micromine_report_extract

Feasibility Study for the Holañia

Prospect in Niebla, South

America.

MICROMINE Exploration Project

Presented to: Dr. Dave Holwell

March 2015

Word Count: 2702

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Table of Contents

Feasibility Study of the Holañia Prospect in Niebla, South America. Page | 2

- TABLE OF CONTENTS -

EXECUTIVE SUMMARY ........................................................................................................... 4

SECTION 1: INTRODUCTION ................................................................................................... 5

1.1 Aims of Report ........................................................................................................................5 1.2 Data collection methods .........................................................................................................5 1.3 Geology ...................................................................................................................................5

1.3.1 Regional structural geology........................................................................................7 1.3.2 Local structural geology .............................................................................................7

SECTION 2: DATA VERIFICATION ............................................................................................. 8

2.1 QA/QC methods ......................................................................................................................8 2.2 Blanks ......................................................................................................................................8 2.3 Certified Reference Material (CRM) Standards ................................................................... 10

2.3.1 Accuracy monitoring................................................................................................ 11 2.3.2 Precision monitoring ................................................................................................ 13

SECTION 3: RESULTS ............................................................................................................ 14

3.1 Stream Sediment Data ......................................................................................................... 14 3.1.1 Arsenic and antimony anomalies ............................................................................ 14 3.1.2 Copper anomalies .................................................................................................... 14 3.1.3 Bismuth/tungsten and lead/zinc anomalies ............................................................ 14

3.2 Soil Survey ............................................................................................................................ 18 3.2.1 Arsenic and antimony anomalies ............................................................................ 18 3.2.2 Copper anomalies .................................................................................................... 18 3.2.3 Gold and silver anomalies ....................................................................................... 18 3.2.4 Mercury anomalies .................................................................................................. 21 3.2.5 Uranium enrichment in surrounding lithologies ...................................................... 21

3.3 IP Data .................................................................................................................................. 22

SECTION 4: INTERPRETATION OF DEPOSIT TYPE .................................................................... 23

4.1 Classification ........................................................................................................................ 23 4.2 Characteristics, ore genesis and tectonic setting ................................................................ 24

SECTION 5: DRILLING PROGRAMME ..................................................................................... 25

5.1 Drillhole locations ................................................................................................................ 25

SECTION 6: RECOMMENDATIONS ......................................................................................... 28

6.1 Target generation ................................................................................................................ 28 6.1.1 Trace element anomalies (Ni/Cr) associated with contamination .......................... 29

6.2 Ranking criteria .................................................................................................................... 30

SECTION 7: REFERENCES....................................................................................................... 32

SECTION 8: APPENDICES ...................................................................................................... 33

MICROMINE Exploration Project | March 2015


SECTION 2: DATA VERIFICATION

2.1 QA/QC Methods

Geochemical data used in this study was inherited from a previous exploration company. It is

therefore imperative that quality control and quality assurance (QA/QC) checks are performed to

ensure the reliability of the acquired datasets. Control samples were assigned a unique sample

number and inserted randomly into data sequences before being sent to an external laboratory for

analysis. Assay results were received and statistically analysed to monitor variations in accuracy and

precision. As sample numbers were assigned sequentially, control charts were also plotted to

analyse instrumental drift (Figures 3; 4a-c).

2.2 Blanks

Reagent Blanks comprised 8.6% and 1.2% of the stream sediment and soil assays respectively. These

are assumed to have low concentrations of contaminants, and Table 1(a-b) indicates that the

majority of elements (Cu, Pb, W, Sb, Bi, U, Au, Ag and Hg) obtained detection limit (DL) values to a

high precision (standard deviations <1).

a) Stream Sediment

Blanks Maximum Minimum Mean Standard Deviation

(ppm

)

Cu 3 1 1.2 0.6

Ni 11 4 7.9 2.1

Pb 4 1 1.6 1

Zn 11 2.5 8 2.1

W 0.5 0.5 0.5 0

As 6 2.5 2.9 1.1

Sb 2 0.5 0.8 0.4

Bi 0.5 0.5 0.5 0

Cr 8 2.5 4.2 1.7

U 1 0.5 0.5 0.1

b) Soil Survey Blanks

Maximum Minimum Mean Standard Deviation

(ppm

)

Cu 1 1 1 0 Ni 0.5 0.5 0.5 0 Pb 2.5 2.5 2.5 0 Zn 2.5 2.5 2.5 0 W 0.5 0.5 0.5 0 As 12 8 10.1 1.2 Sb 0.3 0.3 0.3 0 Bi 0.3 0.3 0.3 0 U 0.5 0.5 0.5 0

(ppb)

Au 0.5 0.5 0.5 0

Ag 12.5 12.5 12.5 0

Hg 27 12.5 14.1 4.8

Table 1: Statistical analysis for blank control samples for, a) stream sediment and, b) soil survey assays.



