the rock. These domains broadly determine the copper minerals likely to occur within the rock and consequently the copper recoveries by acid leaching.

� Statistical and geostatistical analysis was conducted on drill hole sample assays composited to 3 m down-hole interval lengths on a copper domain basis. Prior to compositing the samples within the copper domains that had no copper assay were assigned a default grade of 0.01% Cu.

� Top cuts were applied to the drill hole sample data prior to grade estimation to limit the effect of outlier samples.

� A parent block dimension of 10 m by 10 m by 10 m was used. The parent blocks were allowed to split into 4 by 4 by 4 sub-blocks with seam filling in the vertical direction to a resolution of 2.5 m near copper domain boundaries to improve estimation of the volume and to a resolution of 1 m near topography. This results in a minimum block size of 2.5 m by 2.5 m by 1 m.

� Hard boundaries were used for estimating copper grades within the copper domains with soft boundaries across oxide domain contacts. Calcium and magnesium were estimated using hard boundaries across the oxide domain contacts and soft boundaries across the copper domains.

� Grade estimation was conducted using ordinary kriging (OK) for copper, calcium and magnesium. Copper grades were estimated by copper mineralisation domains while calcium and magnesium grades were estimated using oxidation domains. Default grades were assigned to blocks that were not estimated. Copper was assigned a default of 0.01% Cu while calcium and magnesium were assigned defaults by oxide domain using the mean grades of the drill hole samples.



� Density values were estimated by oxidation domain. Default density values based on the mean density by oxide domain were assigned to blocks that were not estimated.

� Dynamic anisotropy was used during grade estimation to accommodate the varying directions (dip and dip direction) of the mineralisation. This method uses local estimates of dip and dip direction that are used to orient the search ellipse and variogram models for grade estimation rather than using a global lookup table based on domain.

� Validation of the models included visual inspection in three dimensions comparing the model against the drill hole data, comparison of the mean grades of the estimated against the mean grade of the composite drill hole data, and generation of swath plots (comparison of average grade by section).

� Resource classification was assigned to the block model using the following parameters:

− Measured : at least 4 drill holes within a radius of 30 m (i.e. 20 m by 20 m drill spacing)

− Indicated : at least 4 drill holes within a radius of 60 m (i.e. 40 m by 40 m drill spacing)

− Inferred : less than 4 drill holes within a radius of 60 m (i.e. > 40 m by 40 m drill spacing)

Mineral Resource Statement

The total Anthill (Anthill West, Anthill Link, Anthill East) Mineral Resource estimate within the copper mineralisation envelopes by resource classification is presented in Table 1-1, Table 1-2 and Table 1-3.

The Mineral Resource estimate for Anthill East replaces the previous estimate for Anthill East with only minimal change. The Mineral Resources for Anthill West and Anthill Link are maiden estimates. Mineralisation is continuous across Anthill but have been separated into two principal zones (Anthill East and Anthill West) separated by a lower grade zone (Anthill Link).

Table 1-1: Anthill Mineral Resource as at October 2012

Cut-off

Cu %

Resource

Category

Tonnage

(Mt)

Cu

(%)

Ca

(%)

Mg

(%)

0.2

Measured 3.7 0.70 0.9 0.6

Indicated 12.8 0.56 1.7 1.0

Inferred 4.2 0.38 3.6 2.2

Total 20.7 0.55 1.9 1.2

0.3

Measured 3.0 0.79 0.8 0.5

Indicated 8.7 0.71 1.9 1.2

Inferred 2.1 0.52 6.0 3.6

Total 13.8 0.70 2.3 1.4



Table 1-2: Mineral Resource Estimate for Anthill at a 0.2% Cu as at October 2012

Area Category OXIDE *Tonnes (Mt) Cu (%) Ca (%) Mg (%)

East

Measured

Oxide 1.7 0.81 0.4 0.3

Transitional 0.1 1.05 5.5 3.2

Sulphide - - - -

Total 1.9 0.82 0.8 0.5

Indicated

Oxide 5.7 0.63 0.3 0.3


Sulphide 0.2 0.45 4.6 2.7

Total 7.0 0.65 1.2 0.8

Inferred

Oxide 0.1 0.31 0.5 0.3


Sulphide 1.2 0.45 6.4 4.1

Total 1.6 0.43 5.8 3.7

Total

10.5 0.65 1.8 1.2

Link

Indicated

Oxide 1.0 0.28 0.1 0.1


Sulphide 0.02 0.57 10.0 6.0

Total 1.1 0.29 1.0 0.6

Inferred

Oxide 1.8 0.24 0.2 0.2


Sulphide 0.04 0.44 8.6 4.7

Total 1.9 0.25 0.5 0.4

Total

3.0 0.26 0.7 0.5

West

Measured

Oxide 1.5 0.56 0.1 0.1


Sulphide 0.02 0.60 5.8 3.5

Total 1.8 0.57 1.0 0.6

Indicated

Oxide 2.9 0.45 0.3 0.3


Sulphide 0.7 0.61 5.7 3.2

Total 4.7 0.51 2.6 1.5

Inferred

Oxide 0.04 0.27 0.2 1.1

Transitional 0.01 0.37 10.2 6.0

Sulphide 0.7 0.61 6.9 3.9

Total 0.8 0.58 6.6 3.8

Total

7.3 0.53 2.6 1.5

TOTAL

Measured

Oxide 3.3 0.69 0.3 0.2


Sulphide 0.02 0.60 5.9 3.5

Total 3.7 0.70 0.9 0.6

Indicated

Oxide 9.6 0.54 0.3 0.3


Sulphide 0.9 0.58 5.6 3.2

Total 12.8 0.56 1.7 1.0

Inferred

Oxide 1.9 0.24 0.2 0.2


Sulphide 1.9 0.51 6.6 4.0

Total 4.2 0.38 3.6 2.2

TOTAL

20.7 0.55 1.9 1.2

*Totals may not add up due to rounding



Table 1-3: Mineral Resource Estimate for Anthill at a 0.3% Cu as at October 2012


East

Measured

Oxide 1.5 0.91 0.4 0.3


Sulphide - - - -

Total 1.6 0.92 0.8 0.5

Indicated

Oxide 4.1 0.79 0.4 0.3


Sulphide 0.1 0.47 4.4 2.6

Total 5.2 0.79 1.3 0.8

Inferred

Oxide 0.04 0.44 0.4 0.3


Sulphide 1.0 0.49 6.2 4.0

Total 1.2 0.49 5.9 3.7

Total

8.0 0.77 1.9 1.2

Link

Indicated

Oxide 0.2 0.38 0.1 0.1


Sulphide 0.02 0.57 10.0 6.0

Total 0.3 0.40 2.1 1.3

Inferred

Oxide 0.1 0.35 0.3 0.2


Sulphide 0.04 0.44 8.6 4.7

Total 0.2 0.37 3.3 1.8

Total

0.5 0.39 2.5 1.5

West

Measured

Oxide 1.3 0.62 0.1 0.1


Sulphide 0.02 0.69 5.8 3.4

Total 1.5 0.64 0.9 0.5

Indicated

Oxide 1.7 0.58 0.3 0.3


Sulphide 0.7 0.65 5.6 3.2

Total 3.2 0.62 3.0 1.7

Inferred

Oxide 0.01 0.37 0.1 1.5


Sulphide 0.7 0.62 6.7 3.8

Total 0.7 0.61 6.7 3.8

Total

5.4 0.62 2.9 1.7

TOTAL

Measured

Oxide 2.7 0.77 0.3 0.2


Sulphide 0.02 0.70 5.9 3.4

Total 3.0 0.79 0.8 0.5

Indicated

Oxide 6.1 0.71 0.3 0.3


Sulphide 0.8 0.61 5.5 3.1

Total 8.7 0.71 1.9 1.2

Inferred

Oxide 0.1 0.37 0.3 0.3


Sulphide 1.7 0.54 6.5 3.9

Total 2.1 0.52 6.0 3.6

TOTAL

13.8 0.70 2.3 1.4




No mining has been undertaken over the Anthill deposits.

This Mineral Resource estimate is based upon and accurately reflects data compiled or supervised by Mr Matthew Nimmo, Principal Geologist, who is a Member of the Australasian Institute of Mining and Metallurgy and a full time employee of Golder Associates Pty Ltd. Mr Nimmo has sufficient experience that is relevant to the style of mineralisation and the type of deposit under consideration and to the activity which he has undertaken to qualify as a Competent Person as defined in the 2004 edition of the ‘Australasian Code for the Reporting of Exploration Results, Mineral Resources and Ore Reserves’.

