craton mining & exploration pty ltd datamine during the de-survey process. 10% of the 2014...

CLIENT: Craton Mining & Exploration Pty Ltd

PROJECT: Omitiomire Resource Model

REPORT: Evaluation Report

DATE: 31/08/2014

REPORT PREPARED FOR:

Craton Mining & Exploration Pty Ltd

AUTHORS:

Carrie Nicholls & Michael Rohwer

e: [email protected] Bloy - Omitiomire Evaluation - 20140831.docx

© Bloy, 2013. All rights reserved.

Craton – Omitiomire Resource Evaluation – 31/08/2014

i

Executive Summary

Bloy were requested by Craton Mining & Exploration (Pty) Ltd (“Craton”) to model the Omitiomire copper deposit, Namibia, during July and August 2014. The objective was to update the Mineral Resource Estimate for additional drilling completed between July 2012 and May 2014. As well as the estimation of copper, sulphur and Percent Dark (PC Dark) were to be interpolated for mineral processing requirements. The model was to be JORC compliant and form part of the annual reporting for Craton in 2014. Bloy visited the Omitiomire site in May 2014 to observe reverse circulation drilling and sampling procedures and to ensure that procedures were still being followed for logging, sampling and data capture. From mid-2012 to May 2014 an infill drilling campaign added over 18 000 m of drillhole information. The majority of drillholes were reverse circulation (94%) and the remainder were diamond core. The campaign was mostly infill to 25 x 25 m in selected areas throughout the deposit. The QAQC data was reviewed for the Cu and S data which generally returned acceptable results. The repeatability of the samples is very good and there is no evidence of contamination in the sample preparation of the laboratory. The certified reference material (“CRM”) results show variable levels of performance though the CRM near the cut-off grade performs very well. Craton also submit samples for re-assay to an Umpire laboratory for both copper and sulphur. The QAQC programme followed by Craton is of a sufficient standard, though the insertion rate (16%) for this time period is a little lower than the intended 20%. This has been explained to be owing to the disproportionate number of short holes in the drilling campaign. The final database was received on 14th July 2014 and underwent standard validation routines carried out in Datamine during the de-survey process. 10% of the 2014 drilling campaign database was checked against the original hard copies along with 12 other drillholes which amounted to 3% of the total database. No significant errors were found. The general geology of the deposit consists of copper-bearing mafic schists inter-banded with largely barren felsic gneiss. The banding is usually on a centimetre to metre scale, but amphibolite bands can be tens of metres thick. The deposit is broadly sheet-like, striking north-south and dipping approximately 15° to the east. The strike length of the deposit is 3.6 km and across strike it reaches 1.7 km. The thickness of mineralisation can be 100 m but typically lenses are between 10 and 30 m. The interpretation of the mineralised zones was undertaken by Karl Hartman of Craton. Wireframes were created in Datamine of the various lenses. The interpretation was based on logged geological contacts and a cut-off of 0.25% Cu. The methodology of the Cu% estimate followed these steps:

Review of mineralised wireframes supplied by Craton.

Statistical analysis of domains.

Variography analysis.

Grade estimation by Ordinary Kriging into blocks of 50 x 50 x 10 m with 25 x 25 x 5 m blocks in selected areas where drill spacing was consistently 25 x 25 m. Local orientation of search volume and variogram using dynamic anisotropy.

Where a kriged estimate could not be determined after two search volumes, a declustered domain mean was applied to the block.

Classification of the model based on quality of data, geostatistical parameters, drill spacing, number of samples and confidence in geological interpretation.

The gas pycnometer density dataset has increased to 7 513 measurements. This has allowed for a review of the grade/density relationship equations and bulk densities, which were updated for use in the density interpolation. The regression equations are used particularly in the mineralised zones where density readings were not carried out. Average bulk densities were assigned to the lithologies for which no density was determined. Craton required two geometallurgical fields to be interpolated, S% and “% Dark”. For previous models Craton required sulphur ratio (S ratio) to be interpolated for geometallurgical requirements but they have determined that this is no longer necessary and that estimation of S% would be sufficient. The


ii

geostatistical parameters were updated for S% and % Dark and interpolated by Ordinary Kriging into the block model. The Mineral Resource has been classified and reported in accordance with the 2012 Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (JORC, 2012) using a cut-off of 0.25% Cu. The relevant sections of the JORC Checklist of Assessment and Reporting Criteria are supplied in Appendix 4. The table below summarises the Mineral Resource Estimate as of 31st August 2014 with the Measured and Indicated resources constituting 71% of the deposit.

Cut-off grade Resource Class Tonnes Grade Cont. metal

(t) (%) (t)

0.25 %

Measured 4 427 281 0.85 37 525

Indicated 93 380 056 0.52 486 237

Inferred 39 098 770 0.56 217 261

Total 136 906 107 0.54 741 023

Exploration Target material at a cut-off grade of 0.25% Cu is reported to be in the range of 76 to 155 Mt for 430 to 650 Kt of metal between 0.4 and 0.6 % grade. This represents areas that have been drilled but do not meet the confidence criteria for resource classification. The material this relates to is an extension to the currently defined mineralised zones of the deposit and Exploration Targets, Mamba and Tiger, in close proximity to the west and south west respectively of the deposit. The potential quantity and grade of the Exploration Target material remains conceptual in nature and may or may not be realised in the future.


i

Table of Contents

Executive Summary ............................................................................................................ i

Table of Contents................................................................................................................ i

List of Figures ..................................................................................................................... i

List of Tables ....................................................................................................................... i

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

1.1. Background ..................................................................................................................... 1

1.2. Scope of Works ............................................................................................................... 1

1.3. Sources of Information ................................................................................................... 1

1.4. Site Visits ........................................................................................................................ 1

2. Property Description and Location ............................................................................ 2

3. History .......................................................................................................................... 4

3.1. Project History ................................................................................................................ 4

3.2. Exploration and Development ....................................................................................... 5

3.2.1. Resource Extension Drilling Campaign ..................................................................................... 5

3.2.2. Metallurgical Drilling Campaign ................................................................................................. 6

3.2.3. Shallow Oxide Resource ........................................................................................................... 6

3.2.4. Exploration drilling campaigns ................................................................................................... 7

3.3. Historic Resource Estimates ......................................................................................... 8

3.4. Previous Production ....................................................................................................... 8

4. Geology ........................................................................................................................ 9

4.1. Geological Setting .......................................................................................................... 9

4.2. Deposit Geology ........................................................................................................... 10

5. Drilling ........................................................................................................................ 14

5.1. Drilling Campaigns ....................................................................................................... 14

5.2. Discovery Potential....................................................................................................... 15

5.3. Drilling Types ................................................................................................................ 17

5.3.1. Drill Types ................................................................................................................................ 17

5.3.2. Drill Diameters ......................................................................................................................... 18

5.3.3. Drilling Type Comparison ........................................................................................................ 19

5.4. Drill Orientation ............................................................................................................. 19

5.5. Drilling Quality .............................................................................................................. 19

5.6. Survey Control .............................................................................................................. 19


ii

5.6.1. Collars ...................................................................................................................................... 19

5.6.2. Downhole ................................................................................................................................. 19

5.6.3. Topographic Control ................................................................................................................ 21

6. Geological Logging ................................................................................................... 23

6.1. Density Determination .................................................................................................. 24

7. Sampling Methods .................................................................................................... 25

7.1. Sub-sampling Description ............................................................................................ 25

7.1.1. Diamond sampling ................................................................................................................... 25

7.1.2. RC sampling ............................................................................................................................ 26

7.2. Sampling Quality .......................................................................................................... 27

7.3. Sample Storage ............................................................................................................. 27

8. Sample Assaying ....................................................................................................... 28

8.1. Analytical Laboratories ................................................................................................ 28

8.2. Sample Preparation ...................................................................................................... 28

8.2.1. Diamond sampling ................................................................................................................... 28

8.2.2. RC sampling ............................................................................................................................ 29

8.3. Analytical Procedures .................................................................................................. 30

8.3.1. Previous Laboratories .............................................................................................................. 30

8.3.2. Current Laboratory ................................................................................................................... 30

9. Assay QAQC .............................................................................................................. 32

9.1. QAQC Procedures ........................................................................................................ 32

9.1.1. Standards ................................................................................................................................. 32

9.1.2. Blanks ...................................................................................................................................... 32

9.1.3. Duplicates ................................................................................................................................ 32

9.1.4. QAQC Failure Rules ................................................................................................................ 33

9.2. QAQC Results - Copper ............................................................................................... 33

9.2.1. Standards ................................................................................................................................. 33

9.2.2. Blanks ...................................................................................................................................... 37

9.2.3. Duplicates ................................................................................................................................ 38

9.3. QAQC Results - Sulphur .............................................................................................. 40

9.3.1. Standards ................................................................................................................................. 40

9.3.2. Blanks ...................................................................................................................................... 43

9.3.3. Duplicates ................................................................................................................................ 44

9.4. Umpire Analysis ............................................................................................................ 45

9.4.1. Umpire QAQC .......................................................................................................................... 45

9.4.2. Umpire Results ........................................................................................................................ 46

9.5. Discussion and Conclusions ....................................................................................... 51


iii

9.5.1. Copper ..................................................................................................................................... 51

9.5.2. Sulphur ..................................................................................................................................... 51

10. Drillhole Database ..................................................................................................... 52

10.1. Database Description ................................................................................................ 52

10.2. Database Procedures ................................................................................................ 52

10.3. Data Verification ........................................................................................................ 53

10.3.1. Digital Error Checking .............................................................................................................. 53

10.3.2. Manual (Hard Copy) Validation ................................................................................................ 53

11. Statistical Analysis .................................................................................................... 55

11.1. Stationarity Testing ................................................................................................... 55

11.2. Estimation Domains .................................................................................................. 55

11.2.1. Definition .................................................................................................................................. 55

11.2.2. Methodology ............................................................................................................................ 56

11.2.3. Validation ................................................................................................................................. 56

11.3. Sample Assay Statistics ........................................................................................... 56

11.3.1. Copper ..................................................................................................................................... 56

11.3.2. Sulphur ..................................................................................................................................... 60

11.3.3. Percentage Dark ...................................................................................................................... 61

11.3.4. Rock Type ................................................................................................................................ 62

11.4. Declustering Analysis ............................................................................................... 63

11.5. Compositing .............................................................................................................. 64

11.6. Extreme Values ......................................................................................................... 64

11.7. Missing Samples ....................................................................................................... 65

11.8. Density Statistics ...................................................................................................... 65

12. Geological Modelling ................................................................................................ 70

12.1. Geological Interpretation .......................................................................................... 70

12.2. Block Attribute Modelling ......................................................................................... 70

12.2.1. Block Model Setup ................................................................................................................... 70

12.2.2. Lithology ................................................................................................................................... 70

12.2.3. Estimation Domains ................................................................................................................. 71

12.2.4. Structure .................................................................................................................................. 71

12.2.5. Topography .............................................................................................................................. 71

12.2.6. Density ..................................................................................................................................... 72

12.2.7. PC DARK ................................................................................................................................. 72

12.2.8. Depletion .................................................................................................................................. 72

13. Variography ............................................................................................................... 73

13.1. Copper ....................................................................................................................... 73


iv

13.1.1. Calculation Parameters ........................................................................................................... 73

13.1.2. Variogram Models .................................................................................................................... 74

13.1.3. Variogram Comparison ............................................................................................................ 75

13.1.4. Variogram Quality .................................................................................................................... 76

13.2. Sulphur ...................................................................................................................... 77

13.2.1. Variogram Model ..................................................................................................................... 77

13.3. Percentage Dark ........................................................................................................ 78

13.3.1. Variogram Model ..................................................................................................................... 78

14. Grade Estimation ....................................................................................................... 80

14.1. Quantitative Kriging Neighbourhood Analysis ....................................................... 80

14.1.1. Panel Size Selection ................................................................................................................ 80

14.1.2. Search Distance....................................................................................................................... 80

14.1.3. Number of Samples ................................................................................................................. 80

14.1.4. Discretisation ........................................................................................................................... 83

14.1.5. Kriging Sensitivities .................................................................................................................. 83

14.1.6. Final Optimised Parameters .................................................................................................... 85

14.2. Kriging ....................................................................................................................... 85

14.2.1. Kriging Setup ........................................................................................................................... 85

14.2.2. Parameter Validation ............................................................................................................... 86

14.2.3. Model Validation ...................................................................................................................... 86

14.2.4. Reconciliation with Previous Production .................................................................................. 96

14.2.5. Density ..................................................................................................................................... 96

14.3. Geometallurgical Classification Models .................................................................. 96

14.3.1. Sulphur ..................................................................................................................................... 96

14.3.2. Percentage Dark ...................................................................................................................... 97

15. Classification ............................................................................................................. 98

15.1. Classification Methodology ...................................................................................... 98

15.2. Classification Validation ......................................................................................... 103

15.3. Key Criteria for Resource Classification ............................................................... 104

15.4. Reconciliation with Previous Models ..................................................................... 104

16. Resource Tabulations ............................................................................................. 105

16.1. Resource Tabulations by Domain .......................................................................... 106

16.2. Grade Tonnage Curves ........................................................................................... 107

16.2.1. Grade Tonnage Curves by Domain ....................................................................................... 109

17. Exploration Target Material .................................................................................... 111

18. Conclusions and Recommendations .................................................................... 112

19. Signature Page ........................................................................................................ 113


v

20. References ............................................................................................................... 114

Appendices .................................................................................................................... 115

Appendix 1: File Listing ........................................................................................................ 115

Appendix 2: Laboratory details ............................................................................................ 116

Appendix 3: Variogram Models ............................................................................................ 119

Appendix 4: JORC Checklist of Reporting Criteria ............................................................. 122

Section 1 Sampling Techniques and Data ............................................................................................ 122

Section 3 Estimation and Reporting of Mineral Resources ................................................................... 127


i

List of Figures

Figure 1 Locality of deposit in Namibia .............................................................................................................. 2 Figure 2 Omitiomire location and licence area .................................................................................................. 3 Figure 3 Cross section at line 3570 N ............................................................................................................... 5 Figure 4 Longitudinal section at line 803300 E, illustrating the plunge to the north .......................................... 5 Figure 5 Simplified geological map of the upper Black Nossob River area (after Kasch, 1986) showing location of the Ekuja Dome (taken from Steven et al, 2000) ............................................................................. 9 Figure 6 Coarse gained Chalcocite (silver colour) in NQ diamond drill core with brown epidote and black biotite ............................................................................................................................................................... 10 Figure 7 Rock type MGN - banded grey biotite gneiss and irregular bands of amphibolite ............................ 12 Figure 8 Downhole photologging (left) and 360º view of RC hole (right) ........................................................ 12 Figure 9 Section 3670N showing structures determined from downhole photography: fracture (red lines) and foliation (green lines) trace .............................................................................................................................. 13 Figure 10 Omitiomire drillhole plan with mineralised wireframes .................................................................... 15 Figure 11 IBML’s anticipated resource extension ........................................................................................... 16 Figure 12 EPL 3589: Soil geochemistry. "Warm" colours show elevated copper-in-soil, well developed within the Ekuja Dome. Omitiomire resource model outlined. ................................................................................... 17 Figure 13 Drillhole plan by drill type with mineralised wireframes ................................................................... 18 Figure 14 Reflex software showing the results of a survey ............................................................................. 20 Figure 15 Downhole optical camera system showing some results of a survey ............................................. 20 Figure 16 Downhole photography providing image, geological and structural information ............................. 21 Figure 17 Lithology examples as RC chips and core to aid logging ............................................................... 23 Figure 18 Handheld XRF being used on core ................................................................................................. 25 Figure 19 Handheld XRF versus laboratory ICP results ................................................................................. 26 Figure 20 Flow diagram of RC sample procedure ........................................................................................... 27 Figure 21 Core grinder used to shave the core ............................................................................................... 29 Figure 22 Core versus shavings plot ............................................................................................................... 29 Figure 23 Processing flowchart of samples submitted .................................................................................... 31 Figure 24 CRM AMIS0036............................................................................................................................... 34 Figure 25 CRM AMIS0072............................................................................................................................... 35 Figure 26 CRM AMIS0088............................................................................................................................... 35 Figure 27 CRM AMIS0118............................................................................................................................... 36 Figure 28 CRM AMIS0119............................................................................................................................... 36 Figure 29 Blank material .................................................................................................................................. 37 Figure 30 Scatter plot of laboratory pulp duplicates ........................................................................................ 38 Figure 31 Scatter plot of rig duplicates ............................................................................................................ 39 Figure 32 HARD plot of laboratory pulp and rig duplicates for Cu analysis .................................................... 39 Figure 33 CRM AMIS006 S analysis ............................................................................................................... 40 Figure 34 CRM AMIS0072 S analysis ............................................................................................................. 41 Figure 35 CRM AMIS0088 S analysis ............................................................................................................. 41 Figure 36 CRM AMIS0118 S analysis ............................................................................................................. 42 Figure 37 CRM AMIS0119 S analysis ............................................................................................................. 42 Figure 38 Blank material for S analysis ........................................................................................................... 43 Figure 39 Laboratory pulp duplicates scatter plot for S analysis ..................................................................... 44 Figure 40 Rig duplicates for S analysis ........................................................................................................... 45 Figure 41 HARD plot of original assays at primary laboratory vs duplicates with ALS external laboratory .... 46 Figure 42 Scatter plot of umpire laboratory checks ......................................................................................... 47 Figure 43 Percentage relative difference vs paired mean grade plot .............................................................. 48 Figure 44 HARD plot of original S% assays at primary laboratory vs duplicates with ALS external laboratory ......................................................................................................................................................................... 49 Figure 45 Scatter plot of umpire laboratory checks for S% ............................................................................. 50 Figure 46 Estimation domains and collar plan coloured by model year .......................................................... 55 Figure 47 Histogram of all samples within the wireframes .............................................................................. 57 Figure 48 Individual domain histograms .......................................................................................................... 58 Figure 49 Cumulative Frequency plot of all domains ...................................................................................... 59 Figure 50 S % sample histogram for mineralised zone ................................................................................... 60 Figure 51 Sample histogram of PC_DARK within the mineralised zone ......................................................... 61 Figure 52 Histograms by lithology within mineralised zone ............................................................................. 62