Erroneous results for Zn, Cr and Ni were received from the stream sediment assay. The maximum values

for Zn and Cr were 11 ppm and 8 ppm respectively, which do not exceed the accepted threshold of

three times the laboratory detection limit (<15 ppm). Conversely, the maximum value obtained for Ni

was 11 ppm, which falls outside of the threshold (<3 ppm), and it is likely that Blank samples were

subjected to considerable amounts of Ni contamination (Fig. 3). Contaminants may have been

introduced by the use of metallic (stainless steel) instruments, or via contact with other samples during

assay.

Soil assay results were free of elevated values with the exception of As, which gave a maximum value of

12 ppm. However, the accepted tolerance was <15 ppm and therefore contamination of As is not

regarded as significant.

Detection Limit: <1

3 x Detection Limit

0.00

2.00

4.00

6.00

8.00

10.00

12.00

NB

A0

04

NB

A0

16

NB

A0

29

NB

A0

39

NB

A0

53

NB

A0

63

NB

A0

75

NB

A0

88

NB

A0

98

NB

A1

11

NB

A1

22

NB

A1

33

NB

A1

45

NB

A1

56

NB

A1

028

NB

A1

140

NB

A1

201

NB

A1

238

NB

A1

337

NB

A1

397

NB

A1

529

NB

A1

613

NB

A1

723

Ni (

pp

m)

Sequential sample ID

3 x Detection Limit

Detection Limit: <5

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

NB

A0

04

NB

A0

16

NB

A0

29

NB

A0

39

NB

A0

53

NB

A0

63

NB

A0

75

NB

A0

88

NB

A0

98

NB

A1

11

NB

A1

22

NB

A1

33

NB

A1

45

NB

A1

56

NB

A1

028

NB

A1

140

NB

A1

201

NB

A1

238

NB

A1

337

NB

A1

397

NB

A1

529

NB

A1

613

NB

A1

723

As

(pp

m)


Figure 3: Control charts plotted for the analysis of sequentially numbered Ni and As assays for both

stream sediment and soil data. Values in red exceed the accepted limits (> 3 x DL) and are

interpreted having been contaminated in the laboratory. Data tables/calculations can be found in

Appendix I.



2.3 Standards

Certified Reference Material (CRM) standards comprised 6.1% and 1.3% of the stream sediment and

soil assays respectively. The bias between the obtained mean and the certified values for each

element were analysed to give accuracy; and within-batch precision was monitored, as the samples

were also repeats (Tables 2 and 3).

Standard A


% accuracy

% deviation from certified

value

% standard error of the

mean

(ppm

)

Cu 212 198 206.6 5.3 98.4 1.6 2.4

Ni 32 15 24.8 7.7 112.7 -12.7 3.5

Pb 152 118 134.4 15.4 92.7 7.3 6.9

Zn 46 40 43.2 2.4 102.9 -2.9 1.1

W 12 10 10.8 0.8 90.0 10.0 0.4

As 108 102 105.2 2.2 110.7 -10.7 1.0

Sb 24 20 22.6 1.7 90.4 9.6 0.7

Bi 10 7 8.6 1.1 71.7 28.3 0.5

Cr 45 36 38.8 3.7 155.2 -55.2 1.7

U 5 2 3.2 1.3 64.0 36.0 0.6

Standard B


% accuracy

% deviation from

certified value

% standard error of

the mean

(ppm

)

Cu 55 50 52.4 1.9 98.9 1.1 0.9

Ni 152 120 139.2 12.7 105.5 -5.5 5.7

Pb 65 38 51.0 10.2 83.6 16.4 4.6

Zn 16 13 14.6 1.1 97.3 2.7 0.5

W 39 32 35.0 2.5 97.2 2.8 1.1

As 61 59 59.8 0.8 108.7 -8.7 0.4

Sb 129 116 120.0 5.2 100.0 0.0 2.3

Bi 41 35 38.0 2.2 84.4 15.6 1.0

Cr 42 38 40.2 1.8 95.7 4.3 0.8

U 251 245 248.2 2.4 112.8 -12.8 1.1

Table 2: Statistical analysis for Certified Reference Material Standards for the stream sediment assay;

values highlighted are those which exceed the accepted limits for accuracy and precision.