Mine Planning Assumptions

The following items are to be taken into account when considering this assessment:

� No mining lease is currently held for the Anthill deposit so all material remains in-pit Mineral Resource inventory.

� A cut-off grade which varies with material type (i.e. oxide or transition), calcium estimate and haulage distance.

� Heap leaching and electro winning parameters and operating costs provided by CST for the processing rate of 25 000 t of copper per annum, based on costs and recoveries predicted from the existing operation at Lady Annie.

� Sulphide resource is not amenable to acid heap leaching and is excluded from the assessment of in-pit Mineral Resources.

� Geotechnical parameters are based on previous work by Coffey Pty Ltd.

� Survey data of surfaces and previous workings provided by CST.

� Golder completed Whittle pit optimisations using a USD3.00/lb copper price, with a pit shell selected on the basis that the spot copper price at the time of the optimisation was in excess of USD3.24/lb.

� The copper price used for mine planning is USD3.00/lb.

� Evaluations are based on a long term exchange rate of 0.80:1 AUD:USD.

� The economics and cut-off grades of the project are dependent on calcium grade and oxidation type. Higher calcium levels increase acid consumption and consequently increase operating costs. The cut-off grades used to estimate in-pit Mineral Resources are based on both copper and calcium grades estimated in the Mineral Resource block model. Furthermore, copper recovery is also affected by high calcium of the transition ore which further increases the cut-off grade producing a step change in the cut-off grade calculation.

� Marginal cut-off grades used in the in-pit Mineral Resource for Anthill are estimated from the following equation:

��= 0.42% + 0.06% ∗ ��, �� ≤ 2%;0.49% + 0.06% ∗ ��, �� > 2%.

� In-pit mineral inventory are based only on the Measured and Indicated Mineral Resources contained within the final pit designs, based on variable copper cut-off grades described above.

� The Mineral Resource modifying factors for conversion to in-pit mineral inventory includes dilution of 5% assuming a copper grade of 0.2% Cu and mining recovery of 97.5%.



In-Pit Mineral Resource Statement

The Mineral Resources considered feasible for economic extraction are based on the pit design and include modifying factors with mining dilution of 5% at 0.2% Cu and mining losses of 2.5%. These are summarised in Table 7-1.

The current pit design includes an additional 27.4 Mt of waste giving an overall strip ratio of 7.9 t/t.

Table 1-4: Anthill In-Pit Mineral Resources with Dilution and Mining Loss

Deposit

Name

Resource

Category

Material

Type

Tonnage (Mt)

Cu

(%)

Contained

Cu (kt)

Ca

(%)

West

Measured

Transition 0.004 0.94 0.04 3.91

Oxide 0.49 0.83 4.08 0.11

Total 0.50 0.83 4.12 0.14

Indicated

Transition 0.02 1.20 0.24 4.49

Oxide 0.48 0.89 4.24 0.15

Total 0.50 0.90 4.49 0.32

East

Measured

Transition 0.035 1.95 0.69 5.22

Oxide 0.83 1.09 9.00 0.30

Total 0.86 1.12 9.69 0.50

Indicated

Transition 0.09 2.11 1.84 4.74

Oxide 1.59 1.12 17.73 0.19

Total 1.68 1.17 19.57 0.42

Combined

Measured

Transition 0.04 1.85 0.73 5.08

Oxide 1.32 0.99 13.08 0.23

Total 1.36 1.02 13.81 0.37

Indicated

Transition 0.11 1.94 2.09 4.70

Oxide 2.07 1.06 21.97 0.18

Total 2.17 1.11 24.05 0.40



2.0 INTRODUCTION CST Minerals Lady Annie Pty Ltd (CST) requested Golder Associates Pty Ltd (Golder) to estimate the Mineral Resource for the Anthill copper deposit.

Lady Annie project is located approximately 120 km north of Mount Isa in northwest Queensland. It is accessed via the sealed Mt Barkly highway and then the unsealed McNamarras Road. Mining at Lady Annie is at two separate areas, including the Lady Annie area (Lady Annie and Lady Brenda deposits) and the Mt Kelly area (Mt Clarke, Flying Horse, Mt Kelly and Swagman deposits). The Anthill deposit is located approximately 40km south of the Mt Kelly plant.

CopperCo began mining operations at the Lady Annie copper mine in 2007 targeting copper oxide ore for processing by heap leaching followed by solvent extraction and electrowinning. In 2009 Cape Lambert Lady Annie Exploration Pty Ltd (CLLAE) purchased the operations with CST entering into a Share Sale agreement to acquire 100% of CLLAE. CST recommenced mining at Lady Annie in September 2010.

2.1 Scope of Work The scope of work includes estimating Mineral Resource and Mineral Reserves for the Anthill copper deposit.

CST provided the following:

� Drill hole data (assays, lithology, collar, survey, bulk density) as ASCII comma delimited files

� Geological interpretations used in the estimation which included: copper mineralisation (at 0.2% Cu nominal cut-off) and oxidation wireframes

� Topography wireframes

� Report on QAQC

� Drill hole exclusion lists

Golder performed the following tasks as part of the Mineral Resource estimation scope of work:

� Data validation

� Review geological interpretations

� Statistical analysis of drill hole assays

� Variography

� Block modelling

� Grade estimation using ordinary kriging (OK) for copper, calcium and magnesium as well as estimation using inverse distance (IDW) and nearest neighbour (NN)

� Model validation

� Resource reporting

2.2 Effective Dates The effective date for the resource estimate, based on the delivery date of the drilling data, is 3/09/2012.

2.3 Site Visits Matthew Nimmo, B.Sc. (Hons), MAIG, employed by Golder Associates Pty Ltd as Principal Geologist visited the site on two separate occasions. The first visit occurred during 20 November 2011 to 24 November 2011.



The purpose of this visit was: inspection of drilling and site, review current resource model and review current geological interpretation. The second site visit occurred during 24 January 2012 to 28 January 2012. The purpose of this visit was to obtain latest drill hole data, review status of geological interpretation, setup modelling framework and observe grade control processes.

Frank McManus, B.Eng, B.Sc., MBA, who was employed by Golder Associates Pty Ltd at the time as Principal Mining Engineer, visited the site on two separate occasions. The first visit occurred during 21 December 2011 to 22 December 2011 for the purpose of reviewing mine planning and ore grading operations. The second visit occurred during 30 January 2012 to 2 February 2012 and was for obtaining information and data to facilitate undertaking Whittle optimisation and estimating Ore Reserves.

2.4 Data Audits Golder has not undertaken detailed data audits of the drill hole data used in Mineral Resource estimation for the Anthill copper deposit.

A brief review of the QAQC information provided by CST shows no major concerns with the quality of the drill hole sample assaying being conducted by CST.

The drill hole data was first imported into a temporary Microsoft Access database where the following data integrity checks and data adjustments were performed:

� Check for duplicate records

� Check for overlaps

� Replace null values for assays with -9 to mark missing assays

� Replace other negative assay values with half detection limit (typically 0.005)

� Insert records to replace gaps within the assay table and set values to -9

� Check for excessive deviation in survey

� Check for cross-table consistency

� Flag drill holes for exclusion by setting the field KEEP=0

After data checks were performed in Access, the data was then exported out to comma delimited text files. Only the required fields for resource modelling were exported.

2.5 Software Studio 3 version 3.20.6140.0.Released from CAE Datamine Corporate Limited was used for drill hole sample domain encoding (flagging), building the block model, grade estimation and resource tabulation. Proprietary Golder software was used for variography and the R version 2.14.0 (2010-10-31) from the R Foundation for Statistical Computing was used for statistical data analysis and plotting.

2.6 Modelling Framework The modelling framework consists of a series of Datamine macros to perform the following tasks:

� Set global modelling parameters

� Import drill hole data in comma delimited format and desurvey the drill holes

� Flag the drill hole data with the copper mineralisation and oxide domains and composite to regular intervals

� Construct the block model



� Estimate dip and dip direction into the block model

� Estimate copper, calcium and magnesium grades

� Deplete the block model by removing cells above the latest pit wireframe

� Assign resource classification to the block model

� Report grade and tonnage

The modelling framework was tested and validated extensively on the Lady Annie copper deposit. Modelling and estimation parameters were also optimised on the Lady Annie copper deposit.

The grid coordinates used for all projects is AMG AGD84.



3.0 DRILL HOLE DATA CST supplied the drill hole data for the Anthill copper deposit via email on the 3 September 2012. The data was supplied as Microsoft Excel format files (exported from the CST geological database) which were then exported to comma delimited text files.