ii

Figure 53 Decluster Analysis for Domain 1, A Lens ........................................................................................ 64 Figure 54 Density box & whisker plot for Cu<0.25% ....................................................................................... 66 Figure 55 Density box & whisker plot for Cu>0.25% ....................................................................................... 66 Figure 56 Density box and whisker plot for oxide ............................................................................................ 67 Figure 57 Grade versus density for dark lithologies ........................................................................................ 67 Figure 58 Grade versus density for light lithologies ........................................................................................ 68 Figure 59 S ratio versus sample depth ............................................................................................................ 69 Figure 60 Variogram model for Cu % - Domain 1 A lens ................................................................................ 74 Figure 61 Variogram models for S % in horizontal plane and downhole directions ........................................ 77 Figure 62 Variogram models in the horizontal and downhole directions for PC_DARK ................................. 78 Figure 63 Number of sample determination plots for Domain 1 ...................................................................... 81 Figure 64 Number of samples determination for Domain 2............................................................................. 81 Figure 65 Number of samples determination for Domain 3............................................................................. 82 Figure 66 Number of samples determination for Domain 5............................................................................. 82 Figure 67 Number of samples determination for Domain 8............................................................................. 83 Figure 68 Histogram of slope of regression for Domain 2 ............................................................................... 84 Figure 69 Histogram of slope of regression for Domain 4 ............................................................................... 84 Figure 70 West-east cross section in southern area line 7582270 N .............................................................. 87 Figure 71 West-east cross section in northern central area line 7583570 N .................................................. 88 Figure 72 West-east cross section in central area line 7583240 N ................................................................. 89 Figure 73 North-south cross section line 803300 E ........................................................................................ 90 Figure 74 Grade slice validation plots for Domain 1 ........................................................................................ 92 Figure 75 Grade slice validation plots for Domain 2 ........................................................................................ 93 Figure 76 Grade slice validation plots for Domain 3 ........................................................................................ 94 Figure 77 Grade slice validation plots for Domain 4 ........................................................................................ 95 Figure 78 Domain 1: (left) model shown by SOR and Measured string in red; (right) model shown by classification category ...................................................................................................................................... 99 Figure 79 Domain 1: (left) model shown by SOR with Indicated (green) and Inferred strings (blue); (right) model coloured by classification category ..................................................................................................... 100 Figure 80 Domain 5: (left) model shown by SOR with Indicated (green) and Measured strings (red); (right) model coloured by classification category indicating area where the Measured has been extended........... 101 Figure 81 Domain 7: (left) model coloured by SOR with Inferred strings in blue; (right) model coloured by classification category .................................................................................................................................... 102 Figure 82 Grade tonnage curves of Measured and Indicated material ......................................................... 107 Figure 83 Grade tonnage curves for Measured, Indicated and Inferred material ......................................... 107 Figure 84 Total inventory: Measured, Indicated, Inferred and Exploration Target ........................................ 108 Figure 85 Domain 1 grade tonnage curves ................................................................................................... 109 Figure 86 Domain 2 grade tonnage curves ................................................................................................... 109 Figure 87 Domain 3 grade tonnage curves ................................................................................................... 110 Figure 88 Domain 4 grade tonnage curves ................................................................................................... 110


i

List of Tables

Table 1 Summary of drilling campaigns to date ................................................................................................ 7 Table 2 Omitiomire Resources as at April 2010 ................................................................................................ 8 Table 3 Omitiomire Resources as at October 2011 .......................................................................................... 8 Table 4 Omitiomire Resources as at August 2012 ............................................................................................ 8 Table 5 Mafic rock types .................................................................................................................................. 11 Table 6 Felsic rock types ................................................................................................................................. 11 Table 7 Summary of 2014 drillhole database .................................................................................................. 14 Table 8 Additional drillholes for 2014 .............................................................................................................. 14 Table 9 Drillholes surveyed with downhole camera ........................................................................................ 21 Table 10 Logged features ................................................................................................................................ 24 Table 11 Summary statistics of samples which have both handheld XRF as well as laboratory ICP results . 25 Table 12 Sample submission to the laboratories ............................................................................................ 28 Table 13 Sample preparation at the laboratory ............................................................................................... 30 Table 14 Description of sample analysis ......................................................................................................... 30 Table 15 CRM's used and the assigned two standard deviations ................................................................... 32 Table 16 Statistics of CRM performance ......................................................................................................... 34 Table 17 Statistics on CRM performance for S analysis ................................................................................. 40 Table 18 Summary of assay method at ALS ................................................................................................... 45 Table 19 Primary vs ALS laboratory of mean and CV ..................................................................................... 47 Table 20 Tables and fields within database .................................................................................................... 52 Table 21 BHIDs of the drill and log sheets photographed and during which period ....................................... 54 Table 22 Omitiomire mineralised domains compared with 2012 .................................................................... 56 Table 23 Percentage of waste samples per domain ....................................................................................... 57 Table 24 Drillhole sample statistics of Cu % ................................................................................................... 59 Table 25 Sample statistics of S % ................................................................................................................... 60 Table 26 PC_DARK statistics within mineralised zone ................................................................................... 61 Table 27 Cu % statistics by lithology within mineralised zone ........................................................................ 63 Table 28 Declustered sample means by domain ............................................................................................ 63 Table 29 Percentage of missing intervals in the domained drillhole file .......................................................... 65 Table 30 Density data statistics per lithology .................................................................................................. 65 Table 31 Bulk densities based on gas pycnometer means ............................................................................. 69 Table 32 Density determination expressed in metres – Mineralised Zone .................................................... 69 Table 33 Density determination expressed in metres – Non-Mineralised Zone............................................. 69 Table 34 Summary of key fields in the block model ........................................................................................ 70 Table 35 Datamine block model prototype ...................................................................................................... 70 Table 36 Estimation domains .......................................................................................................................... 71 Table 37 Search parameters for density estimation ........................................................................................ 72 Table 38 Experimental variogram parameters for 2014 variography .............................................................. 74 Table 39 Grade variogram models .................................................................................................................. 75 Table 40 2012 Cu % variogram models .......................................................................................................... 75 Table 41 Variogram quality .............................................................................................................................. 76 Table 42 Summary of variogram model for S % for 2014 and 2012 ............................................................... 77 Table 43 Variogram model for PC_DARK ....................................................................................................... 79 Table 44 Summary of kriging parameters for the CU% estimation for the 50 x 50 x 10 m blocks .................. 85 Table 45 Summary of kriging parameters for the CU % estimation for the 25 x 25 x 5 m blocks ................... 85 Table 46 Kriged vs sample mean grade comparison ...................................................................................... 91 Table 47 Interpolated density vs sample mean comparison ........................................................................... 96 Table 48 S% optimised estimation parameters ............................................................................................... 96 Table 49 Optimised kriging parameters for PC_DARK ................................................................................... 97 Table 50 Classification categories of PC_DARK ............................................................................................. 97 Table 51 Mean Slope of Regression by domain ............................................................................................. 98 Table 52 Model classification categories ....................................................................................................... 102 Table 53 Sampling to volume relationship by domain ................................................................................... 103 Table 54 Mean Slope of Regression by domain and classification field ....................................................... 103 Table 55 Criteria for Resource Classification .................................................... Error! Bookmark not defined.


ii

Table 56 Model comparison with previous model with no cut-off - ALL DOMAINS ...................................... 104 Table 57 Model comparison with previous model for Measure, Indicated and Inferred - ALL DOMAINS .... 104 Table 58 Omitiomire Measured and Indicated Resources ............................................................................ 105 Table 59 Omitiomire Inferred Resources ....................................................................................................... 105 Table 60 Omitiomire Measured, Indicated and Inferred Resources .............................................................. 105 Table 61 Omitiomire Indicated and Inferred Resources at 0.25 % ............................................................... 106 Table 62 Resources by domain ..................................................................................................................... 106 Table 63 Exploration Target material for Omitiomire grade and tonnage table ............................................ 111


1

1. Introduction

1.1. Background

This report covers work completed on the Mineral Resource Estimate “MRE” of the Omitiomire copper deposit, Namibia, in 2014. This work builds on previous studies completed by Bloy in 2012 and 2013. The last full MRE was completed in 2012 and more recently an oxide only MRE was completed in 2013.

1.2. Scope of Works

Craton Mining & Exploration (Pty) Ltd (“Craton”) approached Bloy to complete a MRE of the Omitiomire copper deposit, Namibia. The re-model was to include new drilling completed between mid-2012 and mid-2014 and an additional new target south west of the main deposit named Tiger. The scope of works was broadly as follows:

Review and validation of the wireframes (supplied by Craton)

Cu % estimation

S % estimation

Density model for the mineralised zones and the waste country rock

The estimation of ‘percentage dark material’ (PC_DARK), a geometallurgical indicator

Classification of the Resource Model

1.3. Sources of Information

All data and deposit information was provided by personnel from Craton. The drillhole database was provided in Excel spreadsheet format for the collars, surveys, assays, and lithology. The mineralised wireframes for ten domains were provided in Datamine format. The surveyed topography was provided in shape file format.

1.4. Site Visits

Michael Rohwer, Bloy Senior Consultant, has completed two site visits within the last two years. The first one was between 13-15th February 2012 and the second between 26-30th May 2014. Both visits were to Omitiomire Copper deposit site and the Craton head offices in Windhoek, Namibia. The purpose of the most recent visit was to ensure that documented procedures for the drilling, logging and data capture, assay QAQC and database verification processes were still in place. To observe the drilling and sampling procedures taking place in the field.


2

2. Property Description and Location

The project is situated northeast of Namibia’s capital, Windhoek (Figure 1). Omitiomire coordinates are 17°57’E, 21°49’S. The area is accessed from Windhoek via 140 km of bitumen and gravel roads.

Figure 1 Locality of deposit in Namibia

International Base Metals Limited (“IBML”) has established a wholly-owned Namibian-registered subsidiary company, Craton, as its operating entity in Namibia. The Omitiomire deposit is on the farm Omitiomire, within the exclusive prospecting licence EPL3589 as shown in Figure 2. The licence covers an area of 73 517 hectares and is currently valid until 25 April 2016 for the exploration of Base & Rare Metals and Precious Metals.


3

Figure 2 Omitiomire location and licence area


4

3. History

3.1. Project History

Copper occurrences in the Omitiomire area were first recognised from sparse malachite ‘float’. During the period 1975 to 1978, General Mining and Finance Corporation (“GenMin”) carried out a regional soil geochemical survey which showed widespread copper soil geochemical anomalies. Follow-up exploration by GenMin included 24 shallow percussion holes (BH1 – BH24) and three diamond drillholes (ON1 to ON3). In 1989, the Nossob River Mining Company drilled nine shallow percussion holes at Omitiomire (PH1 to PH9), and then contracted out the project to Erongo Mining and Exploration Company (“Erongo”), a subsidiary of Anglo American Corporation. Between 1992 and 1994, Erongo carried out extensive exploration. Geological mapping and detailed soil geochemical grids at Omitiomire and Barreshagen were followed by ground magnetic surveys, interpretation of government airborne magnetics and dipole-dipole Induced Polarisation (IP) resistivity surveys. At Omitiomire, Erongo drilled eight diamond cored holes (OED1 – OED8) on 200 m centres, and 17 shallow percussion holes (OEP1 – OEP17). One of the diamond drillholes (OED5) intersected 106 m at 0.47% Cu. In 1997, the exploration licence was granted to Kalahari Gold & Copper (Pty) Ltd (“Kalahari”). Kalahari carried out an interpretation of the previous drilling results. Straits Resources Limited (“Straits”) bought into the project in 1998 and drilled 13 shallow reverse circulation (RC) holes to test the up-dip extension of known mineralisation and to test for a shallow oxide or supergene-enriched zone (OMRC01 – OMRC13). Straits carried out five acid consumption tests which showed moderate acid consumption of 40 kg/t. A preliminary scoping study showed potential for 20 Mt grading 0.5% Cu at a cut-off grade of 0.2% Cu. By the turn of the century, about 5 800 m had been drilled in 74 drillholes. In 2005, Cheetah Minerals Exploration (Pty) Ltd (“Cheetah”) was awarded Reconnaissance Licence ERL 74 to interpret the regional data. On 25 April 2007, Cheetah was awarded five prospecting licences, which included the Omitiomire prospect on EPL 3589. In May 2007, Cheetah concluded an earn-in joint venture agreement with IBML. During August 2007, IBML registered Craton as its 100% owned Namibian subsidiary. After a year of intensive exploration by Craton, IBML offered Cheetah shares for 100% ownership of EPL 3589. On 13 June 2008, the Minister of Mines and Energy approved the transfer of EPL 3589 to Craton. Further drilling and initial Pre-feasibility studies (“PFS”) studies continued until the global financial crisis constrained cash flow. Initial metallurgical test work showed the potential for a profitable mining operation and beneficiation by means of DMS pre-concentration and production of a high-grade concentrate by flotation. With the improving market conditions during 2009, exploration drilling resumed and by the fourth quarter of 2009 Craton had completed a total of 53 403 m of drilling and commenced with a full PFS on the Omitiomire deposit. At a 0.25% Cu cut-off, Hellman and Schofield estimated a JORC-compliant resource of 117 million tonnes at 0.5% Cu; including 20% in the Indicated and 80% in the Inferred category. The PFS was completed in July 2010 and supports the 2008 mining and beneficiation methods; by means of open cast mining, crushing, dense-medium separation, milling and flotation.


5

3.2. Exploration and Development

3.2.1. Resource Extension Drilling Campaign

A reinterpretation in 2011 showed that the deposit consists of a number of stacked parallel tabular bodies (“lenses”) which partly merge, illustrated in Figure 3 and Figure 4. The drilling programme from mid-2011 to mid-2012 had the objective of demonstrating the potential for a resource of at least 1 million tonnes of contained copper metal. Drillholes in the northeast intersected thick zones of copper mineralisation, including the previously-unknown C Lens in the northeast of the deposit. Further drilling extended the A Lens and B Lens towards the north. The lenses have good continuity along a known strike extent of over 3 km.

Figure 3 Cross section at line 3570 N

Figure 4 Longitudinal section at line 803300 E, illustrating the plunge to the north

The discovery of the C Lens and several infill drillholes completed during 2010 were considered to be sufficient additional data for an updated resource estimation. Although the drillhole spacing in the northeast is too broad to assign a JORC compliant resource status, this drilling added substantially to the resource potential. The MRE, completed by Bloy in October 2011, showed an Indicated + Inferred resource of 123 million tonnes (Mt) at 0.53% Cu (648,000 tonnes copper metal) at a 0.25% Cu cut-off and potential for an additional 600 000 tonnes of copper metal at a 0.25% Cu cut-off.


6

During 2012, drilling aimed at confirming and further extending the potential resource by means of:

Diamond tails on previous shallow reverse circulation (RC) drill holes to test for deeper copper (especially the C Lens) below the identified resource;

Additional widely-spaced drilling (minimum spacing of 200 m x 400 m) with RC or percussion pre-collars and diamond cored tails to test the northern and north-eastern extensions of the deposit;

RC drilling of targets west of Omitiomire discovered the Mamba Lens in a narrow zone at shallow depths.

The resource estimation, completed by Bloy in September 2012, showed an Indicated + Inferred resource of 136 million tonnes (Mt) at 0.53% Cu (~712,000 tonnes copper metal) at a 0.25% Cu cut-off and potential for an additional >500 000 tonnes of copper metal at a 0.25% Cu cut-off. Drilling continued during 2013 and 2014 aimed at:

Identifying additional resources near the current resource. Drilling identified a low grade resource at the Tiger prospect;

Infill drilling (spacing of 25 x 25 m and at 50 x 50 m) was completed during 2014 on the margins of near-surface oxide resources.

3.2.2. Metallurgical Drilling Campaign

Two phases of drilling during late 2012 aimed at collecting metallurgical samples for test work:

Two short diamond drill holes (HQ core) were drilled for the purpose of oxide processing test work;

RC pre-collars and PQ tails through the ore zone were drilled to collect sample for sulphide processing test work.

All metallurgical holes were cut and sampled on site. The analytical results are included in the database, using the same procedure as other diamond drill holes.

3.2.3. Shallow Oxide Resource

During 2013 IBML embarked on the Phase 1 Oxide Definitive Feasibility Study. For this purpose, infill drilling (spacing of 25 x 25 m) was required for a detailed Resource Model to a depth of 50 m. Based on the Resource Model, three pits were designed with a total reserve estimated at 3.14 Mt at 0.93% Cu (Basil Read Matomo, 2013).


7

3.2.4. Exploration drilling campaigns

The table below summarises the drilling campaigns to date. It includes drillholes that were not used in the resource estimated due to unreliable assays results, but were used for their geological information in constructing the mineralised wireframes (see section 10.3).