2.3.1 Accuracy monitoring

The majority of elements (Cu, Zn, W, Sb, Au, Ag and Hg) attained high accuracies of >90 % for both

standards A and B. Assay mean deviations outside of the accepted parameters (> ±10 % deviation from

the certified value) were returned for Ni, As, Bi, U, Pb and Cr.

The least accurate value was 64% for U during the stream sediment assay. However, a significant

improvement was observed for the subsequent soil assay (Fig. 4a), and similar trends were obtained for

Bi and Pb. Higher accuracy for these elements was also obtained for standard B compared with standard

A, with the U assay mean deviating <5 % from the certified value of standard B (42 ppm). This is well

within the accepted limits and may validate the use of this dataset with high U anomalies.

Standard A


% accuracy


value


mean

(pp

m)

Cu 223 210 217.0* 5.4* 103.3 3.3 2.4

Ni 20 16 17.6 1.7 80.0 -20.0 0.7

Pb 160 145 154.2 5.7 106.3 6.3 2.6

Zn 45 41 42.4 1.7 101.0 1.0 0.7

W 14 11 12.4 1.1 103.3 3.3 0.5

As 86 81 83.6 2.1 88.0 -12.0 0.9

Sb 28 25 26.2 1.3 104.8 4.8 0.6

Bi 15 13 13.6 0.9 113.3 13.3 0.4

U 5 2 3.8 1.3 76.0 -24.0 0.6

(pp

b) Ag 125 86 109.4 15.1 104.2 4.2 6.8

Au 69 62 65.2 2.9 100.3 0.3 1.3

Hg 230 216 222.0 5.6 100.9 0.9 2.5

*Corrected for anomalous value obtained for sample NBA1495, see Appendix III.

Standard B


% accuracy


value


mean

(pp

m)

Cu 58 50 53.2 3.1 100.4 -0.4 1.4

Ni 123 102 111.4 8.0 84.4 15.6 3.6

Pb 70 65 68.4 2.1 112.1 -12.1 0.9

Zn 16 13 14.8 1.3 98.7 1.3 0.6

W 38 35 36.2 1.3 100.6 -0.6 0.6

As 48 42 44 2.5 80.0 20.0 1.1

Sb 126 119 123 2.9 102.5 -2.5 1.3

Bi 48 44 46.2 1.5 102.7 -2.7 0.7

U 45 38 41.4 2.7 98.6 1.4 1.2

(pp

b) Ag 50 34 41.8 6.2 119.4 -19.4 2.8

Au 11 8 9.4 1.5 94.0 6.0 0.7

Hg 148 140 143.4 3.4 98.9 1.1 1.5 Table 3: Statistical analysis for standards A and B obtained for the soil assay; values highlighted in red are those

which exceed acceptable accuracy and precision limits.



0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0N

BA

00

8

NB

A0

23

NB

A0

58

NB

A0

81

NB

A1

38

NB

A1

30

6

NB

A1

36

5

NB

A1

49

5

NB

A1

56

0

NB

A1

64

4

U (

pp

m)


U STD A

30.0

32.0

34.0

36.0

38.0

40.0

42.0

44.0

46.0

48.0

50.0

NB

A0

44

NB

A0

69

NB

A0

94

NB

A1

16

NB

A1

50

NB

A1

05

2

NB

A1

09

7

NB

A1

27

5

NB

A1

41

8

NB

A1

45

8

U (

pp

m)


U STD B

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

NB

A0

08

NB

A0

23

NB

A0

58

NB

A0

81

NB

A1

38

NB

A1

306

NB

A1

365

NB

A1

495

NB

A1

560

NB

A1

644

Ni (

pp

m)


Ni STD A

90.0

100.0

110.0

120.0

130.0

140.0

150.0

160.0

170.0

NB

A0

44

NB

A0

69

NB

A0

94

NB

A1

16

NB

A1

50

NB

A1

052

NB

A1

097

NB

A1

275

NB

A1

418

NB

A1

458

Ni (

pp

m)


Ni STD B

70.0

75.0

80.0

85.0

90.0

95.0

100.0

105.0

110.0

115.0

120.0

NB

A0

08

NB

A0

23

NB

A0

58

NB

A0

81

NB

A1

38

NB

A1

306

NB

A1

365

NB

A1

495

NB

A1

560

NB

A1

644

As

(pp

m)