The data included tables for sample assays (104 773 records), drill hole collar (7846 records), drill hole survey (11 319 records), lithology (65 101 records), alteration (47 470 records), core recovery (6973 records), geotechnical logging (6981 records), magnetic susceptibility (13 659 records), logged minerals (7966 records), structural logging (1429 records), veins (5968 records), QAQC sampling (8606 duplicates, 20232 standards), and bulk density (1581 records). This data covers a much broader area than the Anthill deposit.

The interpretation wireframes generated by CST onsite were supplied as AutoCAD dxf file format and included: base of oxidation, top of sulphide, copper mineralisation surfaces, and copper mineralisation solid wireframes.

3.1 Drilling The Anthill drill hole data was restricted to immediate surrounding area of the Anthill deposit covers the area (in MGA coordinates) 302 100 mE 7 758 400 mN to 304 600 mE 7 759 800 mN and comprises 754 drill holes with a mix of drilling types. Reverse circulation (RC) drilling (481 drill holes) accounts for 64% of the drilling. Drill spacing varies from less than 20 m to over 100 m and averages approximately 20 m by 40 m.

A summary of the drill holes for Anthill is presented in Figure 2 and Figure 3. The drilling was completed between 1972 and 2012. Majority of the drilling meters was completed in 2010 (12%), 2011 (19%) and 2012 (46%) using predominantly reverse circulation and diamond drilling methods. The methods used are:

� DD 14% of drill holes – Diamond core drilling method

� DD_MET 1% of drill holes – Diamond core drilling method for metallurgical test work

� PD <1% of drill holes – Percussion drilling method

� RAB 2% of drill holes – Rotary Air Blast (RAB) drilling method

� RC 70% of drill holes – Reverse Circulation (RC) drilling method

� RCDD 12% of drill holes – RC pre-collar with DD tail

� TCH 1% of drill holes – Trench

� WB <1% of drill holes – Water Bore

Figure 1 shows the location of the drill holes in MGA coordinates.

Only the reverse circulation and diamond drill holes were used for estimating grades. Additionally, drill holes that have no assay data in the database were also flagged for exclusion. These include:

� 5 DD_MET diamond drill holes (BURMET006, BURMET010A, BURMET011 to BURMET013)

Down hole surveys at Anthill have been collected using a range of methods. Majority (58%) of the drill holes were surveyed using a REFLEX camera on approximately 30 m intervals. For 15% of the drill holes the survey method is not recorded in the database.



Anthill East=Red, Anthill Link=Blue, Anthill West=Orange

Figure 1: Anthill Location Plan of Drilling and Mineralisation Interpretation

Figure 2: Anthill Summary of Resource Drilling by Drilling Method



Figure 3: Anthill Summary of Resource Drilling Meters by Drilling Method and Year Drilled

Figure 4: Anthill Number of Drill Holes by Survey Method

The predominant down hole survey method for each drill hole is summarised in Figure 4. The methods used are:

� COLLAR 3% of drill holes. Collar sight records are assigned to collar surveys at surface from geologist measurements on the drill rig.

� COMPASS (compass survey of rig setup) <8% of drill holes.

� EASTMAN (Eastman single shot survey) <1% of drill holes.

� ESTIMATE less than <1% of drill holes.

� NR 15% of drill holes.

� REFLEX (Reflex multi or single shot tool) 58% of drill holes.

� SS (Reflex single shot tool) 12% of drill holes.

� TAP 3% of drill holes.



4.0 ANTHILL RESOURCE ESTIMATE

4.1 Geological Interpretation The interpretation of the copper mineralisation and oxidation was completed by CST geologists at the Lady Annie mine site. Copper mineralisation was interpreted using a 0.2% Cu lower cut-off grade while oxidation relied on the geological logging of weathering and the available copper sequential assay data.

A set of closed perimeters were constructed on oblique section lines with different orientations for Anthill East and Anthill Link, and Anthill West. Three-dimensional solids wireframes were then constructed from the closed perimeters by CST. The mineralisation was interpreted as a single domain. Additional wireframe surfaces representing the copper mineralisation were developed for the purpose of estimating dip and dip direction into the block model for grade estimation by dynamic anisotropy.

The solid wireframe of the 0.2% Cu mineralisation is presented in Figure 5. The top of fresh rock surface wireframe is shown in Figure 6.

Wireframe Interpretations at 0.2% Cu cut-off: Anthill East=Red, Anthill Link=Blue, Anthill West=Orange

Figure 5: Anthill Oblique View (looking north northeast) of Drill Holes and Mineralisation Wireframe Interpretation



Figure 6: Anthill Oblique View (looking north northeast) of Drill Holes and Top of Fresh Surface Wireframe

Drill hole sample grade distributions for all data are presented as histogram and log probability plots in Figure 7. The log probability plot for copper confirms that the distribution is approximately log normal and continuous from 0.2% Cu to 20% Cu. For calcium and magnesium there is clearly a bimodal distribution evident in the histogram and log probability plots attributed to oxidation of the host rock.



Figure 7: Anthill Global Grade Distribution for Copper, Calcium, Magnesium and Density



4.2 Data Preparation Database preparation steps are described in Section 2.0. In summary they include:

� Data validation and corrections

� Exclusion of unreliable drill holes and drill holes with no assays

� Assignment of default grades to all missing assays of 0.01 for Cu

� Flagging of resource, geology and oxidation domains

� Compositing drill holes

� Application of top cuts

4.2.1 Default grades

Table 4-1 lists the number of missing samples by domain. Selective sampling is a significant problem for calcium and magnesium with 54% of the samples within the copper mineralisation not assayed. To avoid any bias due to the missing samples a default grade of 0.01 for Cu was assigned to all unassayed intervals in both waste and mineralisation domains. No default grades were assigned to calcium and magnesium due to the significant number of missing samples. The default grades were applied prior to compositing.

Table 4-1: Anthill Proportion of Assayed and Unassayed samples within Mineralised Envelope

Domain Element Samples Missing % Missing

CUDOM=1

(resource domains)

Total 11 725

Cu 11 575 150 1%

Ca 8 754 2 971 25%

Mg 8 845 2 880 25%

CUDOM=0

(waste)

Total 67 285

Cu 64 503 2 782 4%

Ca 51 965 15 320 23%

Mg 52 412 14 873 22%

4.2.2 Resource Domains

Geological domains are used to distinguish and divide areas of different mineralisation style or statistical character. Domains attempt to create zones of statistical stationarity (i.e. consistency) where structure and controls are constant. When achieved, the domains are then suitable for statistical and geostatistical analysis and for grade estimation.

4.2.2.1 Mineralisation domains

Interpretation of the copper mineralisation by CST has only defined one copper mineralisation domain. This domain represents material that exceeds the 0.2% Cu nominal cut-off grade. A domain field (CUDOM) has been added to the drill hole data and block model with the following domains:

� CUDOM = 0 Waste material with copper below 0.2% Cu

� CUDOM = 1 Ore material with copper greater than or equal to 0.2% Cu

4.2.2.2 Oxidation Domains

The boundaries define three domains flagged in the block model by applying the surface wireframes to the mineralised domain blocks. The domains include:



� OXIDE = 2 Oxidised material with copper predominantly as oxide minerals and good leach recovery

� OXIDE = 1 Transitional material with copper as oxide, native copper and some sulphides

� OXIDE = 0 Sulphide zone with copper dominated by sulphide species and poor leach recovery

4.2.2.3 Domain Boundary Analysis

Due to the very high difference in grade for calcium and magnesium between the oxide and transitional zones a contact analysis was undertaken to quantify the grade trends across the oxide boundaries and across the copper domain boundary. Grade trend plots for copper, calcium and magnesium across the oxide domain contacts and copper domain boundary are presented in Figure 8 and Figure 9.

For the contact between the oxide and transitional zones, the grade trend for calcium and magnesium shows a more rapid transition across the contact then for copper over a range of 1 to 3 m from the contact. Copper shows a gradual decrease in grade across the boundary with no noticeable dramatic grade changes near the boundary. A hard boundary between oxide and transitional is appropriate for estimating calcium and magnesium while a soft boundary for copper is more appropriate. A visual check of copper grades near the oxide-transitional boundary showed no indication of high grade copper terminating at or near the boundary. Copper grades appear to smoothly transition across the contact.

For the transitional and sulphide contact there is no discernible change in grade trend across the contact for copper, calcium or magnesium. A soft boundary is considered appropriate for estimating copper, calcium and magnesium. However, a hard boundary is considered for grade estimation to ensure elevated calcium and magnesium values do not impact on the estimation of calcium and magnesium for the oxide zone.