Table 1 Summary of drilling campaigns to date

Year Drill Campaign / Description DD (m) RC (m) RAB (m) PERC (m) TOTAL (m)

1976 Pre-Craton

889 889

1992 Pre-Craton 1 336

755 2 091

1993 Pre-Craton 224

986 1 210

1998 Pre-Craton

991

991

2007 Craton: Pre-Financial Crisis 737 9485

10 222

2008 Craton: Pre-Financial Crisis 2 063 21 258

23 321

2009 Craton 1 484 6 868 832

9 184

2010 Craton: 2010 Oxide Infill

2 094

2 094

2010 Craton: 2010 Prospectus

4 294

4 294

2011 Craton: Resource Extension 5 753 6 114

1 676 13 543

2012 Craton: Resource Extension 4 478 4 729

9 207

2012 Craton: Metallurgical 1 117 1 058 2 175

2013 Craton: Resource Oxide 4 449 4 339

2014 Craton: Resource and Extension 12 102 12 102

GRAND TOTAL 17 192 73 442 832 4 306 95 772


8

3.3. Historic Resource Estimates

Historic resource estimates of the Omitiomire copper deposit include:

April 2010 - Hellman & Schofield

October 2011 – Bloy by C. Nicholls

August 2012 - Bloy by C. Nicholls & M. Rohwer

November 2013 - Bloy by C. Nicholls (oxide only not a full Resource Model of deposit) The MRE undertaken by Hellman & Schofield in 2010 is summarised below.

Table 2 Omitiomire Resources as at April 2010

Cut-off %

Indicated Inferred Total

Tonnes (t) Grade

(%) Metal

(t) Tonnes (t)

Grade (%)

Metal (t)

Tonnes (t) Grade

(%) Metal

(t)

0.25 24 458 700 0.47 114 711 92 298 208 0.5 465 183 116 756 908 0.5 579 114

The MRE undertaken by Bloy in October 2011 is summarised in the Table 3 below. In addition to the stated resources, Exploration Target material was estimated and at a cut-off of 0.25% Cu it totalled 95.6 Mt, at a grade of 0.59% and 565 Kt of contained metal.

Table 3 Omitiomire Resources as at October 2011

Cut-off %


Tonnes (t) Grade

(%) Metal

(t) Tonnes (t)

Grade (%)

Metal (t)

Tonnes (t) Grade

(%) Metal

(t)

0.25 92 255 826 0.51 472 814 31 133 877 0.56 175 247 123 389 704 0.53 648 061

The most recent full MRE for the Omitiomire deposit was undertaken by C. Nicholls of Bloy in August 2012. The resources are summarised in Table 4 below. Exploration Target material at a cut-off grade of 0.25% Cu of 94.5 Mt at 0.5% Cu for 516 Kt of contained Cu metal was reported in addition to the Omitiomire Mineral Resource.

Table 4 Omitiomire Resources as at August 2012

Cut-off %


Tonnes (t) Grade

(%) Metal

(t) Tonnes (t)

Grade (%)

Metal (t)

Tonnes (t) Grade

(%) Metal

(t)

0.25 97 012 867 0.51 497 333 38 511 158 0.56 214 834 135 524 025 0.53 712 168

An interim MRE for the oxides was carried out in November 2013 by C. Nicholls of Bloy (Nicholls, Craton Omitiomire Oxide Resource Model, 2013). This estimate effectively updated for targeted areas with close spaced drilling (25 x 25 m) within the oxide portion of the deposit. The selected areas were potential shallow pit locations. This model allowed the classification of some Measured material (at a cut-off grade of 0.25% of 1.9 Mt at 0.81% for 15 Kt of metal) as well as adding to the Indicated inventory. This formed the basis for the classification of the 2014 MRE. The estimate was for part of the deposit only and is not stated here as it does not encompass the whole deposit.

3.4. Previous Production

There has been no production to date at this deposit.


9

4. Geology

4.1. Geological Setting

The Omitiomire copper deposit is hosted in leuco-gneiss with inter-bedded dark biotite schist and amphibolite. These rocks occur in an inlier known as the Ekuja Dome which covers an area of approximately 15 km x 12 km (Figure 5). Rock outcrops in these areas are limited, mainly to the areas along the Nossob River where geological mapping has been carried out. Much of both the regional and deposit geology has therefore been interpreted from geophysical and drilling data.

Figure 5 Simplified geological map of the upper Black Nossob River area (after Kasch, 1986) showing location of

the Ekuja Dome (taken from Steven et al, 2000)

The regional geology consists of the series of older dome structures such as the Ekuja Dome, a structurally-controlled “window” of Kibaran-age rocks flanked by younger 900 million years (“Ma”) to 450 Ma pan-African rocks rocks of the Damara Orogen. Zircons in the Kibaran gneisses of the dome yield U-Pb dates ranging between 1,063 and 1,115 Ma (Steven et al, 2000). Craton has engaged consultants in geophysics and in structural geology to contribute to the regional understanding of the area. Drilling and geophysical work, especially drill core and downhole photographic logging, has shown the gneisses to be highly deformed, sheared, folded and faulted. Metamorphism of the rocks in the domes is at the upper amphibolite facies. A series of gneiss, calc-silicate rocks, amphibolite, iron-rich rocks and glassy quartzite occurs on a regional scale near some of the Kibaran domes. This sequence is possibly older (±1,800 Ma) and therefore thrusted over the Kibaran domes and the Damaran strata.


10

4.2. Deposit Geology

The deposit geology consists of two main packages: Firstly, mafic rocks, which host the copper, consist mainly of quartz, plagioclase, biotite and amphibole, and are usually inter-banded with more felsic layers. Banding is usually on a centimetre to metre scale, but amphibolite bands can be more massive and attain thicknesses of tens of metres. Epidote (an unusual chromium-rich variety) and, to a lesser extent, magnetite are associated with the copper mineralisation. Secondly, the surrounding leuco-gneisses are usually unmineralised, and carry quartz, plagioclase, variable amounts of biotite and trace amounts of garnet and sphene. Intrusive tonalite and minor late stage pegmatite also occur. The copper-bearing mafic schist is interpreted as metamorphosed basaltic andesite and the barren felsic gneiss as metamorphosed dacite and rhyolite. The mafic banding, which can be on a scale of centimetres or less, is interpreted as representing meta-sedimentary layering, possibly of a tuffaceous origin. The massive amphibolite and massive felsic gneiss may have been a mixture of intrusions, lavas and tuffs. The copper mineralisation at Omitiomire is unusual in that chalcocite dominates, commonly with associated magnetite and only very local bornite. Chalcocite is largely disseminated in the mafic rocks. Zones of higher grade contain coarse blebs which postdate and over print foliation in biotite-amphibole schist. The fact that chalcocite overprints foliation implies remobilisation / emplacement of copper during the late Damaran orogeny. Near surface and down to about 30 m depth, the mineralised zone has been partially oxidised to malachite, chrysocolla and native copper. Drilling has shown about 15% of the copper to occur as “oxide ore”. Copper oxides dominate in the upper parts of the deposit, but also in “weathered” zones associated with faults and fractures down to depths of over 200 m.

Figure 6 Coarse gained Chalcocite (silver colour) in NQ diamond drill core with brown epidote and black biotite

Multi-element, low level geochemical analyses have shown no deleterious or hazardous elements to occur. Pyrite and chalcopyrite are very minor, appearing in just a few drillholes. In the north of the deposit, the highest copper grades occur immediately below a main thrust structure between upper, barren white gneiss and the mineralised schist and amphibolite below. The lower mineralisation boundary is more diffuse, and deeper, lower grade copper zones have been further drill-tested in places. In the south, multiple copper zones, caused by structural complexity, have been intersected in most holes. Multiple mineralised mafic schist bands, usually in the centimetre to metre thickness range, are separated by essentially unmineralised leuco-gneiss bands. Whilst the mafic rocks have a density of over 2.8 g/cm3 and


11

a hardness of less than 150 MPa, the leucocratic rocks have a density of less than 2.65 g/cm3 and a hardness of over 200 MPa. These physical aspects are important in the recovery of copper from the ore. The deposit geometry of the mineralised zone at Omitiomire is broadly sheet-like, striking north-south and dipping moderately to the east. Repetition of the package by south- and east-verging Z folds and possibly thrusting has given mineralised intersections of over 100 m thick. Late, sub-vertical brittle reverse faulting of probably Damaran age has caused displacement of the mineralised zone and resulted in narrow, but deep adjacent oxidation. Rock types can be broadly separated into dark, mafic rocks, which host copper and light felsic rocks, which are largely barren. A description of the rock types are given in Table 5 and Table 6 below.

Table 5 Mafic rock types

Table 6 Felsic rock types


12

Figure 7 Rock type MGN - banded grey biotite gneiss and irregular bands of amphibolite

The geometry of the Omitiomire copper deposit is relatively simple in the north, while structural complexity is known in the south where shearing, folding and intrusive rocks complicate the interpretation. For a better understanding of the geological complexities, downhole digital photography was carried out on 72 RC drillholes, Figure 8. Detailed structural analysis of this data has proven invaluable in unravelling structural complexity, Figure 9.

Figure 8 Downhole photologging (left) and 360º view of RC hole (right)


13

Figure 9 Section 3670N showing structures determined from downhole photography: fracture (red lines) and

foliation (green lines) trace


14

5. Drilling

5.1. Drilling Campaigns

The total drilling database used in this resource modelling exercise is detailed in Table 7. The OEP coded drillholes were omitted from the drillhole file for the modelling due to being percussive holes with low quality assays and are not included in the tables below. They were however used for their geological information in the construction of the mineralised wireframes. The Drill Type coding in the following tables is taken from the coding used in the drillhole database.

Table 7 Summary of 2014 drillhole database

Drill Type No. holes Drilled (m) Assayed (m)

DD 45 4 662 1 803

PERC+DD 733 62 090 60 428

RAB 50 1 294 1 294

RC 9 3 547 2 236

RC+DD 67 21 541 14 316

Total 904 93 133 80 076

The new drillholes since the previous modelling exercise in 2012 (om_201208_model_final (Nicholls & Rohwer, Omitiomire Resource Model, 2012)) are detailed in Table 8. This totals some 18 700 m and 98 % of this metreage was assayed for Cu.

Table 8 Additional drillholes for 2014

Drill Type No. holes Drilled (m) Assayed (m)

DD 2 163 23

PERC+DD 316 16 753 16 654

RAB 0 - -

RC 0 - -

RC+DD 12 1 788 1 657

Total 330 18 704 18 334

The additional drilling for the 2014 model update, coloured red, is outlined in Figure 10 below. The main areas of target were:

New target Tiger (pink wireframe south west of main deposit). The drilling is at 50 m across strike and 100 m along strike. The extent of the drilling is 250 x 400 m.

Infill drilling to 25 x 25 m in central area targeting oxides; area covered is approximately 150 x 700 m. The domains affected are A and T lens.

Infill drilling in northern part of Bruce Terrace lens to 25 x 25 m. Infilled area where previously access was restricted.

Infill drilling of Bruce lens in north to 50 x 50 m. Area covered was 100 x 200 m.

5 drillholes north end of Mamba - effectively closing off the mineralisation.

Infill drilling of Kaya lens in two areas. Drilling was part of oxide infill campaign in 2013. The drilling in the two areas are to 25 x 25 m.

A lens infill drilling to 25 x 25 m in small area north of central area targeting oxides; area covered is 50 x 300 m.


15

Figure 10 Omitiomire drillhole plan with mineralised wireframes

5.2. Discovery Potential

In 2012, IBML anticipated that further drilling would expand the Omitiomire resource to the northeast, as illustrated in Figure 11. This target remains untested.

New target: Tiger 50 x 100 m drilling

Kaya infill drilling to 25 x 25 m

Bruce lens infill drilling to 50 x 50 m

Mamba: Closed off

mineralisation

Shallow oxide infill to 25 x 25 m

A lens: infill to 25 x 25 m

Bruce Terrace

lens: infill to 25 x 25 m


16

Figure 11 IBML’s anticipated resource extension

The company has carried out extensive soil geochemical surveys within EPL 3589. These show the Ekuja Dome as being regionally anomalous in copper (Figure 12). Shallow RAB drilling has demonstrated the presence of copper associated with many of the anomalies but there has been little detailed follow-up drilling to date. Collectively, the geochemical anomalies and the RAB drill intersections indicate that the Ekuja Dome is a copper-rich geological entity, with potential for the discovery of additional resources within trucking distance of the Omitiomire deposit. Limited RC drilling on thes targets has intersected shallow zones with modest grade.


17

Figure 12 EPL 3589: Soil geochemistry. "Warm" colours show elevated copper-in-soil, well developed within the

Ekuja Dome. Omitiomire resource model outlined.

5.3. Drilling Types

5.3.1. Drill Types

The types of drillholes used in this estimation are diamond (DD), reverse circulation (RC), percussive (PERC), and rotary air blast (RAB). The percussive drilling was used to pre-collar the diamond drilling which intersected the mineralised zone. The percussive part of the drillhole was assayed but did not contain significant assays. The DD was sampled and assayed in the mineralised zone only. The RC+DD drillholes were drilled with the RC as deep as possible and the remainder of the hole would have been drilled with diamond. The entire RC drilling portion was assayed whereas the DD was only sampled and assayed in the mineralised zone. The RAB were used mainly to delineate two targets Bruce Terrace and Mamba. These targets were subsequently drilled with RC. The RAB constitutes < 1.5 % of the database used in the estimation.


18

Figure 13 Drillhole plan by drill type with mineralised wireframes

5.3.2. Drill Diameters

Diamond drilling was performed with wire-line drill rigs either by drilling from surface with HQ through the weathered portion, casing and completing the hole with NQ or by a RC pre-collar with diamond (NQ) tail. The RC drilling was completed with conventional RC drill rigs, using 950 to 1100 psi compressors. Hole diameters varied from 134 to 119 mm, depending on downhole equipment used and the progressive wear on the bits. Bit diameter data is available for most of the drillholes, but not all and the average of the holes where the bit diameter was recorded is 128 mm.


19

5.3.3. Drilling Type Comparison

The vast majority of new drillholes are RC (Table 8) therefore the drilling comparison was not repeated. For results of the previous study in 2012 refer to the report (Nicholls & Rohwer, Omitiomire Resource Model, 2012).

5.4. Drill Orientation

The proportion of drillholes that are vertical is approximately 97%, the remaining 3% were angled at either 60º or 70º and were either orientated in the east or west direction. The stratigraphy and associated mineralised horizons are generally nearly flat-lying or dipping at low angle. Therefore a vertical drilling orientation satisfactorily reflects thicknesses of intersections and structure.

5.5. Drilling Quality

The intersected lithologies are competent in nature and the drilling contractor’s ability is reflected by the neatness at the drill site. Recovery is measured against depth during the logging. No scouring patterns or rounded core ends are evident on the core. Core generally needs to be broken on site to fit into the 1 m core trays. The measured core recovery within the mineralised zones is excellent at 98 %. Within the top 5 m the recovery is lower at 74%, whilst below 5 m the recovery is just under 99%. The recoveries for the core have not been repeated due to the low number of metres drilled therefore the recovery is not expected to change by much. The RC chip sample recoveries are recorded as part of the logging procedures. This is carried out by weighing the entire metre sample and comparing it to a theoretical weight (πr2h x density). If the difference is significant, the drilling process is halted and queried for a reason until a satisfactory sample weight is again achieved. The RC chip recovery is calculated using the density measured from the pycnometer where taken, else the density assigned to the interval based on the principles outlined in section 12.2.6. Within the mineralised zone, the chip recovery is 99% in the top 5 m and 98 % below. The core and to a much lesser extent the chip recoveries are lower in the top 5 m due to the presence of overburden or soil, which does not pose a significant risk in the estimate. No checks of the relationship between grade and sample recovery, or any sample bias due to loss/gain of fine/coarse material have been confirmed.

5.6. Survey Control

5.6.1. Collars

A contracted professional land surveyor from African Geomatics, conducts regular surveys of batches of completed holes during which the exact drill-hole locations are captured using a differential GPS. No certification from the land surveyor has been provided. Several drill-locations were verified by checking the co-ordinates displayed on the paper-hardcopy drill or logging sheets located within the geology office on site, and looking for the corresponding BHID in the field, at the reflected co-ordinates. In total 776 drillholes of the 924 drillholes used for resource modelling purposes were surveyed using DGPS; 38 historical drillholes had their elevations generated by Shuttle Radar Topography Mission (SRTM) technology; 51 drillholes had their elevations generated from the LIDAR survey flown; and the remaining 59 were captured with handheld GPS.

5.6.2. Downhole


20

Two forms of downhole survey techniques have been made use of in order to establish the deviation of the holes. 262 holes were surveyed using Reflex multi shot tool and 122 holes were surveyed using a downhole optical camera system. A typical Reflex multi shot survey would be set to obtain readings on average around every 30 metres whereas the optical system produces a reading every centimetre. Only a reading every 10 metres would have been extracted from the data set for downhole survey purposes. Most holes less than 100 metres have not been surveyed and planned dip and azimuth at zero metres were introduced into the survey table of the database.

Figure 14 Reflex software showing the results of a survey

As the results of the azimuth are magnetic, the declination of the Omitiomire area would need to be subtracted from the magnetic reading, this declination was established to be 12°.33 in 2007 and has moved to 11°.45 in 2012 and to 11°.20 in 2014, this shift is not reflected in the holes drilled over time though.