As STD A

20.0

25.0

30.0

35.0

40.0

45.0

50.0

55.0

60.0

65.0

NB

A0

44

NB

A0

69

NB

A0

94

NB

A1

16

NB

A1

50

NB

A1

05

2

NB

A1

09

7

NB

A1

27

5

NB

A1

41

8

NB

A1

45

8

As

(pp

m)


As STD B

Figure 4: Control charts showing within- and between-batch variations of CRM standards. Results which plot

within a narrower band have a lower variance and are therefore more precise; and the bias between the batch

mean and the certified values can be compared to give the accuracy. a) Uranium has greater accuracy and

precision for higher concentrations (standard B); b) Nickel is consistently inaccurate and precise; c) Arsenic

shows high precision and low accuracy during the entire assay.



SECTION 3: RESULTS

6.1 Stream sediment data

Geochemical data obtained during the collection of stream sediment samples was collated to

indicate the presence of pathfinder elements. The association between anomalous trace elements

(Cu, Pb, Zn, As, Sb, Bi and W) is given in Table 4.

3.1.1 Arsenic and antimony anomalies

Strong correlations are observed for As and Sb, which obtained maximum anomalous values of 878

ppm and 300 ppm respectively. The spatial distribution of these elements is displayed in Figure 5;

where anomalous data forms clusters adjacent to the volcanic units. The densest cluster of data

points occurs at [9796, 17892], and so it is estimated that a mineralised zone forms here, and may

be associated with N-S trending D2 faults.

3.1.2 Copper anomalies

The highest copper anomalies (956 ppm) are situated towards the north of the licence area (Figure

6). However, these values are highly dispersed, with an approximate distance of 200 m between

individual anomalies. Clustering of data points occurs further south and correlates with other

chalcophile element (Sb, As, Pb, Zn) anomalies. It is here where the highest geological confidence

is assumed and therefore interpreted as an area hosting mineralisation. Conversely to As and Sb,

copper shows no apparent relationship with structural features in the area for stream sediment data.

3.1.3 Other associated anomalies

Anomalous clusters for Bi, Pb and Zn are also associated with the area described in the above

sections. Bismuth obtained a maximum value of 15 ppm, and can be used to constrain the location

of mineralisation due to its low surface mobility and subsequent low proximity to the ore deposit

(Figure 7).

Cu Pb Zn W As Sb Bi

Cu 1.0

Pb 0.3 1.0

Zn 0.3 0.3 1.0

W 0.0 0.4 -0.1 1.0

As 0.3 0.3 0.6 0.1 1.0

Sb 0.0 0.2 0.4 0.4 0.8 1.0

Bi 0.0 0.4 -0.1 0.9 0.2 0.5 1.0

Table 4: Correlation matrix indicating geochemical associations for anomalous trace elements found in the stream sediment samples. Highlighted values are those which represent a strong correlation (>0.7) between two elements.



Figure 5: Spatial distribution of Sb and As anomalies within the licence area, which appear to

have an association with and occur along D2 fault traces. The area situated centrally within the

licence area is estimated to give the location of mineralisation to the highest level of confidence

due to dense clustering of anomalies.



6.2 Soil data

Anomalous concentrations of trace elements are incorporated into soils by weathering processes,

and create a secondary dispersion halo around the mineralised zone. Therefore, a soil survey was

conducted over a prospective area recognised by the stream sediment analysis. Anomalous values

were returned for Au, Ag, Hg, Cu, Pb, Zn, Bi and W, and the associations between these elements is

summarised in Table 5.

3.2.1 Antimony and arsenic anomalies

A strong correlation exists between As and Sb for the soil as well as the stream sediment data. Arsenic

shows a greater dispersal from the proposed mineralised zone compared with antimony (Fig. 8), which

is likely a feature of its high surface mobility, particularly in oxidising conditions. Nonetheless, the

highest anomalies (> 100 ppm) were situated adjacent to more competent lithologies, displaying a N-

S trend which further indicates an association with D2 structures.

3.2.2 Copper anomalies

Copper is incorportated into soils via absorption by clays and Fe-Mn oxides. High anomalous values

exceeding background were obtained during the soil survey confining an area shown in Figure 8. This

is regarded as being well above average for lithological enrichment and background levels, despite

the stream sediment analysis gave comparatively moderate copper anomalies compared with other

localities within the licence area.