The grade trend for copper across the copper domain boundary shows a slight step change in copper grade and no change in calcium and magnesium grades. A hard boundary is considered appropriate for estimating copper while a soft boundary is considered appropriate for calcium and magnesium.

Figure 8: Anthill Grade Trend Plots across the Oxide-Transitional and Transitional-Sulphide Contacts



Figure 9: Anthill Grade Trend Plots across the Copper Domain Boundary

Based on the contact analysis copper grades are estimated by copper domain using hard boundaries and calcium and magnesium grades are estimated by oxide domain using hard boundaries (soft boundaries for copper domain).

Due to sparseness of the density data no contact analysis was performed for density. It is assumed that density values across the oxidation boundaries show sharp changes and no change across the copper domain boundary.

4.2.1 Compositing

Drill hole sampling length (Figure 10) with majority of the samples being 1 m in length. A composite length of 3 m was determined to be the most appropriate given the block dimensions, estimation parameters, and grade control selectivity.

Log-probability plots of the 3 m drill hole composite samples for copper, calcium and magnesium by copper domain (CUDOM) are illustrated in Figure 11 and in Figure 12 for oxidation domains (OXIDE). Box plots summarising the distributions by oxidation domain are presented in Figure 13.

Copper exhibits an approximately log-normal distribution with an artificial grade break at 0.1% Cu for the copper domain samples due to internal dilution within the copper domain. There is a slight change in the log-probability plot for copper at approximately 0.5% Cu. The log-probability plot and box plot of copper by oxide domain reveals a slight increase in mean grade within the oxide zone. This increase in grade is not evident on the contact plots in Figure 8.



Figure 10: Anthill Histogram of Drill Hole Sample Length and Box Plot of Length by Year Drilled

Figure 11: Anthill Log-Probability Plots of Copper, Calcium, Magnesium and Density for 3 m Drill Hole Composites by Copper Domain (CUDOM)



Figure 12: Anthill Log-Probability Plots of Copper, Calcium and Magnesium and Density for 3 m Drill Hole Composites by Oxide Domain (OXIDE)

Calcium and magnesium exhibit evidence of population mixing within the copper and oxidation domains. There are two calcium and magnesium zones that can be defined by grade from the log-probability plots. These are:

1) Ca < ~9% and Mg < ~5%

2) Ca >= ~9% and Mg >= ~5%

From the log-probability plots there are limited samples within the range of 0.1-9% Ca and 0.1-5% Mg. This is attributed to the complete depletion of calcium and magnesium in the oxide zone and the sharp transition in the grade profile across the oxide-transitional boundary where grades jump from <1% Ca-Mg to >7 to 9% Ca-Mg. Calcium and magnesium grades appear to be a good proxy for defining the oxide-transitional boundary. The strong mixing of populations within the oxide domains for calcium and magnesium suggest that precise definition of the oxide boundaries is difficult. Observations of the oxidation profile in the Lady Annie pit verify the complexity of the oxide boundary. Therefore, the location of the oxidation boundaries are considered to be approximate and pose significant risk in ore loss due to high calcium and magnesium in areas close to the oxide-transitional boundary.



Figure 13: Anthill Box Plots of Copper, Calcium and Magnesium and density for 3 m Drill Hole Composites by oxide domain (OXIDE)

Table 4-2 lists the Pearson correlation coefficients for copper, calcium and magnesium for samples within the copper mineralisation envelope. Calcium and magnesium are highly correlated (0.95 Pearson correlation coefficient) while copper shows no correlation with calcium and magnesium. Copper also shows no correlation with Density for oxide and transitional zones and slight correlation with Density for sulphide zone.

Table 4-2: Anthill Pearson Correlation Coefficients for Resource Domain Samples

Element Cu Ca Mg Density

All Oxide Transition Sulphide

Cu 1 -0.0572 -0.0835 0.0707 0.0707 - -

Ca -0.0572 1 0.9521 0.2469 0.2469 - -

Mg -0.0835 0.9521 1 -0.2852 -2852 - -

For the 0.2% Cu mineralised domain, where selective sampling and the effect of default grades is minimal, it is possible to compare the length weighted average grades for the original samples and 3 m composites (Table 4-3). Note the reduction in copper mean grade relates to the introduction of 0.01% Cu default grades for the small number of missing assay.



Table 4-3: Anthill Length Weighted Sample Statistics for the Copper Mineralisation Domain

Data Set Variable Samples Missing Min Max Mean Var CV Median

Raw Samples

Cu 11575 150 4.00E-04 37.4 0.62 2.324 2.48 0.27

Ca 8754 2971 1.00E-06 16.8 1.41 8.967 2.12 0.07

Mg 8845 2880 0.01 9.99 0.86 2.929 2.00 0.11

Composites

(3 m)

Cu 4044 2 7.00E-04 27.23333 0.61 1.540 2.04 0.29

Ca 3022 1024 1.33E-06 15.05 1.40 8.161 2.04 0.08

Mg 3042 1004 0.01 9.378667 0.85 2.686 1.92 0.11

Cut Composites

Cu 4044 0 7.00E-04 10 0.59 1.1 1.77 0.29

Ca 3022 1022 1.33E-06 15 1.40 8.16 2.04 0.08

Mg 3042 1002 0.01 9 0.85 2.684 1.92 0.11

4.2.2 Top Cuts

The presence of outliers (or ‘extreme’ values), and the need to apply ‘top-cut’ values (or ‘capping’, where samples above a certain threshold are assigned the top-cut value) to sample populations was assessed using a number of techniques:

� Examination of grade distributions using probability plots, see Figure 11

� Statistical assessment of the grade distributions, see Table 4-3

� Examination of the spatial locations of identified outlier samples

Top cuts defined in Table 4-4 are roughly equivalent to the 99.5th percentile of the mineralised samples and

do not have a significant impact on the average grade. Sample statistics in Table 4-3 indicates that the average has been reduced by the top cuts by relatively small margins.

A top-cut of 0.2% Cu was used to prevent overestimation of grades within the waste domain since the grades above 0.2% Cu were not domained in the interpretation. It is assumed that the continuity of grades above 0.2% within the waste domain is limited.

Table 4-4: Anthill Top Cuts by Domains

CUDOM Cu % Ca % Mg %

0 0.2 15 9.0

1 10 15 9.0

4.3 Variograms The 3 m composite drill hole samples with top-cuts applied were used for variogram analysis. Traditional semi-variograms provided erratic results in some instances while inverted correlograms are more robust and display better structure. Correlograms were used for all variogram modelling. All semi-variograms were scaled to the domain variance. Correlogram models are presented in Figure 14 and Figure 15 and listed in Table 4-5. Variogram models were primarily based on the inverted experimental correlograms.

The drill hole data was subset into two geostatistical domains based on overall geometry. These domains represent the flat predominately oxide mineralisation and the steep predominately sulphide mineralisation. The steep mineralisation was unfolded to the centre line of the steep mineralisation wireframes to mimic the dynamic anisotropy method used for grade estimation. Variogram analysis was undertaken for each geostatistical domain separately.



Figure 14: Anthill Variograms for horizontal mineralisation

Figure 15: Anthill Variogram models for vertical mineralisation (unfolded using wireframes)

Additional variogram parameters used in most cases for the unfolded variogram calculation include:

� Two structure spherical models with common nugget and incremental sill levels

� Lag distance of 10 m

� Horizontal search angle of 20o

� Vertical search angle of 12o

� Horizontal distance of 15 m

� Vertical distance of 15 m across the unfolded plane

The variogram models for both geostatistical domains are similar in structure, range and sill and are similar to the variogram models used for the previous Anthill East Mineral Resource estimate (refer to the Golder Technical Report titled: Lady Annie Copper Mine, Mineral Resource Estimate 2012, dated 31 July 2012).

Table 4-5: Anthill Variogram Models

Var-iable

Nugget Spherical Structure 1 Spherical Structure 2

C0 C1

Range H1

C2

Range H2

Cross Strike

Down Dip

Strike Cross Strike

Down Dip

Strike

Cu 0.25 0.55 30 20 11 0.25 90 45 30

4.4 Block Modelling The block model contains 1 035 765 blocks representing copper mineralisation and waste material. The model was built in Datamine Studio 3 software using the model framework defined in Table 4-6 and with additional block attributes listed in Table 4-7.



Blocks were added to the model using the interpreted three-dimensional wireframe defining the copper mineralisation (CUDOM). The oxidation wireframe was used to add the OXIDE value to existing blocks while the original topography (pre mining) was used to add blocks for waste. A parent block size of 10 m by 10 m by 10 m was used. The parent blocks were allowed to split into 4 by 4 by 4 (2.5 m by 2.5 m by 2.5 m) sub-blocks to ensure reasonable resolution of the mineralisation boundaries.