Figure 15 Downhole optical camera system showing some results of a survey

The tilt column in the downhole optical camera system results table reflects the dip of the drillhole which would be subtracted from 90° and the negative sign would be introduced as the standard for the Omitiomire database uses -90° as a vertical hole. There are a total of 2 775 survey readings in the current database for both types of surveys completed at Omitiomire. In addition to obtaining deviation type data the camera system also produces a continuous all-round photograph which provides a permanent record of the geological and structural characteristics of the wall of the hole (Figure 16). A total of 13 786.32 m of RC drilling have been surveyed with the downhole optical camera system. Table 9 below lists the drillholes which have been surveyed with the downhole camera system and the total amount of metres surveyed per drillhole.


21

Table 9 Drillholes surveyed with downhole camera

BHID Metres BHID Metres BHID Metres BHID Metres BHID Metres BHID Metres

ORC102 106.32 ORC157 131.48 ORC208 119.39 ORC291 102.75 ORC491 102.46 ORC132 62.5

ORC108 73.98 ORC158 119.68 ORC209 71.54 ORC292 99.13 ORC521 96.5 ORC213 180




ORC121 156.09 ORC162 89.54 ORC251 75 ORC297 182.61 ORC533 163.21 ORC891 60







ORC133 59.26 ORC178 215.8 ORC276 63.16 ORC452 127.28 ORC547 140.68





ORC145 18.82 ORC203 203.34 ORC284 63 ORC459 191.85 ORC609 35.95




Figure 16 Downhole photography providing image, geological and structural information

5.6.3. Topographic Control

The DGPS survey was based on Namibia's Schwarzeck coordinate system, as well as on the ITRF2000, epoch 2005.0, which is the (WGS84) reference system of Namibia’s Zero Order Geodetic Network. The


22

height system of the Schwarzeck datum is based on Mean Sea Level heights, while the height system of the ITRF2000 is a purely ellipsoidal height system on the WGS84 ellipsoid. One permanent reference point is established at the entrance gate to the farm. This permanent reference point is a 16mm iron peg in a 200mm PVC pipe in concrete, with an aluminium name tag ‘CRATON – OMIT – ‘. The coordinates of this survey station are: Easting 802941.167; Northing 7582891.898; Upping 1689.449 (ITRF UTM Zone 33) Y -96287.551; X -18368.548; Height 1659.668 (Schwarzeck Lo.22/17).


23

6. Geological Logging

Standard pre-drilling produced drill sheets are used as part of the logging procedures to capture drilling related information including the geological information. Prior to drilling the drill-log, logging sheets and sample packaging is prepared. To maintain consistency during logging, examples of all the lithologies likely to be encountered at Omitiomire are available for comparison both as RC chip samples and core (Figure 17). The entire process of logging and sampling a single drillhole is supervised from start to finish by one geologist, to maintain consistency. It should be noted that Craton replaced a drill contractor after spurious drill depths were being reported, subsequently all holes drilled by this contractor were entirely re-logged.

Figure 17 Lithology examples as RC chips and core to aid logging


24

The fields that are logged are listed in Table 10 below. The logging comprises a mixture of qualitative, quantitative and semi-quantitative features.

Table 10 Logged features

Category Feature Core Chips Data Type

Geotechnical

RQD Quantitative

Fractures/m Quantitative

Hardness Semi-Quantitative

Geology

Lithology Qualitative

Alteration Qualitative

Clay Qualitative

Oxidation Semi-Quantitative

% Dark Semi-Quantitative

Colour Qualitative

Mineralisation

Chalcocite Semi-Quantitative

Malachite Semi-Quantitative

Chrysocolla Semi-Quantitative

Magnetite Semi-Quantitative

Epidote Semi-Quantitative

Structure Type and angle Quantitative

Quality Recovery Quantitative

The logged fields that have been pertinent to this resource estimation have been the % dark material and the lithology. Though a geological model was not constructed for this evaluation, the logged lithology was used to help define the mineralised envelopes.

The “% Dark” logging is based on the fact that mineralisation is associated with the darker lithologies, which also generally have higher densities. The density will enable a degree of separation of the waste and ore in the processing plant by Dense Medium Separation (DMS). By logging and interpolating % Dark, the resulting model will have some form of geometallurgical classification that may assist in planning. Note that the deeper drillholes, which are core, do not have this field logged and therefore the % dark model will have less reliability at depth.

6.1. Density Determination

Gas pycnometry was used to measure the specific gravity of the drill sample pulp (already milled) materials. This technique uses gas displacement to measure volume (and hence density). The sample to be measured is sealed in the instrument compartment of known volume, helium gas is admitted, and then expanded into another compartment. The pressure, before and after expansion, is measured and used to calculate the sample volume. Dividing this volume into the sample weight gives the gas displacement density or specific gravity (SG) of the material. The value is considered representative of the full sample interval. 7 513 samples were measured throughout the deposit using this method of determination. While density determination by gas pycnometer does not take porosity into account, therefore restricting its suitability for weathered samples, Hellman & Schofield argued that most samples at Omitiomire are from solid, metamorphic rocks, and thus porosity should not be considered a factor in fresh rock (Hellman & Schofield Pty Ltd, 2010). Several tests were conducted by Hellman & Schofield using comparative methods of density determination to substantiate the application of gas pycnometry as the preferred method. Outside of statistical validation included in latter sections of the report, Bloy have not conducted any further verification of the methodologies of sample density determination.


25

7. Sampling Methods

7.1. Sub-sampling Description

7.1.1. Diamond sampling

The diamond core is received at the geological camp in metal core trays. At the camp the core recovery, geotechnical measurements, lithology and mineralisation are recorded. Only what is determined as the mineralised zone will be sent for assaying. The samples are selected based on lithology and visual grade, which is verified from a handheld XRF (Figure 18). Mineralisation corresponds exclusively with the darker lithologies and can be associated with shear-type deformation, thus variable sample lengths occur. The core is sawn in half and half of the core is submitted for assay. The core is orientated with an orientation line so that top and bottom cannot be misidentified and the southern portion of the core is sampled throughout.

Figure 18 Handheld XRF being used on core

Pre-screening of mineralised intervals using a handheld XRF, presents a convenient and cost- and time-effective way of validating the suitability of sample intervals selected for laboratory analysis. While these sampling intervals are selected visually by the on-site geologist according to his/her geological interpretation of the deposit, the use of the handheld XRF provides a means checking for possible misinterpretation which could lead to either under sampling or oversampling. The basic statistics in Table 11 as well as the comparative assay vs XRF plot (Figure 19) show that there is considerable low bias in the XRF.

Table 11 Summary statistics of samples which have both handheld XRF as well as laboratory ICP results

METHOD n Minimum Maximum Mean CV

FIELD XRF 5 483 0.00 11.92 0.28 1.75

LAB ICP 5 483 0.00 11.60 0.42 1.49


26

Figure 19 Handheld XRF versus laboratory ICP results

Although the XRF reads low, there is no risk that mineralisation would be missed as mineralised intersections were bracketed by additional sampling.

7.1.2. RC sampling

A summary of the RC sampling procedure is in Figure 20. Dry 1 m RC samples are split using a large riffle splitter. One split is then re-riffled to a 1/16th to produce an “A” and a “B” sample. “B” samples are stored while “A” samples a split again to produce a 1/32 fraction which is packaged and sent to the labs for assay if selected. At the drill site a sub-sample is washed and screened and the coarse fraction is examined by the site geologist, who records lithological and mineralogical details. The fine fraction is panned and the heavy portion examined for dense minerals including chalcocite. All of these samples are stored in chip trays. This method provides a semi-quantitative estimate of copper grade prior to analysis. The entire field sample handling procedure is closely monitored by Craton’s geologists. After sample preparation the copper content of the pulp is determined onsite by internal XRF analysis. Following the receipt of the XRF results, mineralised intervals including cut-off samples above and below the mineralised intersections are selected to be sent for ICP analysis at the laboratory.


27

Figure 20 Flow diagram of RC sample procedure

7.2. Sampling Quality

The RC sampling was observed whilst on site and noted that the procedure was followed exactly. Two observations were:

1. When the initial sample from the cyclone is split, it is poured through a large riffle splitter from the side rather than from the front. However, considering that the initial sample weighs on average 30kg, it is not ergonomically viable to pour the sample from the bag into the splitter while leaning over the underlying sampling pan.

2. When the sample is split for the second time, a smaller riffle splitter is used along with

accompanying smaller sample pans. On occasion, as the half sample is poured into the splitter, very small amounts of the sample are occasionally lost from the edges where the larger pan breadth exceeds the breadth of the smaller splitter.

However, considering the thickness of the intersections and the associated volumes of sample at this stage (16 kg split to 8 kg), the spilling of no more than half a cup full is deemed to be of little significance. The risk of losing critical sample or biasing the sample in any way is in this case very low.

7.3. Sample Storage

Logged and remaining sampled core is moved to and stored within a shaded and designated storage area. The trays are stacked by hole number to allow for easy reference while reducing surrounding activity and thus preserving the integrity of the core. Core samples are tagged and bagged for laboratory submission in standard thick plastic sampling bags and a corresponding tag is placed into the core-tray to represent the removed half core sample. These plastic sample bags are of such a nature that they are resistant to everyday wear-and-tear and will also retain fine, dust-sized particles. The bags are sealed with a “cable-


28

tie”, several bagged samples are then bagged together within larger “poly-weave” sacks as a batch and temporarily stored while awaiting transport and submission to the labs.

8. Sample Assaying

8.1. Analytical Laboratories

Over the last 7 years of developing the copper deposit at Omitiomire, five accredited laboratories have been made use of. Initially RC and diamond samples were sent to the Genalysis sample preparation facility in Johannesburg for XRF where semi-quantative analysis was conducted. From these results it was decided which samples were to be analysed using ICP-OES at the Genalysis Laboratory facility in Perth, Australia. During 2008 the backlog of the Perth laboratory was such that an amount of the samples submitted there were forwarded to the Genalysis/Intertek laboratory in Jakarta. The third laboratory that was made use of was Setpoint in South Africa where a similar approach using pressed pellet XRF technology was made use of to determine which samples need to be further analysed using ICP-OES. Bureau Veritas opened a laboratory in Swakopmund, Namibia and all samples from the project drilled since October 2010 have been sent to the laboratory for ICP-OES analysis. As Bureau Veritas is only a recently established laboratory, accreditation is supplied. ALS Global (formally ALS Chemex) has been used as the external check laboratory.

Table 12 Sample submission to the laboratories

Laboratory No. samples submitted

Genalysis, Perth, Australia 2 654

Genalysis/Intertek, Jakarta, Indonesia 2 694

Setpoint, Johannesburg, South Africa 3 931

Bureau Veritas, Swakopmund, Namibia 13 122

All laboratory addresses and the accreditation certificate for Bureau Veritas are located in the Appendix 2.

8.2. Sample Preparation

8.2.1. Diamond sampling

Wet and dry core photos are taken before the core gets cut and are available for all diamond drillholes. Once logging has been completed whole core from mineralised zones are cut in half with a diamond blade core cutter. Half of the cut core remains in the core tray and the other half sampled at the discretion of the geologist, labelled, bagged and dispatched to the laboratory. A second method of sampling diamond core that has been made use of with 10 diamond holes (ORC319 to ORC328) is with a core grinder. This involves placing the whole core onto the grinding tray and ±5 mm gets shaved off along the length of the core by a heavy-duty diamond blade (Figure 21). Approximately 200 to 600 g of core shavings are generated. The shavings are then collected for analysis and the remaining core placed back into the core tray. As this was the first time using this method both the shavings and remaining core from these holes, amounting to 226 samples (113 core, 113 shavings) were sent for analysis.


29

Figure 21 Core grinder used to shave the core

A comparison was made of the results received and the shavings were shown to be 10 % higher than the whole core assays. Of the results received there were a number of obvious sample swaps and where the core was very broken this made the sampling very difficult and some of the results did not compare well. When the sample swaps and the broken core samples were removed the difference between the two methods reduced to 3.9 %, where the shavings were higher. The scatter plot of the results excluding the sample swaps and broken core are in Figure 22 below. Based on these findings the core shaving method would not be used for broken core.

Figure 22 Core versus shavings plot

8.2.2. RC sampling

After sample preparation the copper content of the pulp is determined onsite by internal XRF analysis. Following the receipt of the XRF results, mineralised intervals including cut-off samples above and below the mineralised intersections are selected and sent for ICP analysis. The ICP sample results represent the final copper analysis of the sample used in resource evaluation. The XRF analysis is considered preliminary and not used in the resource estimation except at low levels.


30

From the same pulp samples, 10% of all samples above 0.1% copper are sent to ALS Chemex’s laboratory in Johannesburg as the ‘C’ check sample. For every ‘C’ sample greater than 0.25% copper, a ‘D’ sample is prepared and analysed for Gold, Platinum and Palladium. Analyses of the size fractions of 12 samples of varying grade and lithologies indicates that on average 89% of the sample is <2 mm. The implication of the high percentage of fines is that after the riffling process, a 1 kg sample is representative of the original ±32 kg sample. Analysis of the size fractions of 12 samples shows that the higher grade samples have more copper in the -2000 to +500 size fractions. This is consistent with visual observations that the higher grades contain coarse chalcocite. The sample preparation of the various laboratories used in the past and including the current laboratory is summarised in Table 13.

Table 13 Sample preparation at the laboratory

Laboratory Milling Pulp Size Fraction Sampling Apparatus Sampling Procedure

Genalysis – Perth LM5 75 µm Chrome-steel bowl Scoop from bowl

Set Point - Mokopane LM2 106 µm Chrome-steel bowl Scoop from bowl

Bureau Veritas - Swakopmund LM2 75 µm Standard steel bowl Scoop from bowl

8.3. Analytical Procedures

8.3.1. Previous Laboratories

Prior to the October 2010 drilling phase all ‘A’ samples were sent to Genalysis, Intertek and Setpoint laboratories. All samples since October 2010 have been sent to Bureau Veritas laboratory in Swakopmund and it is likely that all future samples will be sent there. Table 14 summarises the assay method for Bureau Veritas and the previous laboratories used. Set Point used Aqua Regia as the leaching method which requires a larger analyte sample.

Table 14 Description of sample analysis

Laboratory Analyte Sample Size Leaching Method ICP Method Detection Limit

Genalysis – Perth 0.2 g Four Acid ICP-OES 1 ppm Cu

Genalysis/Intertek - Jakarta 0.5 g Four Acid ICP-OES 2 ppm Cu

Set Point 2 g Aqua Regia ICP-OES 10 ppm Cu

Bureau Veritas - Swakopmund 0.15 g Four Acid ICP-OES 2 ppm Cu

For the analysis of sulphur ICP-OES is used, which Craton have found to be adequate. It was highlighted in the Hellman & Schofield report (Hellman & Schofield Pty Ltd, 2010) that there was a potential low bias with the sulphur results and recommended using LECO. Craton had 20 samples analysed by LECO and found that the mean was 7.5% less than the ICP-OES results, thus Craton have continued with ICP-OES analysis.

8.3.2. Current Laboratory

The analytical procedure for samples submitted to Bureau Veritas is as follows and is summarised in Figure 23: PR101 – Crushing (where required for core samples) PR1004 - Total receive, sort, dry and pulverize up to 1.5Kg (LM2). Verification of optimum grinding parameters. A split of the initial, and every subsequent 20th sample from the first batch, will be wet screened through a 75µm sieve following pulverizing. Once established that a minimum of 90% passes this size fraction consistently, checks can be done on the leader sample in each batch.


31

MA101 - (Every sample) - An aliquot of sample is accurately weighed and digested with a mixture of nitric, perchloric and hydrofluoric acids. The digestion temperature and time is carefully controlled to near dryness, followed by a final dissolution in hydrochloric acid. This digest approximates a 'total' digest in most samples. This method is suitable for large production runs of samples with consistent matrices. The nature of the samples may compromise detection limits. Detection by ICP-OES and the detection limits in ppm are: Cu (2) and S (50). Craton have not found evidence of refractory copper when comparing Aqua Regia and the four acid digestion, but local concentrations of native copper could theoretically be refractory. GC004 – (Where Cu from MA101 > 0.1%) – Pulp density (SG) determination by gas pycnometry. FA002 – (Where Cu from MA101 > 0.25%) - Nominal 40g charge analysed; Silver used as secondary collector, Au, Pt, Pd determined with ICP quantification. Nature of the sample and/or lower sample weights may compromise detection limits. Detection limits in ppb; Au (1) Pt (5) Pd (5). Though Au, Pt and PD are routinely sampled as above, there are no significant results for these elements.

Figure 23 Processing flowchart of samples submitted

Sort and Dry Samples

Crush where required PR101

Split Sample

Mixed Acid Digest MA101

Store reserve / Return to Craton

Pulverise to P85+>75um (min) PR1004

OES Analysis for Cu and S

If Cu>0.1% SG by Gas Pycnometer GC004 Every 10th

Sample to External Lab

If Cu>0.25%

Fire Assay FA002

OES for Au/Pt/Pd


32

9. Assay QAQC

9.1. QAQC Procedures

The Quality Assurance/Quality Control (QAQC) procedures applied towards the previous Resource Model have remained in force into 2014. Hereby, QAQC samples are inserted on a basis of 5%, with the intent of biasing the insertion frequency towards intersections of expected mineralisation. The QAQC samples include standards, blanks and both pulp and rig duplicates which are inserted based on one of three insertion templates as selected by the geologist responsible for a specific hole.

9.1.1. Standards

The Certified Reference Material (CRM) utilised by Craton for their standard insertions are supplied by AMIS of South Africa in 50g sachets.