3.2.3 Gold and silver anomalies

A close correlation exists between anomalous values of Ag and Au (Fig. 9). Both elements obtained

anomalies > 200 ppm, resulting in a high Ag/Au ratio of 1:1 at some localities. This confirms the

observations made from the abundance of pathfinder elements in the stream sediment analysis in that

this deposit hosts economic quantities of gold. The spatial distribution of Ag and Au gives some bias

towards a N-S trend, which may indicate localisation of anomalies within D2 structures.

Au Ag As Cu Zn Pb Bi Sb W Hg

Au 1.0

Ag 0.6 1.0

As 0.6 0.6 1.0

Cu 0.8 0.6 0.7 1.0

Zn 0.4 0.3 0.3 0.4 1.0

Pb 0.5 0.3 0.3 0.4 0.9 1.0

Bi 0.6 0.3 0.7 0.6 0.2 0.3 1.0

Sb 0.8 0.5 0.7 0.8 0.4 0.4 0.6 1.0

W 0.7 0.4 0.5 0.6 0.3 0.3 0.5 0.6 1.0

Hg 0.8 0.5 0.7 0.9 0.3 0.4 0.7 0.9 0.6 1.0

Table 5: Correlation matrix indicating the geochemical associations between anomalous elements in the soil

survey. Highlighted values are those which represent a strong correlation (>0.7) between two elements.



Figure 8: Spatial distributions of Sb and As within the licence area for soil data, As shows high

dispersal due to its high surface mobility.

Figure 9: Spatial distributions of Cu anomalies within the licence area for soil data.



SECTION 5: DRILL PROGRAMME

Having interpreted the mineralisation style, an exploration drilling programme is proposed here with

Mackem Drilling Inc., to better define mineral resources with the Holañia Prospect. The programme

comprises a total 3979 m of drilling corresponding to sixteen drill holes costing US$ 999,900 (Table 7). Collar

locations were chosen to define the spatial associations of the deposit with the regional scale structures, as

well as the vein-type morphology of the deposits.

5.1 Drillhole locations

Drill collars are scattered about the inferred D2 fault plane to record lateral (along strike) variations,

whilst drill traces are designed to intersect the plane at multiple dips to observe variations in

mineralisation with depth (Figures 13-15). BH1-4 are drilled so as to intersect the plane at Z=120

m, as high IP anomalies were found at this depth. BH8-13 were plotted to assess mineralisation at

greater depths in the system, capped at 400 m due to the nature of the deposit being hosted in the

shallow crust (300 – 600 m). BH14-16 are drilled to intersect the adjacent inferred fault which offsets

the volcanic rocks from the carbonate sediments, to further analyse the significance of the structural

relationship.

It is estimated that the borehole data should retrieve characteristic massive and disseminated ores

hosted by quartz gangue. Distinct alteration patterns grading from propylitic into advanced argillic

(kaolinite-alunite) alteration may be seen with increasing proximity to the mineralised zone.

It is hoped that drilling shall help to define the mineral deposit in terms of depth (along a particular

horizon) and grade/tonnage, in an attempt to increase geological confidence.

Hole ID EAST NORTH RL DEPTH (M) DIP AZIMUTH

BH01 9834.708 17458.95 165.43 90 -65 90

BH02 9894.862 17385.92 161.155 100 -60 270

BH03 9841.729 17317.04 181.049 90 -65 90

BH04 9919.186 17248.24 186.927 100 -60 270

BH05 9794.12 17411.39 183.757 250 -80 90

BH06 9930.94 17342.95 167.104 260 -60 270

BH07 9801.059 17272.77 190.878 250 -80 90

BH08 9954.608 17207.57 202.856 260 -60 270

BH09 9762.947 17480.92 191.87 390 -85 90

BH10 9963.85 17434.76 166.566 400 -60 270

BH11 9760.062 17365.58 195.385 390 -85 90

BH12 9971.179 17293.49 173.033 400 -60 270

BH13 9766.621 17227.5 192.663 390 -85 90

BH14 9548.082 17287.98 129.03 300 -85 90

BH15 9694.942 17256.36 153.14 209 -60 270

BH16 9594.149 17224.97 130.439 100 -65 90

Table 7: Data table indicating the location of drill collars and corresponding depths and

azimuths. See Appendix IV for cost calculations.



Figure 13: Plan view of proposed drill programme, with drill collars focussed around the highest IP

anomalies.



Figure 14: Side view (left) and 3D view (right) of proposed drill programme, with boreholes

intersecting major D2 fault traces.

Figure 15: 3D view of proposed drill programme, showing boreholes scissoring major D2 fault

traces.

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