Table 4-6: Anthill Block Model Framework

Parameter Easting Northing RL

Model origin 302 350 7 758 600 100

Model limit 304 220 7 759 540 380

Model extent (m) 1870 940 280

Parent block dimensions (m) 10 10 10

Number of parent blocks 187 94 28

Minimum sub-block size for domains (m) 2.5 2.5 2.5

Table 4-7: Anthill Model Fields

Variable Type Description

CUDOM numeric Cu domain code (1=mineralisation 0=waste)

OXIDE numeric Oxidation (0=fresh, 1=transitional, 2=oxide)

CU numeric Estimated Cu % block value

CA numeric Estimated Ca % block value

MG numeric Estimated Mg % block value

SG numeric Estimated block in-situ dry bulk density t/m3

RESCAT numeric Resource classification (0=unclassified, 2=Indicated, 3=Inferred)

4.5 Grade Estimation Ordinary kriging (OK) was used to estimate copper into the block model. The variogram models presented in Table 4-5 were used for estimation. Copper was estimated separately for each copper domain using a hard boundary between domains (soft boundaries between oxide domains). That is, only those samples falling within the domain being estimated are used to inform the block estimate.

Inverse Distance (ID) with a power of 2 was used to estimate calcium and magnesium. Both were estimated separately for each oxide domain using hard boundaries (soft boundary for copper domains). Grades were estimated on a parent block basis using block discretisation of 3 by 3 by 3.

Copper was also estimated using inverse distance and nearest neighbour (NN) while calcium, magnesium were also estimated using nearest neighbour. These estimates were used to validate the OK and ID estimates. Each domain was estimated separately.

To ensure that all blocks in the model had values for copper, calcium, magnesium and density, a three pass elliptical search strategy was used for selecting the neighbouring composite drill hole samples for estimation. Those blocks that were not estimated in the third pass were assigned default grades listed in Table 4-8. Copper defaults were assigned regardless of domain while calcium, magnesium and density were assigned by oxide domain.



Table 4-8: Anthill Default Grades by Domain

Domain CODE Cu % Ca % Mg % Bulk Density t/m3

CUDOM 0 0.01

1 0.01

OXIDE

2 0.01 0.24 0.24 1.95

1 0.01 3.64 2.06 2.60

0 0.01 3.48 2.31 2.80

Dimensions of the search ellipse radii were based on the ranges of the variogram models for copper. The search pass ellipse radii used are:

� PASS 1: 30 m by 30 m by 10 m

� PASS 2: 60 m by 60 m by 20 m (pass 1 expanded by a factor of 2)

� PASS 3: 120 m by 120 m by 40 m (pass 1 expanded by a factor of 4)

A minimum of 6 and maximum of 14 composites per estimate and a maximum of 3 composites per drill hole were selected. The required minimum number of samples per estimate was relaxed to 1 sample for the third search pass.

To improve local grade estimates the Datamine Studio dynamic anisotropy method for grade estimation was used. The dynamic anisotropy method requires local estimates of dip and dip direction in the block model that are used in orienting the search ellipse and variogram model. To estimate the dip and dip direction into the block model the mineralisation surfaces were used to construct a point set with each point positioned at the centre of gravity for each triangle and the dip and dip direction calculated from the triangle. This point set was then used in estimating dip and dip direction into the block model. The estimate values were then rounded to two decimal places.

4.6 Model Validation Validation of the block model included:

� Visual inspection of the grade estimates.

� Global mean and variance comparisons.

� Review of estimation quality parameters such as number of number of samples, slope of regression, kriging variance, and average distance of samples.

� SWATH plots (Figure 16). These include comparison of block model and declustered composite grade averages for North-South and vertical slices.



Figure 16 Anthill Swath Plots for Copper in the x and y Directions

A comparison of the global mean and variance between the declustered composites and the volume weighted block model estimates for each combined domain is provided for copper in Table 4-9. The mean grades compare favourably and indicate no significant bias.

Table 4-9: Anthill Global Mean and Variance Comparison for mineralised domain

Sample/ Model Cu Ca Mg

Mean Var Mean Var Mean Var

Samples - cut 0.58 1.066 1.52 8.941 0.92 2.939

Nearest Neighbour Samples 0.50 0.745 1.87 11.177 1.17 3.877

OK Estimates 0.51 0.231 1.92 9.380 1.19 3.201

4.7 Classification Mineral Resource classification was assigned on the basis of a target drill spacing of:

� Measured : at least 4 drill holes within a radius of 30 m (i.e. 20 m by 20 m drill spacing)

� Indicated : at least 4 drill holes within a radius of 60 m (i.e. 40 m by 40 m drill spacing)

� Inferred : less than 4 drill holes within a radius of 60 m (i.e. > 40 m by 40 m drill spacing)

4.8 Previous Mineral Resource Estimate The previous Mineral Resource estimate (Table 4-12 and Table 4-13) for Anthill only included the Anthill East deposit. For the current Anthill Mineral Resource estimate the Anthill East resource had only changed slightly (2% drop in tonnes and 5% increase in copper grade) due to changes in the variogram model.



Table 4-10: Anthill Mineral Resource estimate at a 0.2% Cu as at March 2012

Deposit Category OXIDE **Tonnes (Mt)

Cu (%)

*Ca (%)

*Mg (%)

Anthill East

Measured

Oxide 1.8 0.75 0.4 0.3


Total 1.9 0.78 0.8 0.5

Indicated

Oxide 5.9 0.60 0.4 0.3


Sulphide 0.2 0.46 5.2 2.8

Total 7.3 0.61 1.2 0.8

Inferred

Oxide 0.1 0.29 0.8 0.6


Sulphide 1.1 0.49 5.9 3.7

Total 1.6 0.47 5.1 3.2

Total

10.8 0.62 1.7 1.1

* Due to the sparseness of Ca & Mg assays the Ca & Mg estimates are indicative only

**Totals may not add up due to rounding

Table 4-11: Anthill Mineral Resource estimate at a 0.3% Cu as at March 2012

Deposit Category OXIDE **Tonnes (Mt)

Cu (%)

Ca (%) Mg (%)

Anthill East

Measured

Oxide 1.4 0.88 0.4 0.3


Total 1.5 0.91 0.8 0.5

Indicated

Oxide 4.1 0.75 0.4 0.3


Sulphide 0.1 0.52 4.6 2.5

Total 5.3 0.75 1.3 0.8

Inferred


Sulphide 1.0 0.52 5.7 3.6

Total 1.3 0.51 5.0 3.2

Total

8.1 0.74 1.8 1.2

* Due to the sparseness of Ca & Mg assays the Ca & Mg estimates are indicative only

**Totals may not add up due to rounding

4.9 Mineral Resource Statement The global Mineral Resource estimate for the Anthill (Anthill West, Anthill Link, Anthill East) copper deposit is presented in Table 4-12 and Table 4-13.

The Mineral Resource estimate for Anthill East replaces the previous estimate for Anthill East with only minimal change. The Mineral Resources for Anthill West and Anthill Link are maiden estimates. Mineralisation is continuous across Anthill but have been separated into two principal zones (Anthill East and Anthill West) separated by a lower grade zone (Anthill Link).

No mining has been undertaken over the Anthill deposits.



The Mineral Resource estimate within the interpreted copper mineralisation is:

At 0.2% Cu cut-off:

Measured 3.7 Mt at 0.70% Cu, 0.9% Ca, 0.6% Mg

Indicated 12.8 Mt at 0.56% Cu, 1.7% Ca, 1.0% Mg

Inferred 4.2 Mt at 0.38% Cu, 3.6% Ca, 2.2% Mg

TOTAL 20.7 Mt at 0.55% Cu, 1.9% Ca, 1.2% Mg

At 0.3% Cu cut-off:

Measured 3.0 Mt at 0.79% Cu, 0.8% Ca, 0.5% Mg

Indicated 8.7 Mt at 0.71% Cu, 1.9% Ca, 1.2% Mg

Inferred 2.1 Mt at 0.52% Cu, 6.0% Ca, 3.6% Mg


The total mineral resource estimate within the copper mineralisation envelopes by oxidation is:

At 0.2% Cu cut-off:

Oxide 14.8 Mt at 0.54% Cu, 0.3% Ca, 0.3% Mg

Transitional 3.0 Mt at 0.63% Cu, 5.8% Ca, 3.3% Mg

Sulphide 2.9 Mt at 0.53% Cu, 6.3% Ca, 3.8% Mg


At 0.3% Cu cut-off:

Oxide 8.9 Mt at 0.73% Cu, 0.3% Ca, 0.3% Mg

Transitional 2.4 Mt at 0.74% Cu, 5.6% Ca, 3.2% Mg

Sulphide 2.5 Mt at 0.57% Cu, 6.2% Ca, 3.7% Mg


This Mineral Resource estimate is based upon and accurately reflects data compiled or supervised by Mr Matthew Nimmo, Principal Geologist, who is a Member of the Australasian Institute of Mining and Metallurgy and a full time employee of Golder Associates Pty Ltd. Mr Nimmo has sufficient experience that is relevant to the style of mineralisation and the type of deposit under consideration and to the activity which he has undertaken to qualify as a Competent Person as defined in the 2004 edition of the ‘Australasian Code for the Reporting of Exploration Results, Mineral Resources and Ore Reserves’.