Five CRM’s have been used within the most recent drilling campaign – these are listed below with their expected and two standard deviation values. CRM’s AMIS0036, AMIS0072, AMIS0088 and AMIS0118 have been previously used during the 2008-2009 sampling campaign, with CRM AMIS0118 being omitted in 2010-2013. CRM AMIS0119 has been recently introduced. The selected CRM’s cover a suitable grade range in relation to what can be expected at Omitiomire.

Table 15 CRM's used and the assigned two standard deviations

CRM Name

Cu ppm S ppm Applied

Expected value

±2 std dev

Expected value

±2 std dev

2008-09 2010-13 2013-14

AMIS0022 1 132 88 4 550 - √

AMIS0031 30 840 1 760 300 20 √

AMIS0036 13 806 630 - - √ √ √

AMIS0040 4 881 418 - - √

AMIS0041 20 320 1 470 - - √

AMIS0071 8 874 630 - - √ √

AMIS0072 16 500 950 2 200 200 √ √ √

AMIS0088 3 216 222 600 60 √ √ √

AMIS0118 4 615 270 3 000 300 √ √

AMIS0119 6 370 540 4 000 300 √

CRM’s AMIS0036 and AMIS0119 are copper sulphide ore from Kansanshi Mine, Zambia.

CRM’s AMIS0072 and AMIS0118 are derived from copper sulphide and copper oxide ores respectively, from the Lonshi Mine, DRC.

CRM AMIS0088 comprises RC chips from the Omitiomire deposit.

9.1.2. Blanks

Various blank materials have been used throughout the duration of the project including the currently used silica river sand. Blank silica pulp was also purchased from AMIS in the past. This is bought in 1 kg containers and then packaged in 50 g packets. Previously Craton had used material from what was expected to be barren hangingwall rocks, but after values with low level mineralisation (<500 ppm) were detected the use of this material was discontinued.

9.1.3. Duplicates

Two types of duplicates are used within the QAQC procedures:


33

Rig duplicates: duplicate samples of RC chips that were riffle split at the drill rig during collection.

Pulp duplicates: duplicate of milled pulp. An empty sample bag is provided with a ticket inside; the laboratory is thereby instructed to produce a duplicate of the milled pulp.

9.1.4. QAQC Failure Rules

A set of rules governing QAQC failure and possible assay resubmission is used as a guide to trigger re-assays. However, in this case the results are meticulously scrutinised by Karl Hartmann and re-submitted on a basis of logical argument in the case of several spurious results. During the latter periods of the Omitiomire operations, no significant re-assay has been deemed necessary with occasional spurious results being accounted for by misallocation or mix-up between two samples. The failure guidelines for standards, duplicate or blanks are as follows:

1. Look at a possible insertion error (Craton report that this tends to be the most common error) 2. Check for a sequencing error or some form of sample swap. If there is an obvious error from the

various log sheets or XRF, it is corrected. 3. If there is no obvious error that can be corrected, a limited range of samples adjacent to the failed

QC sample are submitted for re-assay to the laboratory. Craton report that the re-assays have been very close to the originals, except in 2011 many densities by Bureau Veritas were incorrect and all the densities were reanalysed.

4. There are also various other logical checks that can be run from the XRF, logging and other assays such as sulphur.

5. If all of the above fail, then they resubmit a split from the stored samples. Craton report that this has only been required on a few occasions.

9.2. QAQC Results - Copper

The following QAQC results relate to samples submitted post the previous evaluation campaign in July 2013, the period August 2013 to July 2014. The samples are currently sent to Bureau Veritas in Swakopmund – this has been the case since October 2010. ALS Johannesburg was used as external umpire laboratory. The drilling and assay data updated for this current evaluation comprises a small portion of data received too late for inclusion within the previous campaign, as well as that from the most recent sampling during the 2014 drilling campaign. Throughout this entire dataset, 150 standards, 150 blanks, 115 rig duplicates and 100 laboratory or pulp duplicates were inserted. This totals 515 QAQC samples amongst 3 196 sampled intervals and comprises a 16% insertion frequency (4.7 % CRM standards, 4.7 % blanks and 3.6 % rig and 3.1 % pulp duplicates respectively). While this is somewhat less than what was intended, this is largely due to the shorter average drillhole length throughout this latest campaign. These short drillhole lengths meant that not each of the QC samples could be inserted within the few metres drilled. While the template/matrix could be adjusted to accommodate this, no major discrepancies were noted while monitoring the laboratory results. Thus a slight reduction in the insertion frequency was deemed more suitable rather than having to, at this stage, change templates / matrices and entrenched procedural format which could ultimately lead to confusion.

9.2.1. Standards

The standard material results are provided below by individual CRM. The recommended standard deviations as calculated by the issuing company AMIS are for guidance purposes. The following is quoted on the CRM certificates:


34

“Slight variations in analytical procedures between laboratories will reflect as slight biases to the recommended concentrations and this is acceptable. Good laboratories however will report results within the two standard deviation levels with a failure of <10%.” The best practice is to monitor the performance of a given CRM over a period of time to determine any drift in the analyses of the laboratory by plotting a rolling average on 30-40 samples. None of the CRM analyses comprise sufficient samples for any long term analysis of drift of the laboratory results. Consistently with previous sampling campaigns CRM’s AMIS0072 and AMIS0118 along with the newly introduced AMIS0119 indicate a somewhat high bias (see Table 16 below - % difference with CRM mean) even though AMIS0072 hints at slight improvement since the previous report in 2013 (Nicholls, Craton Omitiomire Oxide Resource Model, 2013). The assay results per individual CRM are outlined below.

Table 16 Statistics of CRM performance

CRM Number of Samples

Expected value (ppm)

% difference with CRM mean

Certified RSD (CV%)

Lab RSD (CV%)

AMIS0036 30 13 806 0.1% 2.28% 4.68%

AMIS0072 11 16 500 3.1% 2.88% 2.55%

AMIS0088 41 3 216 -0.4% 3.45% 3.09%

AMIS0118 30 4 615 5.4% 2.93% 3.60%

AMIS0119 38 6 370 2.3% 4.24% 2.98%

AMIS0036 Although generally understating within the 2008-09 period, CRM AMIS0036 has reported reasonably well within 2 Standard Deviations (SD) in the past. The results of the current campaign are somewhat inconsistent with this prior trend. Of the 30 samples analysed, 7 were outside of 2 SD and 5 were outside of 3 SD as seen in Figure 24. No significant bias is noted however and there is no indication of drift. Thus, and in consideration of the high grade of this standard, the results are deemed acceptable although the performance of this standard should be monitored in the future.

Figure 24 CRM AMIS0036


35

AMIS0072 CRM AMIS0072 has reported generally within 3 SD but often outside of 2 SD throughout the various sampling campaigns 2008-2013. This fairly consistent overstating seems to continue throughout the current campaign although improvement seems evident with reported results somewhat closer to the expected value – albeit that this CRM was not used in large volume in 2013-2014. Of the 11 samples submitted, 2 reported outside 2 SD while all were within 3 SD. Previous recommendation for the monitoring of this particular CRM in the future still stands.


AMIS0088 CRM AMIS0088 performance has been by far the most reliable, reporting consistently within 2 SD – however, this could be expected in light of its origin from this deposit. This trend continues throughout 2013-2014. Of the 41 samples submitted, only 2 reported outside of 2 SD.



36

AMIS0118 CRM AMIS0118 performed relatively poorly in the 2008-09 period. Outside of a considerable period wherein this CRM was consistently reporting below the 2 SD level, it was generally overstated but within 2 SD. Within the current sampling campaign this CRM has reported poorly with 6 of the 30 submitted samples reporting outside of 3 SD and 6 others outside of 2 SD. Reporting was particularly poor during the early stages of the campaign with significant improvement evident later, albeit with a continued high bias.


AMIS0119 This newly introduced CRM, while showing a slight high bias, has performed well as shown in Figure 28. Of the 38 samples submitted, only 1 was outside of 2 SD.



37

9.2.2. Blanks

The continued application of the recently introduced use of “unmineralised” river sand as a blank standard is discouraged. The large majority of these insertions are close to the mean of 12 ppm which in terms of this deposit, is blank. As such, there doesn’t appear to be a problem with contamination. However, even a material such as “pure” silica river sand, in proximity to surficial or near-surface mineralisation could be expected to introduce some anomalous results as seems to be the case. In comparison to previously applied blanks and the associated results, those reported herein are variable to poor with more than 70% of the “blanks” reporting above the previously considered threshold of 5 ppm – as per the AMIS-produced blank.

Figure 29 Blank material


38

9.2.3. Duplicates

Laboratory Pulp Duplicates Figure 30 below is a scatter plot of the laboratory pulp duplicates. The results show an excellent correlation between the original and duplicates indicating good repeatability of the laboratory.

Figure 30 Scatter plot of laboratory pulp duplicates

Rig Duplicates The rig (field) duplicates are expected to have a lesser repeatability than those of the laboratory pulp duplicates, however, is this case the correlation is very good. The best fit line of the samples sits slightly below the x=y line indicating a slightly positive bias as shown in Figure 31.


39

Figure 31 Scatter plot of rig duplicates

Half Absolute Relative Deviation (HARD) plots of the original and duplicate laboratory pulps and rig duplicates are shown below in Figure 32. The ideal precision is for 90% of the data to be within a HARD of 10%. In this case, both the laboratory pulp and rig duplicates indicate excellent precision with the prior displaying expected superior precision.

Figure 32 HARD plot of laboratory pulp and rig duplicates for Cu analysis


40

9.3. QAQC Results - Sulphur

9.3.1. Standards

The standard materials that are used for the sulphur QC are the ones routinely used for the Cu analysis. Of the five standard materials used within the current sampling campaign, three of these include a certified S analysis (CRM AMIS0072, CRM AMIS0118 and CRM AMIS0119). AMIS0088 has a laboratory approximated value with two standard deviations, while AMIS0036 has no approximation of the sulphur content. The expected values and their standard deviations where applicable are in Table 17.

Table 17 Statistics on CRM performance for S analysis

CRM Number of Samples

Expected value (ppm)

% difference with CRM mean

Certificate RSD (CV%)

Lab RSD (CV%)

AMIS0036 30 - - - 3.81%

AMIS0072 11 2 200 -2.1% 4.40% 3.95%

AMIS0088 41 600 -5.8% - 4.94%

AMIS0118 30 3000 3.0% 4.34% 4.17%

AMIS0119 38 4000 3.4% 4.29% 3.50%

AMIS0036 The S analyses of AMIS0036 have shown good consistency throughout the current sampling campaign. While this standard does not have a certified or approximated value for the sulphur content, the variability is less than within the previous 2013 campaign, whereby the RSD is down from 4.74 % to 3.81 %.

Figure 33 CRM AMIS006 S analysis


41

AMIS0072 CRM AMIS0072 has reported reliably within 2 SD throughout. Similarly to the performance of this CRM within the previous campaign, a fairly consistent low bias is suggested.


AMIS0088 The reported values for CRM AMIS0088 are consistent with previous results and while performing generally within 2 SD, a distinct understating or low bias continues to be prevalent. Of the 41 samples 4 report outside of 2 SD with numerous samples tending towards the lower 2 SD level.



42

AMIS0118 Initially CRM AMIS0118 reported irregularly with a seemingly high bias but stabilising during the second half of the sampling campaign. Of the 30 samples, 3 reported outside for 2 SD.


AMIS0119 CRM AMIS0119 has reported consistently during the initial periods of the campaign, becoming more irregular with a high bias during the latter application. Generally the performance is acceptable with only 3 out of 39 samples reporting outside of the 2 SD limits, of which 2 are outside of 3 SD.



43

9.3.2. Blanks

The blank material results for S analysis is in Figure 38. The failure rate is relatively high 11 % but this is also attributed to the use of silica river sand.

Figure 38 Blank material for S analysis


44

9.3.3. Duplicates

Laboratory Pulp Duplicates The scatter plot for the pulp duplicates are in Figure 39. The results show an excellent correlation between the original and the repeats, as shown by the grey line which is very close to the perfect correlation line in red.

Figure 39 Laboratory pulp duplicates scatter plot for S analysis


45

Rig Duplicates The results of the rig duplicates are excellent. Scatter of points is restricted within the 10 % tolerances, which for rig duplicates is exceptional. Similarly to the laboratory pulp duplicates, the results show an excellent correlation between the original and the repeats.

Figure 40 Rig duplicates for S analysis

The overall results for the duplicates are excellent, even for the rig duplicates which usually show significantly lower repeatability than those of the laboratory pulp. The difference between the pulp original and repeat mean grades is just -0.4, % while that of the rig duplicates is 0.2 %.

9.4. Umpire Analysis

9.4.1. Umpire QAQC

The external laboratory umpire checks have been carried out with ALS Global (formerly ALS Chemex), Johannesburg. The procedure is to for 10% of all pulp samples above 0.1% Cu to be sent for analysis as a check sample. Table 18 summarises the method of sample assay at ALS, Johannesburg.

Out of 3 711 samples comprising this dataset, 2 419 samples reported Cu values greater than 0.1% Cu. Of these, 158 samples were submitted for umpire analyses which equates to 6.5%. While this umpire submission rate is somewhat lower than initially intended, the results for those samples submitted shows excellent correlation between the respective laboratory’s determined values.

Table 18 Summary of assay method at ALS

Laboratory Analyte Sample Size Leaching Method ICP Method Detection Limit

ALS Global 0.5 g Aqua Regia ICP-OES 1 ppm Cu


46

9.4.2. Umpire Results

The HARD plot Figure 41 shows that approximately 90% of the data has a HARD of 5. The recommended amount is for 90% to be within a HARD of 10.

Figure 41 HARD plot of original assays at primary laboratory vs duplicates with ALS external laboratory


47

The scatter plot of the primary vs the umpire duplicates below, illustrates an excellent correlation with a R2 value of 0.99. The best fit line of the samples is so close to perfect correlation that any hint of bias towards one or the other laboratory is irrelevant. However above 12 000 ppm it can be seen that Bureau Veritas reports slightly higher grades, which is also evident in Figure 43.

Figure 42 Scatter plot of umpire laboratory checks

The statistics for the datasets, as summarised in Table 18, conclude that there is very little variation of the mean between the primary laboratory and the check assays at ALS. The mean at the primary laboratory is 0.3% lower than ALS and the CV is the same.

Table 19 Primary vs ALS laboratory of mean and CV

Laboratory Mean ppm CV

Primary 5 432 1.31

ALS 5 446 1.31


48

The percent relative difference plot in Figure 43 shows that Bureau Veritas reports slightly higher between approximately 12 000ppm and 30 000 ppm. Overall the linear regression lie (in red) is showing that there is no bias between the results.

Figure 43 Percentage relative difference vs paired mean grade plot


49

The HARD plot of the sulphur analysis below shows that approximately 80% of the data has a HARD of 11. This is not within the desirable range of relative difference

Figure 44 HARD plot of original S% assays at primary laboratory vs duplicates with ALS external laboratory

The scatter plot of the Bureau Veritas sulphur analysis vs the umpire duplicates below, illustrates a good correlation with a R2 of 0.97. The correlation line is biased towards the assay of approximately 25 000 ppm of the primary laboratory which reports significantly lower with the umpire laboratory. Overall Bureau Veritas reports a mean grade of the sulphur analyses 11.6% higher than the umpire laboratory. This could be in part due to the leach method difference between the two laboratories. The method used at ALS is a partial leach (Aqua Regia), whereas Bureau Veritas uses near total method of four acid digestion.


50

Figure 45 Scatter plot of umpire laboratory checks for S%


51

9.5. Discussion and Conclusions

9.5.1. Copper

Considering all results of the CRM’s, 9% are outside of 2 SD and 7% outside of 3 SD. For resource reporting it would be desirable for the failures to be < 10 % and within 2 SD. However, the majority of these failures can be attributed to laboratory drift i.e. high or low bias in relation to the expected value. Considering 2 SD from the mean of the reported grades for each CRM, the failure rate would be much lower. The low grade CRM AMIS0088, which is around the cut-off for the mineralisation, continues to perform well and has shown that the laboratory has not drifted over the years. In light of this particular CRM’s value remaining consistent, one could suggest that continued bias over several sampling campaigns, such as is the case for CRM AMIS0072 and to an extent CRM AMIS0118, indicates that the mean for the Bureau Veritas laboratory is slightly different to the certified value. The main requirement of the CRM’s is to monitor for drift and that results remain consistent – even if they are biased higher or lower. This function has been satisfied at lower grade in light of the continued results of CRM AMIS088. However, in the case of the higher grades, it is recommended that the results of CRM AMIS0072 are continuously monitored to prevent any significant overestimation. While the application of silica river sand has been shown to be not ideal, the reported values do not show any evidence for continued cross-contamination. The correlations of both the rig and laboratory pulp duplicates are exceptionally good. However, considering the low number of samples, the nature of this relatively high-grade, base metal deposit and the excellent umpire laboratory results, an associated low variability when compared to for example a gold deposit, is deemed suitable.

9.5.2. Sulphur

The CRM materials indicate good consistency of results while a slight low bias may be evident at lower grades whereas the higher grades may be somewhat overstated in comparison to the expected values. No significant problems of drift or grade estimation are expected. The results of the blank material although not ideal, do not indicate problems with contamination. The duplicates from the rig and laboratory pulp, like in the case of the copper, show good repeatability.