Table 4-12: Anthill Mineral Resource Estimate at a 0.2% Cu as at October 2012


East

Measured

Oxide 1.7 0.81 0.4 0.3


Sulphide - - - -

Total 1.9 0.82 0.8 0.5

Indicated

Oxide 5.7 0.63 0.3 0.3


Sulphide 0.2 0.45 4.6 2.7

Total 7.0 0.65 1.2 0.8

Inferred

Oxide 0.1 0.31 0.5 0.3


Sulphide 1.2 0.45 6.4 4.1

Total 1.6 0.43 5.8 3.7

Total

10.5 0.65 1.8 1.2

Link

Indicated

Oxide 1.0 0.28 0.1 0.1


Sulphide 0.02 0.57 10.0 6.0

Total 1.1 0.29 1.0 0.6

Inferred

Oxide 1.8 0.24 0.2 0.2


Sulphide 0.04 0.44 8.6 4.7

Total 1.9 0.25 0.5 0.4

Total

3.0 0.26 0.7 0.5

West

Measured

Oxide 1.5 0.56 0.1 0.1


Sulphide 0.02 0.60 5.8 3.5

Total 1.8 0.57 1.0 0.6

Indicated

Oxide 2.9 0.45 0.3 0.3


Sulphide 0.7 0.61 5.7 3.2

Total 4.7 0.51 2.6 1.5

Inferred

Oxide 0.04 0.27 0.2 1.1

Transitional 0.01 0.37 10.2 6.0

Sulphide 0.7 0.61 6.9 3.9

Total 0.8 0.58 6.6 3.8

Total

7.3 0.53 2.6 1.5

TOTAL

Measured

Oxide 3.3 0.69 0.3 0.2


Sulphide 0.02 0.60 5.9 3.5

Total 3.7 0.70 0.9 0.6

Indicated

Oxide 9.6 0.54 0.3 0.3


Sulphide 0.9 0.58 5.6 3.2

Total 12.8 0.56 1.7 1.0

Inferred

Oxide 1.9 0.24 0.2 0.2


Sulphide 1.9 0.51 6.6 4.0

Total 4.2 0.38 3.6 2.2

TOTAL

20.7 0.55 1.9 1.2




Table 4-13: Anthill Mineral Resource Estimate at a 0.3% Cu as at October 2012


East

Measured

Oxide 1.5 0.91 0.4 0.3


Sulphide - - - -

Total 1.6 0.92 0.8 0.5

Indicated

Oxide 4.1 0.79 0.4 0.3


Sulphide 0.1 0.47 4.4 2.6

Total 5.2 0.79 1.3 0.8

Inferred

Oxide 0.04 0.44 0.4 0.3


Sulphide 1.0 0.49 6.2 4.0

Total 1.2 0.49 5.9 3.7

Total

8.0 0.77 1.9 1.2

Link

Indicated

Oxide 0.2 0.38 0.1 0.1


Sulphide 0.02 0.57 10.0 6.0

Total 0.3 0.40 2.1 1.3

Inferred

Oxide 0.1 0.35 0.3 0.2


Sulphide 0.04 0.44 8.6 4.7

Total 0.2 0.37 3.3 1.8

Total

0.5 0.39 2.5 1.5

West

Measured

Oxide 1.3 0.62 0.1 0.1


Sulphide 0.02 0.69 5.8 3.4

Total 1.5 0.64 0.9 0.5

Indicated

Oxide 1.7 0.58 0.3 0.3


Sulphide 0.7 0.65 5.6 3.2

Total 3.2 0.62 3.0 1.7

Inferred

Oxide 0.01 0.37 0.1 1.5


Sulphide 0.7 0.62 6.7 3.8

Total 0.7 0.61 6.7 3.8

Total

5.4 0.62 2.9 1.7

TOTAL

Measured

Oxide 2.7 0.77 0.3 0.2


Sulphide 0.02 0.70 5.9 3.4

Total 3.0 0.79 0.8 0.5

Indicated

Oxide 6.1 0.71 0.3 0.3


Sulphide 0.8 0.61 5.5 3.1

Total 8.7 0.71 1.9 1.2

Inferred

Oxide 0.1 0.37 0.3 0.3


Sulphide 1.7 0.54 6.5 3.9

Total 2.1 0.52 6.0 3.6

TOTAL

13.8 0.70 2.3 1.4




5.0 MINE PLANNING

5.1 Block Model

The geological model used was an_0912md.dm, which is described in Table 4-6 and Table 4-7. Table 4-12 summarises the Mineral Resources for the Anthill deposit at a 0.2% Cu cut-off.

Table 5-1 describes the major variables common to both block models.

Table 5-1: Major Variables in Geological Model

Variable Type Description

CUDOM numeric Cu domain code (1=main zone, 0=waste)

OXIDE numeric Oxidation (0=fresh, 1=transitional, 2=oxide)

CU numeric Estimated Cu % block value

CA numeric Estimated Ca % block value

MG numeric Estimated Mg % block value

SG numeric Estimated block in-situ dry bulk density t/m3

RESCAT numeric Resource classification (0=unclassified, 2=Indicated, 3=Inferred)

MINED numeric Mined flag (0=not mined, 1=removed by open pit)

AREA numeric Mining area (1=East Zone, 2=Transition Zone, 3=West Zone

Both block models use a 10x10x10m parent cells and 2.5x2.5x1m sub cells

5.2 Whittle Optimisation A Datamine script was used to create additional block model columns necessary to the Whittle Four-X software pit optimisation; which includes:

� PCAF: Processing Costs discussed in detail in section 5.3.2

� RockType: A three digit number representing RESCAT (first digit), OXIDE (second digit) and AREA (third digit)

5.2.1 Pit Optimisation Block Model

The block model was imported into Whittle software from Datamine. Table 5-2 summarises the Whittle model definition. Both parent and sub block sizes were maintained from the original block model.

Table 5-2: Whittle Parameters (an_0912_whittle.mod)

X (Easting) Y (Northing) Z (RL)

Block size (m) 10 10 10

Model origin 302 350 7 758 600 100

Extent (m) 1870 940 280

Number Blocks 187 94 28

Table 5-3 summarises the in-situ pit material by rock type within the Whittle optimisation model. For the base optimisation only Measured and Indicated Mineral Resources were used. These reconcile with the original two resource models.



Table 5-3: Optimised Pit Resources (an_0912_whittle.mod where CUDOM=1)

Resource

Classification

Weathering

Type

Deposit

Name

Rocktype

Code

Tonnage

(Mt)

Cu Grade

(%)

Measured Oxide East 121 1.73 0.81

Measured Transition East 111 0.13 1.05

Indicated Oxide East 221 5.72 0.63

Indicated Transition East 211 1.11 0.74

Indicated Sulphide East 201 0.16 0.45

Inferred Oxide East 321 0.11 0.31

Inferred Transition East 311 0.30 0.42

Inferred Sulphide East 301 1.19 0.45

Indicated Oxide Transition 222 1.02 0.28

Indicated Transition Transition 212 0.09 0.31

Indicated Sulphide Transition 202 0.02 0.57

Inferred Oxide Transition 322 1.77 0.24

Inferred Transition Transition 312 0.05 0.32

Inferred Sulphide Transition 302 0.04 0.44

Measured Oxide West 123 1.54 0.55

Measured Transition West 113 0.25 0.66

Measured Sulphide West 103 0.03 0.60

Indicated Oxide West 223 2.81 0.45

Indicated Transition West 213 1.04 0.59

Indicated Sulphide West 203 0.66 0.62

Inferred Oxide West 323 0.04 0.27

Inferred Transition West 313 0.01 0.37

Inferred Sulphide West 303 0.69 0.60

5.3 Economic Parameters

The basic economic parameters were provided by CST and are summarised in Table 5-4.

Table 5-4: Economic Parameters

Parameter Value

Copper Price (US$/lb) 3.00

Exchange Rate (AUD:USD) 1.00:0.80

Selling Costs (including transport of concentrate) 159A$/tCu

Royalty 4.4%

Administration costs for the site and corporate overheads of $12.6M per annum were not included as a unit cost per tonne. In interpreting the undiscounted values provided by the mine optimisations, the combined total should be reduced by life of mining operations (in years) multiplied by $12.6M. This was a corporate decision by CST to maximise the mine life based on a marginal cut-off grade scenario which maximises resource usage.



5.3.1 Mining Costs and Parameters

Mining costs include both fixed costs and depth dependent costs. Fixed costs are shown in Table 5-5, and total cost by depth is shown in Figure 17. The depth dependent costs are calculated on 10 m bench steps to match the parent block model size.

Table 5-5: Mining Costs

Mining Activity Cost A$/bcmrock

Excavators 0.83

Dozers 0.63

Supervision 0.14

Miscellaneous (lighting, dewater, reclaim) 0.15

Drilling and Blasting Variable by Depth (1.65 to 1.91)

Ancillary Equipment Variable by Depth (0.61 to 0.79)

Haulage Variable by Depth (1.92 to 4.48)

Figure 17: Mining Costs by Depth

Mining recovery and dilution assumptions are summarised in Table 5-6 based on values used by CST mining.

Table 5-6: Mining Recovery and Dilution

Mining Recovery 95%

Mining Dilution 2%

5.3.2 Processing Costs and Parameters

Processing costs include incremental ore costs, grade control, road transport, ROM loading, acid costs, and other ore related costs, and are summarised in Table 5-7

Incremental ore costs cover the difference between hauling waste to the waste dump and ore to stockpiles. Since it is cheaper to haul to the transfer stockpiles this component is negative.

Road transport is hauling the ore from stockpile to ROM and costs.

0

50

100

150

200

250

300

350

$0.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00

mR

L

$/bcm

Total Mining Cost by Depth



Processing costs for optimisation includes all other aspects of processing the ore including leaching, solvent extraction and electrowinning. The processing costs comprise a fixed component and a variable component based on acid consumption. Acid costs 210 $/t and the acid consumption costs are based on calcium grades as follows:

Acid Costs ($/t ore) = 1.85 + Calcium Grade (%) * 4.66

Table 5-7: Processing Costs

Mining Activity Cost A$/tore

Incremental Ore costs -0.82 between mRL 250 and mRL 290,-0.64 otherwise

Grade Control 0.75

Road Transport 6.50

ROM loading 0.51

Other Fixed Processing Costs 11.06

Acid Costs 1.85 + Ca * 4.66

The process recovery is based on an assumed residual copper component left in the heap after leaching and is shown in Table 5-8.

Table 5-8: Residual Copper

Ore Description Residual Cu (%)

Calcium below 2% 0.15%

Calcium above 2% 0.22%

The metal recovery is therefore estimated as:

Recovery = (Cu% - Residual Cu%)/ Cu%

The marginal cut-off grade for the Anthill deposit is described by the function below.

��= �0.42% + 0.06% ∗ ��, �� ≤ 2%;0.49% + 0.06% ∗ ��, �� > 2%.

The first expression is primarily used for oxide ore, the second is used mainly for transition ore. These functions are also shown in Figure 18. Note that transition ore can have very high calcium grades pushing the economic cut-off above 1% Cu as each 1% of Ca will increase the cut-off by 0.06% Cu.



Figure 18: Anthill Marginal Copper Cut-off Grade vs. Calcium

The pit optimisation used a number of constraints based on current mining practices to limit the annual production to reasonable limits. These constraints are shown in Table 5-9. Copper metal production was found to be the limiting constraint in all cases.

Table 5-9: Production Constraints

Variable Constraint

Mine 12.6 Mtpa

Plant 2.96 Mtpa

Copper Produced 25 000 tpa

5.4 Pit Slope Angles

An overall slope angle of 40° has been used for all pit walls. This was derived from the 2009 optimisation by Snowden which was based on their wall measurements at the site.

5.5 Pit Optimisation Results

Pit optimisation was carried out on all Anthill deposits. Results show there is no connection of pits between Anthill West and Anthill East. Table 5-10, Table 5-11 and Table 5-12 summarise the results for the Anthill West, Anthill East and the combined optimisations respectively.

y = 0.06x + 0.49

y = 0.06x + 0.42

0.00

0.25

0.50

0.75

1.00

1.25

1.50

0 2 4 6 8 10 12

Marg

inal C

uto

ff (C

u%

)

Ca %

Transition

Oxide

Marginal Cutoff does not

include Mining Costs but is

economic to process if it is

mined anyway



Table 5-10: Summary of Results Anthill West

Case Pit Rev Fact.

Slope Angle

Mine Life (yrs)

Rock (Mt)

Strip Ratio

Ore (Mt)

Grade (% Cu)

Cu Prod (kt)

Undisc Cash Flow ($M)

Cost ($/rec

t)

a 24 1 40 0.6 6.9 5.9 1.0 0.94 7.8 18 5635

b 28 1.08 40 0.8 7.9 5.6 1.2 0.89 8.8 18 5906

c 19 1 35 0.5 5.8 6.0 0.8 0.92 6.4 15 5625

d 23 1.08 35 0.9 8.7 6.5 1.2 0.89 8.5 14 6256

Table 5-11: Summary of Results Anthill East

Case Pit Rev Fact.

Slope Angle

Mine Life (yrs)

Rock (Mt)

Strip Ratio

Ore (Mt)

Grade (% Cu)

Cu Prod (kt)


Cost ($/rec

t)

a 26 1 40 2.0 20.2 6.2 2.8 1.20 29.1 100 4466

b 30 1.08 40 2.0 21.0 6.2 2.9 1.17 29.8 100 4551

c 26 1 35 2.1 22.6 7.2 2.8 1.19 28.6 90 4762

d 30 1.08 35 2.2 23.4 7.2 2.9 1.18 29.2 89 4837

Table 5-12: Summary of Results Anthill Combined

Case Pit Rev Fact.

Slope Angle

Mine Life (yrs)

Rock (Mt)

Strip Ratio

Ore (Mt)

Grade (% Cu)

Cu Prod (kt)


Cost ($/rec

t)

a 26 1 40 2.7 27.2 6.1 3.8 1.13 37.0 118 4716

b 30 1.08 40 2.8 28.9 6.0 4.1 1.09 38.6 117 4860

c 26 1 35 2.7 28.7 6.9 3.6 1.13 35.2 105 4934

d 30 1.08 35 3.0 32.1 7.0 4.0 1.09 37.8 104 5153

Figure 19 shows a plan view of the Whittle optimised pit shells. Figure 20 and Figure 21 show sections through the pits with all blocks that exceed the marginal cut-off grade calculated on a block by block basis. Due to the depth of the ore the stripping ratio is high which limits the pit sizes.



Figure 19: Whittle Optimal Pit Shells Anthill

Figure 20: Anthill East Whittle Pit Section 7 758 900N

Figure 21: Anthill West Whittle Pit Section 7 758 900N

Anthill West

Anthill West Anthill East

Anthill East



6.0 PIT DESIGN

6.1 Mine Design Parameters The pits were designed using a revenue factor of 1.08 (3.24USD/lb). This was chosen to maximise the resource usage with minimal impact on project value (~5%). An overall slope angle of 35 degrees was selected to match the berm and batter heights provided by the client.

Slope design parameters were provided by CST and are presented in Table 6-1.

Table 6-1: Pit Design Parameters

Domain Batter Height

Batter Angle

Berm Width

Above 290 m RL 20 m 50° 8 m

Below 290 m RL 20 m 60° 8 m

All haul roads used by mine equipment have been designed to accommodate Caterpillar 777F dump trucks. The overall haul road width of 25 m based on current mine design. For single lane traffic roads 15 m wide roads have been used. In particular this width is used to gain access to the bottom two benches.

The maximum haul road gradient is 11% based on current mining practices.

6.2 Mining Methodology Mining is currently being undertaken using normal truck and shovel operation. Excavators (6.7m

3) load 82 t

trucks. Blasting is done on 3.5 m or 3 m flitches used to make up 10 m benches. Most of the pit uses double benching for a total batter height of 20 m.

Waste material will be hauled to waste dumps adjacent to the mining areas.

Ore will be hauled to the crusher ROM (Mount Clarke and Flying Horse) or to ROM stockpiles adjacent to the pit that will then be carted using road-train to the crusher ROM stockpile.