52

10. Drillhole Database

10.1. Database Description

The database is maintained by Simon Brodie, GIS and Data Manager at head office in Windhoek. Simon Brodie has over 22 years of experience in the Exploration field. His experience spans field assistant in groundwater, geophysical surveying, supervising drilling operations and test pumping groundwater resources. The past 15 years has seen his experience move into the mineral exploration industry and has had an increasing role in both GIS and database management. From 2000 to 2003 he worked for Anglo Base Metals Namibia firstly as a field technician and then GIS and database manager for the companies’ exploration activities in the surrounding areas of Skorpion mine. He then became the grade control database manager for Navachab gold mine until 2006. 2006 to 2007 he saw himself managing the Namibian exploration activities for Helio Resources, a Canadian based junior exploration company and from 2007 to the present has held the position as GIS and database manager for Craton. The database is held within Microsoft Access at the Craton offices in Windhoek. The drillhole database was supplied to Bloy in Excel file format exported from aforementioned database. The main tables and fields within the database are outlined in Table 20. The number of records represent the entire database for Omitiomire and surrounding areas.

Table 20 Tables and fields within database

Table Fields Records

Collar HoleID, X, Y, Z, EOH, DrillType, CollarCaptureDevice, DateDrilled, Geologist, Comments, DrillContractor & ProjectID (Resource or Exploration Drilling)

1 645

Geology HoleID, From, To, Lithological Logging, Mineralisation Logging & Descriptions as per the standard RC and diamond log sheets

105 832

Sampling HoleID, From, To, Interval, SampleID, Weights, SampleType

116 741

Assays SampleID, Cu, S, CuOx 37 296 (2 845 CuOx)

Survey Dip and Azimuth records 4 500, 2 775 actual readings

Internal XRF SampleID, Cu (plus 17 other elements) 67 969

External XRF Cu 30 469 records from Genalysis and Setpoint

External ‘C’ Check

Cu (plus 34 other elements) 1 294

‘D’ Sample Au, Pt, Pd 1 669; SG – 8 663 records

Geotechnical logging per metre

HoleID, From, To, Index, Fractures, Hardness, RQD 14 096

Geotechnical logging per run

HoleID, From, To, Interval, Recovery 5 570

Final Merged A series of queries which links all data from the above tables together (except Collar and Survey)

10.2. Database Procedures

Locally on site, geologists are assigned ownership of drillholes and it is their responsibility to ensure all procedures are followed from beginning to end. The data capture is done on site by the responsible geologist on pre-designed worksheets and imported into the main database using macros. All field logging sheets are standardised to meet the requirements of the database department and fields within these sheets are not allowed to be changed. Many of the columns for the data capture have pick lists to select


53

from. For example in the geology logging sheet, there are pick lists for the lithology, hardness, oxidation and clay fields. Procedures have been made for the field crews in order to maintain a smooth import of data into the database. The procedures cover:

Geology log capture

Drillsheet data capture

Drillsheet design

Laboratory submission

Filing name procedure Validation of drillhole depths, logging and assay data is undertaken by Simon Brodie, Karl Hartmann and the geologists involved. The validation procedure is by:

Comparison of ICP results with logging and the XRF results

Plotting drillholes onto section The results are received from the laboratory digitally and are imported into the database using the Microsoft Access import facility.

10.3. Data Verification

Percussive drillholes that are pre-fixed with OEP were excluded from the mineral resource estimation due to their unreliable assay results. The drillholes were used for their geological logs in the generation of the mineralised wireframes. The total number of OEP drillholes in the database are 17 totalling 1 741m.

10.3.1. Digital Error Checking

Standard checks were made during the drillhole de-surveying process for the following kinds of errors:

Interval overlaps

Interval duplication

Missing coordinates

Missing assays Duplicate records were found in the assay file for drillholes: ORC900, ORC928, ORC962, ORC974, ORC993, ORC996. They were reported to Craton and they were rectified.

10.3.2. Manual (Hard Copy) Validation

During both sites visits in 2012 and the most recent one, several geological logging sheets and sampling drill sheets were photographed for various reasons. The data on these photos was subsequently captured to allow electronic comparison of this data to that which has been passed onto Bloy directly from the database - for inclusion within the current evaluation. This comparison thus comprises a form of database validation ensuring that what is captured both in the field and in the laboratory is correctly transferred to, and reflected within the database. The intention during the current site visit was to capture 10% of the current campaign’s raw data for such comparison. Considering that the current drilling campaign at the time comprised around 140 holes, the drill and log sheets of 14 holes were photographed. The raw data for 8 other holes, selected randomly but not necessarily from the current campaign, were also captured. Fairly randomly selected intervals from 4 other holes were photographed during the 2012 site visit – these were subsequently also captured and included within the database checks. While all of the selected sampling intervals represent RC drilled sampling, similar documented and stringent sampling control procedures are applied to diamond-core drilled sampling to ensure similar levels of data integrity.


54

Table 21 BHIDs of the drill and log sheets photographed and during which period

2012 - Random selection

2014 - Random selection

2014 - Current campaign

1 ORC126

ORC410 ORC999 2 ORC173

ORC529 ORC978

3 ORC464

ORC578

ORC983 4 ORC485

ORC598 ORC956

5 ORC607 ORC944 6 ORC905 ORC030 7 ORC263 ORC024 8 ORC244 ORC017 9 ORC010 10 ORC008 11 ORC007 12 ORC002 13 ORC996 14 ORC966

The laboratory assayed CU ICP and S ICP values as well as the logged “handheld” XRF CU values for the latest sampling campaign were received from the Craton database administrator. These values were combined with the captured log sheet data, by sample ID, into a single file. Thus an electronic comparison between the two CU, CU XRF and S values (one from raw log sheets and one from the database) could be achieved for each assayed sample interval. In those instances whereby the associated values did not match, the interval was flagged as a discrepancy. Out of more than 2 000 captured sample intervals, 296 contained comparable assay values for CU, CU_XRF and S – thus 888 comparable values. 55 differences between the S values of the finalised drillhole file and the captured data were noted – these can however in every single case be directly attributed to the fact that the assay values of these intervals were below detection limit. The database reflects “below detection limit” values as “-20 ppm”. During the data import into Studio 3 and subsequent processes, the “below detection limit” intervals are replaced with a value of 10 ppm as working with negative values is impractical in Studio 3. This difference in value between what is reflected within the database and within the final drillhole file is thus firstly mis-representative or irrelevant and secondly, not a reflection of actual comparison between raw field vs database captured data. While the 55 differences in S values can be ignored, 18 consecutive intervals were noted whereby the original and final CU, CU XRF and S values did not correspond – those of hole ORC944; 17 m to 35 m. However, although this is a case whereby a genuine mismatch of sample interval has occurred, once again the cause suggests a low significance to the validity of the overall dataset as a whole. In this case the entire holes’ sample intervals have been offset by a single metre – thus the intervals reflected within the database from 18 m - 36 m, should in fact reflect the true depth intervals as per the original sampling sheets; from 17 m - 35 m. Overall it is suggested that in terms of samples and associated assay values, what is reflected within the final database is a good reproduction of what is originally captured in the field and assayed in the laboratory.


55

11. Statistical Analysis

11.1. Stationarity Testing

There was no major re-interpretation of any domains therefore stationarity checks were not carried out. The stationarity checks carried out for the previous Resource Model were considered to be valid for this estimation (Nicholls & Rohwer, Omitiomire Resource Model, 2012).

11.2. Estimation Domains

11.2.1. Definition

The domaining of the deposit was completed by Karl Hartmann. There was no major re-interpretation of the domains, they were modified for new drilling and associated local interpretation of the mineralised domaining. A new target, Tiger, approximately 1 km south west of the main deposit has been included in the estimation. The mineralised wireframes of the 10 estimation domains are illustrated in Figure 46 and are listed in Table 22.

Figure 46 Estimation domains and collar plan coloured by model year

Tiger - approx. 1 km

from main deposit

Mamba - approx. 0.5 km

from main deposit


56

In comparison to 2012 the overall volume of the domains has reduced by 4%. The loss of volume has been from the modification of the domains for new drilling. All domains except Bruce lens are reduced in volume. The larger domains 1 to 4 have between 2 and 4 % loss in volume, the remaining smaller domains have a higher percent loss between 10 and 17%. The Bruce lens, domain 7, is the only lens to see an increase in volume of 10%. The domain has undergone a slight change in the interpretation on the peripheries which resulted in some gains and losses. The new drilling in the north west has locally thickened the domain from 9 to 15 m in some instances. Overall there has been a positive effect on the volume.

Table 22 Omitiomire mineralised domains compared with 2012

Domain Description 2012 Volume

(m3) 2014 Volume

(m3) % Difference

1 A lens 18 572 500 17 377 625 -6%

2 B lens East 23 172 250 22 232 250 -4%

3 B lens West 25 408 250 23 864 250 -6%

4 C lens 29 791 250 29 206 875 -2%

5 T Central lens 2 296 000 2 045 875 -11%

6 Kaya 1 305 500 1 088 688 -17%

7 Bruce lens 5 052 250 5 556 750 10%

8 Bruce Terrace lens 347 750 298 500 -14%

9 Mamba 693 500 609 500 -12%

10 Tiger N/A 2 424 625

11.2.2. Methodology

Local adjustments were made to the domain wireframes in Datamine for new drilling information. The wireframes were updated from the previous model following either a geological continuity and/or applying a cut-off of approximately 0.25% Cu. To ensure geological continuity the cut-off was sometimes lowered to 0.1% whereas in higher grade areas a cut-off of 0.25% was used. This cut-off was chosen largely on a geological basis as this provided reasonable continuity between several of the more patchy areas of mineralisation towards the western extents of the lenses is evident. Wireframes were generally projected approximately half the drillhole spacing to close off the mineralisation.

11.2.3. Validation

The wireframes were verified in Datamine and the sample selections thereof were visually checked. The wireframes have been analysed by Boundary Analysis for the previous resource model (Nicholls & Rohwer, Omitiomire Resource Model, 2012) which supported a ‘hard’ krige approach to the estimation method.

11.3. Sample Assay Statistics

11.3.1. Copper

Figure 47 below is the histogram of samples within the mineralised wireframes. Overall for the mineralised zone, 40% of the data is below 0.25%. By domain, the percentage of waste samples (<0.25%) varies somewhat as shown in Table 23. The domains with the lowest mean grades, all ≤0.30 %, have the highest percentage of waste samples within them in excess of 57%. These are B lens west (D3), Bruce lens (D7), Mamba (D9) and Tiger (D10). In the case of the Tiger target, the mean grade is less that the cut-off. The results are not unexpected as they are low grade domains and clearly fluctuate around the cut-off grade.


57

In comparison, the domains with the higher mean grades of >0.65%, all have lower percentage waste samples of around 22-26%. This indicates that the mineralised material can be reasonably partitioned from the surrounding waste.

Figure 47 Histogram of all samples within the wireframes

Table 23 Percentage of waste samples per domain

Domain % Below 0.25 %

1 25

2 38

3 63

4 39

5 22

6 42

7 71

8 26

9 57

10 75

The histograms by domain are in Figure 48 below. Domains 1 to 3 are well sampled, each in excess of 1500 samples. The low grade domains as discussed above (D3, 7, 9 and 10) are distinguished by the high percentage of low grade samples in the histogram distribution compared to the other domains whose means are well above the cut-off grade.


58

Figure 48 Individual domain histograms

The cumulative frequency plots of selected domains are collated in Figure 49. This plot shows the difference in the sample distributions between the domains with the highest mean grade, Bruce Terrace (D8) and the lowest, Tiger (D10).


59

Figure 49 Cumulative Frequency plot of all domains

The sample statistics for each domain were calculated on 2m composites (section 11.5) and are summarised in Table 24.

The Coefficient of Variation (CV) for all domains is between 0.73 and 1.17 which indicates a moderate to high variability

Bruce lens has a moderately high CV of 1.17, and is significantly under sampled in terms of its volume (Table 53)

The A lens, T Central lens and Bruce Terrace lens have the highest mean grades ≥0.67%

The new target Tiger has the lowest mean at 0.19% followed by B lens West

Table 24 Drillhole sample statistics of Cu %

Domain Description DOMAIN No. samples Min Max Mean CV

A Lens 1 3 146 0 8.06 0.67 1.07

B Lens East 2 1 734 0 7.13 0.51 1.17

B Lens West 3 2 443 0 2.45 0.25 0.96

C Lens 4 611 0 3.96 0.48 1.10

T Central Lens 5 766 0.01 6.67 0.68 1.00

Kaya 6 141 0.01 1.17 0.37 0.73

Bruce 7 125 0 1.68 0.28 1.17

Bruce Terrace 8 267 0.03 3.19 0.81 0.84

Mamba 9 84 0.02 1.28 0.30 0.86

Tiger 10 205 0 1.87 0.19 1.32


60

11.3.2. Sulphur

The sample histogram for the S % for the mineralised zone is below in Figure 50. The distribution shows high positive skewness. The statistics are in Table 25, it has a moderately high CV of 1.49.

Figure 50 S % sample histogram for mineralised zone

Table 25 Sample statistics of S %

Field DOMAIN No. samples Min Max Mean CV

S % 1-10 inclusive 8 788 0.00 2.43 0.10 1.49


61

11.3.3. Percentage Dark

Below in Figure 51 is the sample histogram of the logged field PC_DARK within the mineralised zone. The histogram is negatively skewed which is as expected as the mineralisation is associated with dark mafic rocks. The values logged are from 0 to 100 % and the mean within the mineralised zone is just less than 50 % (Table 26), though the mode is 75 %, which is more relevant in this case. The CV is low at 0.51.

Figure 51 Sample histogram of PC_DARK within the mineralised zone

Table 26 PC_DARK statistics within mineralised zone

Field DOMAIN No. samples Min Max Mean CV

PC_DARK 1-10 inclusive 6 801 0 100 49.99 0.51


62

11.3.4. Rock Type

The histograms of Cu % by lithology within the mineralised zone are below in Figure 52. Only lithologies that have sufficient samples (>100) have been included. All lithologies display a high positive skewness. Of the mafic rock types the BAS and MGN are the most sampled, in excess of 4800 and 6000 respectively. Of the felsic rock types the GBG and WGN are the most sampled both with >2000 each.

Figure 52 Histograms by lithology within mineralised zone


63

The sample statistic by lithology are summarised in Table 27.

The mafic rock types all have CV’s moderate to high range in contrast to the felsic rock types all have very high CV’s > 2.0

The mafic rock types, as expected have higher mean grades than the felsic rock types

Table 27 Cu % statistics by lithology within mineralised zone

LITHO Description No.

samples Min Max Mean CV

BAS Biotite amphibolite 4873 0 11.6 0.72 0.96

SCH Biotite schist 797 0.01 8.02 0.77 1.14

MGN Mafic gneiss 6165 0 11.6 0.54 1.4

GBG Grey biotite gneiss 2385 0 11.1 0.25 2.16

WGN White gneiss 2191 0 13.04 0.21 2.27

PGN Pink gneiss 403 0 6.58 0.2 2.33

PEG Pegmatite 227 0 11.9 0.41 2.16

11.4. Declustering Analysis

The mean grade as determined from the assays could be biased if there is a concentration of drilling in a high or low grade area. This is a common occurrence – a wide-spaced grid is placed over the target area and then once the potentially-economic zones are discovered, drilling is concentrated in these areas to firm up on the resource. Checking and correcting for this “Clustering” effect is necessary because it is recommended practice to assess the reliability of the estimates by comparing the global means of the blocks versus the samples. If one has a highly irregular drilling grid or a concentration of drilling in any one area of the deposit, then it is necessary to “Decluster”. Bloy uses a modified version of the GSLIB Decluster routine to determine the unbiased mean from spatially located sample data. The decluster routine was attempted on all domains, and where a suitable set of results allowed, a declustered grade was determined. Generally datasets with few points will not produce reliable results. The results are summarised in Table 28. Figure 53 below illustrates the declustering results for A Lens, Domain 1. This is a typical example where the high grade has been targeted and the resulting arithmetic mean is high due to the clustering of data. The grade drops away and though does not stabilise, it does indicate that the declustered mean is around 0.60 %.

Table 28 Declustered sample means by domain

Domain Description DOMAIN No.

samples Arithmetic

Mean Declustered

Mean

A Lens 1 3146 0.67 0.60

B Lens East 2 1734 0.51 0.59

B Lens West 3 2443 0.25 0.24

C Lens 4 611 0.48 0.52

T Central Lens 5 766 0.68 0.57

Kaya 6 141 0.37 0.33

Bruce Lens 7 125 0.28 0.34

Mamba 9 84 0.30 0.30


64

Figure 53 Decluster Analysis for Domain 1, A Lens

11.5. Compositing

Compositing is necessary to ensure that sample support is constant throughout the geostatistical process, and that a very small interval does not have the same influence of a large interval. The selection of an appropriate compositing length should consider the lengths of the existing samples, the geometry of mineralised domains and the proposed mining selectivity. Previous work has established that a 2 m composite is suitable for this deposit (Nicholls & Rohwer, Omitiomire Resource Model, 2012). The compositing was within each domain wireframe to 2 m. The maximum composite length was 2 m and the minimum was 1 m.

11.6. Extreme Values

In general extreme values do not present a problem on this deposit. One domain, Bruce Lens (D7), required grade capping in the previous Resource Model (Nicholls & Rohwer, Omitiomire Resource Model, 2012). It was necessary to cap this domain again, as the new drilling was not in the same area as the high grades and therefore remained unsupported. The grade capping was set to 1.11%.