6.3 Processing Methodology Once at the crusher ROM the ore goes through a series of processes to extract the copper which include:

� Crushing

� Agglomeration

� Stacking

� Sulphuric Acid Leaching

� Solvent Extraction

� Electrowinning

Heap leach solution costs are increased by high levels of calcium (as carbonate). CST has advised that the maximum average calcium levels in the leach heaps should be 3%. This constraint has been applied on a pit total basis and scheduling will be required to maintain this limit on a heap pad basis.

6.4 Mine Design Mine design was carried out on a Mining block model which was based on the Resource block model (anw_0912.dm). The mine design was based on the pit optimisation Case D shell 30.



The mining model (an_0912.bmf) had additional variables added based on the Whittle costs and calculations to facilitate mine planning. These are defined in Table 6-2.

Table 6-2: Additional Variables

Variable Description Model Calculation

mcutoff Marginal Cu cut-off grade iff(ca gt 2, 0.49 + 0.06 * ca, 0.42 + 0.06 * ca)

pit Whittle pit shell number Imported from Whittle results file

A plan view of the Anthill pits design is shown in Figure 22. Figure 23 is a cross section through the East Pit and Figure 24 is a section through the West Pit.

Figure 22: Anthill Pit Plan View

Figure 23: Anthill East Section 7 758 900N

345

340

270

270

225

285

Anthill East Anthill West

Anthill East



Figure 24: Anthill West Section 7 758 900N

6.5 Mineral Inventory The mineral resources were reported within the pit designs together with the waste material as shown in Table 6-3. These figures are before dilution and mining loss.

Table 6-3: Anthill In-Pit Mineral Inventory without Dilution or Mining Loss

Deposit Resource

Category

Material

Type

Tonnage

(Mt)

Cu

(%)

Contained

Cu (kt)

Ca

(%)

West

Measured

Transition 0.004 0.97 0.04 3.73

Oxide 0.48 0.86 4.13 0.10

Total 0.48 0.86 4.17 0.13

Indicated

Transition 0.02 1.25 0.25 4.34

Oxide 0.47 0.92 4.30 0.14

Total 0.49 0.94 4.55 0.31

East

Measured

Transition 0.035 2.04 0.71 5.10

Oxide 0.81 1.13 9.15 0.30

Total 0.84 1.17 9.86 0.50

Indicated

Transition 0.09 2.20 1.88 4.61

Oxide 1.55 1.16 18.02 0.18

Total 1.64 1.22 19.91 0.41

Combined

Measured

Transition 0.04 1.93 0.74 4.96

Oxide 1.29 1.03 13.29 0.23

Total 1.33 1.06 14.03 0.36

Indicated

Transition 0.11 2.02 2.13 4.56

Oxide 2.02 1.11 22.33 0.17

Total 2.12 1.15 24.46 0.39

The pit also includes 27.4 Mt of waste. The ore tonnes are lower than the whittle optimisation due to ramp requirements; which restricted the ramp design from reaching some of the ore in the base of the pits.

The overall tonnage was reduced by 4% with the ore being reduced by 14% when compared to the Whittle Optimisation.

Anthill West



Once a mineral inventory was calculated a dilution of 5% material at 0.2% Cu was applied along with a 2.5% mining loss to convert the material into an Ore Reserve.

There is no Inferred material within the designed pits. Anthill is a greenfield site with no mining having been carried out at this time.

7.0 IN-PIT MINERAL RESOURCES No Ore Reserves are reported due to the lack of a current mining lease. The in-pit Mineral Resource inventory is summarised in Table 7-1 . This includes dilution and mining recovery and should convert directly to Ore Reserves once a mining lease is secured.

Table 7-1: Anthill In-Pit Mineral Resources with Dilution and Mining Loss

Deposit Resource

Category

Material

Type

Tonnage

(Mt)

Cu

(%)

Contained

Cu (kt)

Ca

(%)

West

Measured

Transition 0.004 0.94 0.04 3.91

Oxide 0.49 0.83 4.08 0.11

Total 0.50 0.83 4.12 0.14

Indicated

Transition 0.02 1.20 0.24 4.49

Oxide 0.48 0.89 4.24 0.15

Total 0.50 0.90 4.49 0.32

East

Measured

Transition 0.035 1.95 0.69 5.22

Oxide 0.83 1.09 9.00 0.30

Total 0.86 1.12 9.69 0.50

Indicated

Transition 0.09 2.11 1.84 4.74

Oxide 1.59 1.12 17.73 0.19

Total 1.68 1.17 19.57 0.42

Combined

Measured

Transition 0.04 1.85 0.73 5.08

Oxide 1.32 0.99 13.08 0.23

Total 1.36 1.02 13.81 0.37

Indicated

Transition 0.11 1.94 2.09 4.70

Oxide 2.07 1.06 21.97 0.18

Total 2.17 1.11 24.05 0.40

The section below is a set of Ore Reserve criteria filled in for Anthill. This is provided in preparation for eventual conversion of the in-pit Mineral Resource to Ore Reserves which should follow the successful application for a mining lease covering the Anthill resource and pit designs

Estimation and Reporting of Ore Reserves

Criteria Comments

Mineral Resource Estimate for Conversion to

The Mineral Resource model for the Anthill Deposit was developed by Golder Associates Pty Ltd as part of an ongoing planning for the Lady Annie project.

The stated In-pit Mineral Resource is inclusive of the main resource statement.



Criteria Comments

Ore Reserves

Study Status The Lady Annie Project is located 120 km North of Mt Isa. It consists of three areas – Lady Annie (Lady Annie and Lady Brenda), Mt Kelly (Mt Clarke, Flying Horse and Swagman) and Anthill (Anthill West and Anthill East). The Anthill deposit is located 40km south of the Mt Kelly plant.

CopperCo began mining operations in 2007. CopperCo went into voluntary liquidation in November 2008. Mining stopped in November 2008 and production from the treatment plant in December 2009 when the project was placed on a care and maintenance basis. In June 2009 Cape Lambert Lady Annie Exploration Ltd (CCLAE) purchased the operations. CST acquired 100% of CCLAE and recommenced mining operations at Lady Annie in September 2010.

Cut-off Parameters

Cu�� 0.42% + 0.06% ∗ Ca, Ca ≤ 2%;0.49% + 0.06% ∗ Ca, Ca > 2%. The cut-off is based on both the copper content for revenue and the calcium content that affects the processing cost due to acid consumption.

Mining Factors or Assumptions

The Resource model has block size of 10x10x10m with sub cells down to 2.5x2.5x1m.

A dilution of 5% at 0.2% Cu and a mining loss of 2.5% were used.

The Ore Reserves are reported within a pit design which is based on a Whittle open pit optimisation. The optimisation was carried out including Measured and Indicated Mineral Resource categories. The optimisation used a copper price of US$3.00/lb. The pit selected was the 1.08 revenue factor shell (price US$3.24/lb). This was chosen as it matches the current metal price and meets CST’s corporate objective to maximise the resource size. This results in a 3% loss of value when applying the base case metal price of US$3.00/lb.

The overall pit slopes used for the design are based on previous optimisations carried out by Snowden which used measured actual pit slopes at the site.

Metallurgical Factors or Assumptions

The operation involves a heap leach followed by solvent extraction and electrowinning. The metal recovery is based on experience at the site and uses a residual copper grade left in the heap to estimate recovery. Residual grades are 0.15% Cu for Ca < 2% and 0.22% Cu for Ca ≥ 2%.

Recovery = (Cu-Residual)/Cu

Cost and Revenue Factors

Costs are based on history or budgets. Acid cost is an important variable and is increased for increased calcium grade.

The base price assumed is US$3.00/lb Cu with an exchange rate of USD$0.8 = AUD$1

Market Assessment

Copper is produced as LME Grade A equivalent cathode with a nominal production of 25 kt/a.

Other The Lady Annie mine is operating with all its necessary approvals and licenses however the Anthill deposit is not within an approved mining lease at this time.

Classification There is Measured, Indicated and Inferred Mineral Resources within the model. The Measured and Indicated Mineral Resources within the designed pits have not been converted to Proved and Probable Ore Reserves (Measured to Proved, Indicated to Probable) as yet due to the lack of current mining lease.

Audit/Previous Studies

Snowden carried out a Resource estimation on the Anthill Deposit in May 2011 which was 6.5 Mt at 0.86% Cu compared to 13.8 Mt at 0.7% Cu (cut-off 0.3% Cu) in this report.



Report Signature Page

GOLDER ASSOCIATES PTY LTD

Matthew Nimmo Ross Bertinshaw Principal Geologist Principal

MN/JH/MN

A.B.N. 64 006 107 857

Golder, Golder Associates and the GA globe design are trademarks of Golder Associates Corporation.

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