65

11.7. Missing Samples

Since the unsampled intervals within the mineralised domains are diamond core that was logged but indicated little or no copper, the intervals were set to half the detection limit of 0.00005%. This would make the estimate more conservative, but with the assumption that the unsampled intervals are barren it is more realistic. Table 29 summarises the percentage of intervals of each domain that had missing values.

A summary of the results are in Table 29 below. The C lens is most affected by the correction of missing samples to half the detection limit. It has the effect of lowering the mean grade by almost 6%. This domain also proportionally has the highest amount of missing values.

Table 29 Percentage of missing intervals in the domained drillhole file

Domain Description % Missing

Values Uncorrected mean grade

Corrected mean grade

Percentage difference of mean grade

1 A lens 0.7% 0.68 0.67 -1.5%

2 B lens East 0.6% 0.51 0.51 0.0%

3 B lens West 1.7% 0.26 0.25 -3.8%

4 C lens 5.7% 0.51 0.48 -5.9%

5 T Central lens - 0.68 0.68 -

6 Kaya - 0.37 0.37 -

7 Bruce lens 4.3% 0.29 0.28 -3.4%

8 Bruce Terrace lens - 0.81 0.81 -

9 Mamba - 0.30 0.30 -

10 Tiger - 0.19 0.19 -

11.8. Density Statistics

Some 7 513 gas pycnometer density measurements have been taken throughout the deposit. There is a 80:20 split of measurements for within and outside of the mineralised zones. When considering the density by lithology, the dataset is mostly in the BAS and MGN dark lithologies which are associated with the mineralisation (Table 30).

Table 30 Density data statistics per lithology

Lithology Colour No. samples Min Max Mean CV

BAS Dark 2 147 2.60 3.60 2.94 0.03

MGN Dark 3 017 2.62 3.81 2.87 0.03

SCH Dark 656 2.62 3.15 2.89 0.03

WGN Light 640 2.61 3.05 2.79 0.02

GBG Light 739 2.62 3.05 2.80 0.02

PEG Light 90 2.53 2.93 2.78 0.02

PGN Light 150 2.66 2.89 2.75 0.02

QTZ Light 25 2.69 2.95 2.78 0.02

A comparison was made on the current dataset for measured density above and below 0.25% Cu by lithology with the Hellman & Schofield derived bulk density values where available (Hellman & Schofield Pty Ltd, 2010). Box and whisker plots were used to display the results as shown in Figure 54 and Figure 55. The main mineralisation bearing lithologies BAS, MGN and SCH compare reasonably well with the Hellman & Schofield means for both the mineralised and unmineralised units. The waste lithologies GBG, PEG and PGN where Cu is <0.25% do not compare so well. The Hellman & Schofield values for these units are considerably lower than the gas pycnometer means. However, the GBG unit mean, where Cu >0.25% compare very well with each other.


66

Figure 54 Density box & whisker plot for Cu<0.25%

Figure 55 Density box & whisker plot for Cu>0.25%

The gas pycnometer data was also compared to the values for the oxide GBG and PEG units as shown in Figure 56. There is no differentiation on grade for this comparison. The Hellman & Schofield oxide values both units were determined to be 2.50 g/cm3 which is considerably lower than the gas pycnometer values at 2.80 g/cm3 and 2.77 g/cm3 for the GBG and PEG respectively. Given that the gas pycnometer dataset exceeds 7500 readings, it was decided that the gas pycnometer means would be used for the bulk density assignments where no data was available instead of the Hellman & Schofield values.


67

Figure 56 Density box and whisker plot for oxide

The samples where no measured density was available but had been assayed for Cu, a regression equation was used to calculate the density. For the previous model, the lithologies were divided into “light and “dark” and trendlines were fitted to determine the regression equation to be used to calculate the density of the lithological unit based on the grade. When reviewing the updated dataset, the data was further divided by the main lithologies as shown in Figure 57 and Figure 58. The equations derived from these trendlines were used to calculate the density where Cu was assayed for the main lithologies BAS, MGN, SCH, GBG, PEG, PGN and WGN.

Figure 57 Grade versus density for dark lithologies


68

Figure 58 Grade versus density for light lithologies

This application of interpolated density values provided 11 095 density values for estimation within the mineralised domains, as outlined in in section 12.2.6.

The oxide/sulphide interface was taken into account based on the following guidelines supplied by the client:

All samples with a depth of less than 20 m were assumed to be “oxide”

If a sample had an S_Ratio of less than 0.155 then it was assumed to be “oxide”

The rationale for the use of a S_Ratio value is described by the client below:

“The S_Ratio displays variations of oxidation with depths, as seen in borehole logging. The figure below (Figure 59) shows that the copper almost totally oxidised to a depth of 20 m, followed by a transition zone to 40 m, whilst below 40 m the copper occurs mainly in the form of sulphide. Samples above the line, representing an S_Ratio of 0.22, contain anomalous amounts of bornite. The implications are that modelling of S_Ratio must have a soft boundary between 20 and 40 m (as was done in September 2011).”


69

Figure 59 S ratio versus sample depth

These oxide codes could then be used in conjunction with logged rock type for all intervals that did not have either measured or derived density values. For lithologies other than those listed in Table 31, a bulk density of 2.76 g/m3 was assigned. The bulk density values for individual lithologies are shown in Table 31.

Table 31 Bulk densities based on gas pycnometer means

LITHO Density Comments

BAS 2.88

PGN 2.75

SOL 2.00

SCH 2.86

GBG 2.79 Oxide

PEG 2.77 Oxide

Table 32 and Table 33 summarise the levels of each method in the database. In the mineralised domains the dominant method is by derivation with 36% being directly measured by the gas pycnometer and only a very small percentage being assigned default values. In the non-mineralised domain the proportion of assigned is larger (21%) and only 2% percentage was measured directly.

Table 32 Density determination expressed in metres – Mineralised Zone

Method Metres Percentage

Pycnometer 6 610 36%

Derived 11 573 63%

Assigned 270 1%

Table 33 Density determination expressed in metres – Non-Mineralised Zone

Method Metres Percentage

Pycnometer 1 678 2%

Derived 57 608 77%

Assigned 15 394 21%


70

12. Geological Modelling

12.1. Geological Interpretation

A geological model was not required for the modelling of this deposit as the mineralised wireframes are constructed taking into account the geological relationship associated with the mineralisation.

12.2. Block Attribute Modelling

The key fields in the block model are summarised in Table 34 below.

Table 34 Summary of key fields in the block model

Field Name Interpolation method Description

DENSITY Estimated by IDW Estimated density (IDW2)

DOMAIN Assigned Kriging control field based on mineralised zone

CU% Estimated by OK Kriged Cu% estimate

S% Estimated by OK Estimated Sulphide content

PC_DARK Estimated by OK Kriged estimate of ‘Percentage Dark’

CLASS Assigned Classification category:1=MEAS; 2= IND; 3= INF; 4=Exploration Target

PCD_CAT Assigned Confidence category for PC_DARK: 1=High;2=Medium;3= Low

OK Assigned Cu% OK estimate = 1; Global estimate = 0

GC Assigned 1=50x50x10m block; 2=25x25x5m block

PIT Assigned Individual pit ID number (1-4)

SV Assigned Search volume number (Cu%)

SR Assigned Slope of Regression (Cu%)

EVAL_BY Assigned Person responsible for model

EVAL_DT Assigned Date model was completed

EVAL_BH Assigned Drillhole file used for model

12.2.1. Block Model Setup

The block size used was 50 x 50 x 10 m, which is the same as the previous model (om_mod_201208_final). A GC type model was incorporated into the parent Resource Model at a block size of 25 x 25 x 5 m. Sub-celling was to 5 x 5 x 1.25 m to wireframe boundaries. As the deposit is generally dipping 21º to the east/north-east, the sub-celling was vital in order to maintain the integrity of the mineralised wireframes. The block model prototype is in Table 35.

Table 35 Datamine block model prototype

X Y Z

Model origin 801 000 7 581 145 1 000

Parent Block size (m) 50 50 10

Number of Blocks 63 87 75

Model Maximum 804 125 7 585 495 1 750

12.2.2. Lithology

A lithological model has not been created for this model. At this time Craton are satisfied that the inclusion of the geological logging in the mineralised domain wireframing is sufficient and that a lithological model is not vital. It is possible that a model might be of some benefit since that the grade is associated distinctly with mafic rocks. Whether in reality a geological model would be successful enough to improve the domaining would have to be further investigated.


71

12.2.3. Estimation Domains

The estimation domains are controlled in the model by the field DOMAIN. The mineralised model was created by filling the mineralised wireframes ‘omwf_201407_mzonept,tr’ with full parent sized blocks and sub-celled to the wireframe boundaries, to the minimum cell size as stated in section 12.2.1. The domains are described in Table 36.

Table 36 Estimation domains

Domain Wireframe colour Description Volume (m3)

1 29 A lens 17 377 625

2 3 B lens East 22 232 250

3 27 B lens West 23 864 250

4 9 C lens 29 206 875

5 5 T Central lens 2 045 875

6 13 Kaya 1 088 688

7 53 Bruce lens 5 556 750

8 8 Bruce Terrace lens 298 500

9 6 Mamba 609 500

10 17 Tiger 2 424 625

12.2.4. Structure

No structures have been wireframed to be used in the modelling process. Where structures are known to exist, the mineralised wireframes took these into account.

12.2.5. Topography

The topographical surface was created from Lidar survey points.


72

12.2.6. Density

The density model was created using IDW2 to estimate individual block values based on the sample file omdk_201407_assay_2m where each individual sample within the file has a density value which is either by actual measurement, by calculated relationship, or by default. The sample file was then used to estimate by IDW2 into full size parent blocks. The search volumes were orientated locally using dynamic anisotropy. The search parameters used are in Table 37.

Table 37 Search parameters for density estimation

Search radii (m) No. samples Search Volume multiplying factor

No. samples Discretisation (xyz)

X Y Z Min Max Min Max

200 200 20 5 20 12 3 20 6x6x5

As the oxide/sulphide boundary is already represented within the sample file, the density was not interpolated within two separate oxide/sulphide domains (i.e. interpolated using a soft boundary). However, density was interpolated separately within the mineralised and waste domains.

12.2.7. PC DARK

The PC_DARK field in the model is the interpolated percentage of dark rocks expected. The % dark rock is logged in the field and inputted into the database. The values were used to krige into the blocks within the mineralised domains.

12.2.8. Depletion

Mining has not commenced at Omitiomire therefore no depletion surfaces are available.


73

13. Variography

13.1. Copper

The variography for all the domains were revisited. The main reasons are to check whether the previous model still holds or if there is sufficient new data to allow an improved experimental variogram for modelling.

13.1.1. Calculation Parameters

Variography was carried out using 2 m composites and a 50% tolerance on the lag distance. Where necessary, the filtering of grades was used to control the structures of the variogram. The variograms were orientated, where possible into the plane of the mineralisation, in the three orthogonal directions. Table 38 summarises the parameters used for the experimental variography. Domain 1 (A lens)

The variogram model was last updated for the Oxide model in 2013 (Nicholls, Craton Omitiomire Oxide Resource Model, 2013). An experimental variogram was calculated with the updated dataset and was found to fit the 2013 model reasonably well. It was decided to use the 2013 model. Domain 2 (B lens east) The last model for this domain was 2012 (Nicholls & Rohwer, Omitiomire Resource Model, 2012). The experimental variogram for the new dataset was a reasonable fit to the downhole model from 2012, this was used as a base and then the along and across strike was fitted for the new data. Domain 3 (B lens west) The last fitted model from 2012 needed slight adjustment for the new experimental data points. No filtering of grades were necessary. The ranges in the major and semi-major directions Domain 4 (C lens) Due to the addition of only one drillhole to this domain, the experimental variogram could not be improved from the 2012 model. Domain 5 (T lens) The model for this domain was last fitted in the oxide resource update in 2013. The experimental variogram could not be improved from the previous model. Domain 6 (Kaya) Due to the small dataset of Kaya (<150 samples) the resultant variography is very poor. The domain itself is narrow (3-8m) and is not completely planar with varying dip directions. Therefore directional variography is problematic, though the omni-directional is equally as poor. Domain 7 (Bruce lens) The dataset size and distribution for Bruce lens does not allow for any reasonable variography. Domain 8 (Bruce Terrace) The last variogram model was in 2012. Additional data improved the experimental variogram and therefore could update the model. Domain 9 (Mamba) Small dataset (<100 samples), does not enable any reasonable structures. Domain 10 (Tiger) This is a new domain for this model with ~200 samples. The drill spacing is approximately 50 x 100 m, the variography along and across strike was very poor. Some structure was observed downhole, but by itself would not have been of any use as the maximum range was approximately 25 m.


74

Table 38 Experimental variogram parameters for 2014 variography

Domain Lag distance (m)

Additional Details Along strike Down dip Downhole

1 25 25 2 No filtering of grades

2 55 55 2 Values > 4 % filtered



13.1.2. Variogram Models

Models were fitted to five of the domains where models could be adequately fitted. The variogram model for Domain 1 is shown below in Figure 60. All variogram models are in Appendix 3.

(a) Downhole direction (b) Along strike direction

(c) Down dip direction

Figure 60 Variogram model for Cu % - Domain 1 A lens

The following table summarises the variogram models used for each domain. The models are expressed in their normalised state.


75

Table 39 Grade variogram models

Domain Description C0 C1 C2 Range 1 (m) Range 2 (m)

X Y Z X Y Z Comments

1 A lens 0.41 0.25 0.34 20 25 5.3 45 90 17 2013 model

2 B lens East 0.51 0.09 0.40 50 112 6 270 450 27 2014 (modified 2012 model)

3 B lens West 0.32 0.19 0.49 20 20 6 80 120 12 2014 model

4 C lens 0.36 0.32 0.31 9 9 9 120 120 29 2012 model

5 T lens 0.23 0.35 0.42 25 25 7 150 150 25 2013 model

6 Kaya 0.51 0.09 0.40 50 112 6 270 450 27 D2 model

7 Bruce 0.32 0.19 0.49 20 20 6 80 120 12 D3 model

8 Bruce Terrace

0.14 0.45 0.41 13 13 7 30 70 11 2014 model

9 Mamba 0.32 0.19 0.49 20 20 6 80 120 12 D3 model

10 Tiger 0.32 0.19 0.49 20 20 6 80 120 12 D3 model

In order to determine which model would be most suitable to be applied to the remaining four domains, the population statistics were examined. By comparing the cumulative frequency histograms (Figure 49), domains that displayed a similar distribution to a domain with a variogram model was considered to be similar enough to apply that variogram model to the un-modelled domain. Domain 6 used the model from Domain 2; Domains 7, 9 and 10 used the variogram model from Domain 3. The models were rescaled to the true population variance per domain prior to kriging.

13.1.3. Variogram Comparison

Three domains were updated for their variogram models; the previous models are summarised in Table 40. The domains updated were B lens east (D2), B lens west (D3) and Bruce Terrace lens (D8). Domain 2: the nugget remained relatively unchanged at 51% but the first structure decreased from 20% to 9%. The ranges across and along strike were increased substantially from 150 m along strike to 450 m. The range in the minor axis remained relatively unchanged at 27 m. Domain 3: the overall structure did not alter by much; the main change was an increase in the ranges. Domain 8: the main change was from a single to a double structure model. The nugget remained similar at 14 % from 12 %. The longest range along strike increased to 70 m from a maximum of 36 m previously.

Table 40 2012 Cu % variogram models

Domain Description C0 C1 C2 Range 1 (m) Range 2 (m)

X Y Z X Y Z

2 B lens east 0.52 0.20 0.29 35 35 7 150 150 25

3 B lens west 0.34 0.19 0.46 10 10 5 90 50 10.5

8 Bruce Terrace 0.12 0.88 - 36 36 7 - - -


76

13.1.4. Variogram Quality

Common to all the models is that the semi major axis, down dip, confidence is generally poor. The best direction is downhole followed by along strike. Domains 1 to 4 have sufficiently high sample numbers to be reasonable confident in the models, especially in the major and minor axes. The domain 5 model, from 2013, is represented reasonably well in the minor axis and much less so in the major and semi major axes. The domain 8 model is an improved model on the previous, and though very poor in the semi major axis, the minor and major axes are good.

Table 41 Variogram quality

Domain Description Confidence

1 A lens Good

2 B lens East Good

3 B lens West Good

4 C lens Good

5 T lens Moderate

6 Kaya N/A

7 Bruce N/A

8 Bruce Terrace Moderate to good

9 Mamba N/A

10 Tiger N/A


77

13.2. Sulphur

13.2.1. Variogram Model

The variogram model for sulphur was updated. The data from all the mineralised domains was used for the variography. Directional variograms were poor therefore the downhole and horizontal planes were modelled. Lags of 50 m were used in the horizontal plane and 2 m for the downhole, both with a 50 % tolerance. In comparison to the previous model from 2012, the nugget is slightly reduced from 50 % to 46 %. The ranges are significantly reduced in the horizontal plane from 175 m to 47 m in the first range and 1000 m to 422 m in the second range. The variogram models from both 2012 and 2014 are summarised in Table 42. Variogram models in the horizontal plane and downhole directions were produced as illustrated by Figure 61 and summarised in the table below.

Figure 61 Variogram models for S % in horizontal plane and downhole directions

Table 42 Summary of variogram model for S % for 2014 and 2012

Year C0 C1 C2 Range 1 (m) Range 2 (m)

X Y Z X Y Z

2014 0.46 0.42 0.13 47 47 13 422 422 45

2012 0.50 0.26 0.24 175 175 6.5 1000 1000 55


78

13.3. Percentage Dark

13.3.1. Variogram Model

The previous model for the PC Dark was in 2012. The variography was revised for the additional data. The domained mineralised samples were used for the variography, as this was the zone of interest. The downhole/short range variogram was reasonable but stopped short of reaching the sill. The nugget and first range was used as a basis to fit the model in the horizontal plane in both the major axis along strike and semi major axis down dip. The experimental variogram and model are illustrated the figures below.

Figure 62 Variogram models in the horizontal and downhole directions for PC_DARK


79

The updated 2014 model has a higher nugget at 26% from 17%, this is still more or less in the range of a low nugget effect. In the horizontal plane the ranges have increased from 70 to 122 m and in the vertical direction they have increased to 62 m from 45 m.

Table 43 Variogram model for PC_DARK

Year C0 C1 C2 Range 1 (m) Range 2 (m)

X Y Z X Y Z

2012 0.17 0.31 0.51 11 5 4.75 70 70 45

2014 0.26 0.45 0.29 5.3 5.3 5.3 122 122 62


80

14. Grade Estimation

14.1. Quantitative Kriging Neighbourhood Analysis

14.1.1. Panel Size Selection

The main consideration of the block size is based on the drill spacing. Previous resource models from 2011 and 2012, used a block size of 50 x 50 x 10 m which was deemed suitable for the deposit (Nicholls & Rohwer, Omitiomire Resource Model, 2012). Subsequent to the 2012 model, a campaign of shallow oxide infill drilling to 25 x 25 m was carried out. In 2013 an oxide model utilised a block size of 25 x 25 x 5 m for selected potential pit areas, which through testing was deemed acceptable (Nicholls, Craton Omitiomire Oxide Resource Model, 2013). This model uses both block sizes of 50 x 50 x 10 m and 25 x 25 x 5 m. The smaller block size used in areas where there is 25 x 25 m drill coverage (Figure 10). The validation process has been carried out previously for both block sizes and the reader is referred to the relevant reports as stated above.

14.1.2. Search Distance

The search distances used were 90% of the maximum variogram range in each orthogonal direction for each domain. The optimisation of the search volume was determined by the minimum and maximum number of samples within the search volume.

14.1.3. Number of Samples

The number of samples used in the search volume was primarily used for the optimisation of the kriging neighbourhood. The search distances were set to 90% of the second structure variogram range and then testing various sample numbers in the neighbourhood. The kriging quality parameters such as the slope of regression, kriging variance and the negative kriging weights were used to determine the optimal minimum and maximum number of samples to be used. As with previous optimisation exercises the slope of regression was the main driver, used in conjunction with the kriging variance and some consideration was taken into account for the kriging efficiency. Each scenario was tested using the optimal test block position of the drillhole centred on the block and repeated for various drill spacing and block sizes as follows:

50 x 50 x 10 m block within 50 x 50 m drill spacing





81

Domain 1

Figure 63 Number of sample determination plots for Domain 1

Domain 2

Figure 64 Number of samples determination for Domain 2


82

Domain 3


Domain 5



83

Domain 8 The majority of the drilling spacing is approximately 25 x 25 m and subsequently the majority of the estimate is into 25 x 25 x 5 m blocks.


14.1.4. Discretisation

The discretisation points used was 6 x 6 x 5. This remains unchanged from previous estimates.

14.1.5. Kriging Sensitivities

Kriging sensitivity runs are necessary as the parameters are optimised on theoretical grids. A number of runs were conducted and each run analysed via statistics, visual examination and slice plots to further tweak the kriging parameters to ensure optimum results. A further check on the optimised parameters is to look at the histograms of the slope of regression. Some domains perform as expected with the majority of search volume (SV) 1 being over 60 % slope of regression. Domain 2, B lens East, as seen in Figure 68, shows that the optimised parameters have produced good slope of regression results.


84

Figure 68 Histogram of slope of regression for Domain 2

Some domains, such as the C lens, do not have the majority of the search volume 1 above 60 % slope of regression, as seen in Figure 69. This is mainly due to the drill spacing not being adequate for the majority of the domain and higher slopes of regressions will improve with increased drillhole information.

Figure 69 Histogram of slope of regression for Domain 4


85

14.1.6. Final Optimised Parameters

The final optimised kriging parameters used for the Cu % estimation are summarised in Table 44 below. A maximum of two search volumes were used and any blocks that remained un-estimated were assigned the declustered mean for the relevant domain.

Table 44 Summary of kriging parameters for the CU% estimation for the 50 x 50 x 10 m blocks D

om

ain

Sea

rch

rad

ii (

m)

No

. sam

ple

s

Sea

rch

Vo

lum

e 2

mu

ltip

lyin

g f

acto

r

No

. sam

ple

s

Dis

cre

tisati

on

(x

yz)


1 45 90 17 14 70 1.5 14 70 6x6x5

2 243 405 24 6 40 1.5 6 40 6x6x5

3 72 108 11 10 40 1.5 10 40 6x6x5

4 120 120 29 12 50 1.5 12 50 6x6x5

5 135 135 22 6 50 1.5 6 50 6x6x5

6 243 405 24 6 40 1.5 6 40 6x6x5

7 72 108 11 12 40 2 12 40 6x6x5

8 27 63 10 10 50 1.5 10 50 6x6x5

9 72 108 11 10 40 2 10 40 6x6x5

10 72 108 11 10 40 1.5 10 40 6x6x5

As the 25 x 25 m drilling only affects selected areas, the domains that were estimated on this block size are summarised in the table below.

Table 45 Summary of kriging parameters for the CU % estimation for the 25 x 25 x 5 m blocks

Do

main

Sea

rch

rad

ii (

m)

No

. sam

ple

s

Sea

rch

Vo

lum

e 2

mu

ltip

lyin

g f

acto

r

No

. sam

ple

s

Dis

cre

tisati

on

(x

yz)


1 45 90 17 14 70 N/A N/A N/A 6x6x5

5 135 135 22 6 30 N/A N/A N/A 6x6x5

6 243 405 24 8 40 N/A N/A N/A 6x6x5

8 27 63 10 8 50 N/A N/A N/A 6x6x5

14.2. Kriging

14.2.1. Kriging Setup

The method of Cu % estimation used for the Omitiomire deposit is Ordinary Kriging (OK). The search neighbourhood used was determined as described in section 14.1. Kriging was into full size parent blocks of 50 x 50 x 10 m or 25 x 25 x 5 m. Sub-celling was allowed along the mineralised boundaries to 5 x 5 x 1.25 m. The samples were composited to 2 m prior to kriging (see section 11.5). Each domain was kriged with its own samples from its respective domain, therefore there was no influence from samples in adjacent domains.


86

The resulting OK model is ‘om_201408_model_final’

14.2.2. Parameter Validation

All kriging parameters required for Datamine’s ESTIMA process were stored in csv files which were accessed by the modelling macro. The advantage to this is that the parameters can be accessed easily in a spreadsheet rather than hard coded into the macro. During the Dynamic Anisotropy process the angles dips and dip directions were visually checked on screen as well as filtering out any extreme angles and directions that did not fit in the geological model.

14.2.3. Model Validation

The model validation process involves visual checks in Datamine, statistical checks and slice plots of grade and tonnage throughout the model. The following west-east cross sections are of the Cu grade model and drillholes, one each in the south, central and central-northern part of the deposit, in Figure 70 to Figure 72. A north-south section is in Figure 73.


87

Figure 70 West-east cross section in southern area line 7582270 N


88

Figure 71 West-east cross section in northern central area line 7583570 N


89

Figure 72 West-east cross section in central area line 7583240 N


90

Figure 73 North-south cross section line 803300 E


91

Drillhole vs Model The declustered means are compared to the kriged block means, with the exception of domains 8 and 10 for which the drillhole statistical mean is used. Differences of ±5% would be considered acceptable. The largest domains volumetrically are 1 to 4 inclusive and account for 89% of the deposit. These four domains compare well to the declustered means. The summary of the comparison is in Table 46 below.

Table 46 Kriged vs sample mean grade comparison

Domain Domain Description Volume (m3) Domain as %

of deposit

Declustered Drillhole

Mean (Cu %)

Kriged Mean (Cu %)

Drillhole vs Kriged %

Difference

1 A lens 17 377 625 17% 0.60 0.59 -2%

2 B lens East 22 232 250 21% 0.59 0.62 5%

3 B lens West 23 864 250 23% 0.24 0.25 4%

4 C lens 29 206 875 28% 0.52 0.51 -2%

5 T Central lens 2 045 875 2% 0.57 0.53 -7%

6 Kaya 1 088 688 1% 0.33 0.32 -3%

7 Bruce lens 5 556 750 5% 0.34 0.30 -12%

8 Bruce Terrace lens 298 500 0.3% 0.81 0.82 1%

9 Mamba 609 500 1% 0.30 0.29 -3%

10 Tiger 2 424 625 2% 0.19 0.20 5%


92

Slice Plots Grade and tonnage validation slice plots were generated in the Easting, Northing and Elevation directions. The sample file and model were sliced into 100 m increments along the Easting and Northing and by 20 m along Elevation per domain. The grade validation slice plots for Domains 1, 2, 3 and 4 are illustrated in Figure 74 to Figure 77, these are volumetrically the largest. The validation plots presented here are in the northing and elevation only. The mean sample grades show a general approximation of the model which is to be expected.

Figure 74 Grade slice validation plots for Domain 1


93



94



95



96

14.2.4. Reconciliation with Previous Production

The project is not at the operating mine stage as yet, therefore no comparison can be made.

14.2.5. Density

Drillhole vs Model Comparisons were made between the drillhole density means and the interpolated density means for each domain. Table 47 below summarises the results and suggests a very good correlation between raw input and estimated values:

Table 47 Interpolated density vs sample mean comparison

Drillholes Blocks

DOMAIN No Samples Min Max Mean Volume Min Max Mean % Difference

- 37 803 2.00 3.01 2.75 9 349 117 000 2.00 2.88 2.76 0.4%

1 3 146 2.00 3.15 2.86 17 377 625 2.70 2.97 2.86 -0.1%

2 1 734 2.63 3.08 2.85 22 232 250 2.76 2.99 2.85 0.0%

3 2 443 2.00 3.69 2.83 23 864 250 2.70 3.07 2.83 0.0%

4 611 2.70 3.69 2.87 29 206 875 2.75 3.00 2.87 0.0%

5 766 2.64 3.13 2.89 2 045 875 2.77 2.99 2.88 -0.3%

6 141 2.73 2.99 2.85 1 088 688 2.77 2.91 2.84 -0.4%

7 125 2.71 3.17 2.83 5 556 750 2.73 2.94 2.84 0.1%

8 267 2.74 3.13 2.90 298 500 2.80 3.00 2.91 0.4%

9 84 2.73 3.03 2.84 609 500 2.77 2.93 2.86 0.6%

10 205 2.71 3.03 2.79 2 424 625 2.75 2.89 2.79 -0.1%

14.3. Geometallurgical Classification Models

14.3.1. Sulphur

The sulphur was estimated within the mineralised domain wireframes using Ordinary Kriging. The parameters were optimised in a similar way to the Cu % by setting the search ranges to 90% of the maximum variogram range and the minimum and maximum number of samples determined by the kriging quality graphs. The parameters used are summarised in Table 48.

Table 48 S% optimised estimation parameters

Block size (m)

Search radii (m) No. of

samples 2nd search

volume multiplier

No. of samples Discretisation


25x25x5 380 380 40 6 40 1.5 6 40 6x6x5

50x50x10 380 380 40 8 60 1.5 8 60 6x6x5

The estimation of S % was into full size parent blocks of 50 x 50 x 10 m as defined by the model prototype in Table 35. In order to model the S % profile correctly from the oxide to sulphide, three surfaces were used as kriging boundaries in the creation of the model:

Base of oxide – created by translating the topography wireframe 20 m below

Base of transitional – created by translating the topography surface to 40 m below

10 m below topography oxide surface


97

14.3.2. Percentage Dark

The percentage darkness was estimated within the mineralised domain wireframes using Ordinary Kriging. The kriging parameters were optimised first using the QAQC graphs and further refined in a number of test runs. The parameters used are summarised in Table 49. The search ellipses and variogram were orientated using Dynamic Anisotropy. Three search volumes were used to rank the quality of data available:

1st search volume - used only the logged Dark % values

2nd search volume - used logged data plus assigned means of the LITHO fields within the mineralised zone.

3rd search volume - logged plus assigned data with search volume multiplier of 2.5 times.

Table 49 Optimised kriging parameters for PC_DARK

Block size (m)

Search radii (m)

No. samples

Search Volume 2 multiplying factor

No. samples

Search Volume 3 multiplying factor

No. samples Discretisation

(xyz) X Y Z Min Max Min Max Min Max

25x25x5 110 110 8 8 40 0 10 60 2.5 10 60 5x5x3

50x50x10 110 110 52 10 60 0 10 60 2.5 10 60 5x5x3

Three search volume multipliers were used to ensure an estimate of PC_DARK was interpolated into all blocks. A confidence category of the PC_DARK estimate was assigned to field PCD_CAT based on the search volume as summarised in the table below.

Table 50 Classification categories of PC_DARK

PCD_CAT Description Definition

1 High confidence Search Volume 1

2 Medium confidence Search Volume 2

3 Very low confidence Search Volume 3


98

15. Classification

15.1. Classification Methodology

There is currently no single accepted standard in the industry for determining estimate quality on a block by block basis but practitioners typically use variables such as number of samples included within a block estimate or distance of samples from the estimated block as a measure of quality. Slope of Regression (SOR) is Bloy’s preferred guide in that this geostatistical variable is sensitive to a number of parameters including data density, distance from data as well as size of block and position of block relative to the drilling grid. The mean slope of regression per domain is shown in Table 51. Bloy usually considers values greater than 0.7 an acceptable minimum for an Indicated resource, though as low as 0.6 would be acceptable. The slope of regression of Measured material would be greater than 0.85 to 0.9. The SOR is used as a guide and other factors such as drill spacing, quality of data, geological interpretation and confidence in geostatistical parameters are also taken into account. The mean SOR by domain is summarised in Table 51 below.

Table 51 Mean Slope of Regression by domain

Domain Domain Description SOR

1 A lens 0.40

2 B lens East 0.87

3 B lens West 0.55

4 C lens 0.35

5 T Central lens 0.79

6 Kaya 0.77

7 Bruce lens 0.25

8 Bruce Terrace lens 0.65

9 Mamba 0.41

10 Tiger 0.37

The classification was reviewed only in areas where drilling post 2013 is present. Drilling undertaken between 2012 and 2013 was addressed in the Oxide Model (Nicholls, Craton Omitiomire Oxide Resource Model, 2013). As highlighted in section 14.1.5 in Figure 68 and Figure 69, the slope of regression can show high variability throughout the domain. Therefore it is important to review each domain with respect to the slope of regression in conjunction with other pertinent criteria such as drill spacing, search volume and other quality measurements. When classifying each domain the following criteria were considered:

Measured material - SOR ≥ 0.85, search volume = 1, generally 25 x 25 m drill spacing

Indicated material – SOR ≥ 0.6, search volume = 1, generally 50 x 50 m drill spacing

Inferred material – SOR < 0.6, search volume ≥ 1, drilling density 50 x 100 to 100 x 200 m

Exploration Target material – SOR < 0.6, search volume ≥ 2, drilling density > 100 x 200 m, i.e. very poorly sampled areas usually where strike extent is being tested and shows some geological continuity

The distribution of the slope of regression within the domains was not always consistent and where necessary, for continuity’s sake strings were used to delineate the categories. Strings were used for domains 1, 2, 3, 4, 5, 6 and 7.


99

Domain 1 / Measured Between 2012 and 2014 a campaign of infill drilling to 25 x 25 m, linking the Pan and Palm pit areas was undertaken. The interim oxide model in 2013 (Nicholls, Craton Omitiomire Oxide Resource Model, 2013), had some areas classified as Measured within the two separate pit areas. The slope of regression supports the extending of the Measured area to include the area between the pits as shown in Figure 78.

Figure 78 Domain 1: (left) model shown by SOR and Measured string in red; (right) model shown by

classification category

Domain 1 / Indicated Since the 2012 model the Indicated material of Domain 1 has been extended to include an area where drill spacing has been infilled to 25 x 25 m north west of the central area, as shown in Figure 79. This upgrade has remained the same since the 2013 oxide model. The mean SOR for this category is lower than the required 0.60 at 0.45. The boundaries of the Inferred and Exploration target material have remained unchanged since the 2012 model.

Pan pit area

Palm pit area

Extent of 2014

Measured


100

Figure 79 Domain 1: (left) model shown by SOR with Indicated (green) and Inferred strings (blue); (right) model

coloured by classification category

Domains 2, 3 & 4 The classification of these domains has remained unchanged since the 2012 model.

2014 additional Indicated

area


101

Domain 5 The oxide update in 2013 categorised an area in the north of the domain as Measured. This area of Measured could be extended due to infill drilling to 25 x 25 m to the north and west.

Figure 80 Domain 5: (left) model shown by SOR with Indicated (green) and Measured strings (red); (right) model

coloured by classification category indicating area where the Measured has been extended

Domain 6 The classification of this domain has not changed since the 2013 Oxide model.

Area of extended Measured category


102

Domain 7 The Inferred areas in this domain are within the 50 x 50m drill spaced areas. Additional to 2012, a new area in the north has been classified as Inferred, as shown in Figure 81.

Figure 81 Domain 7: (left) model coloured by SOR with Inferred strings in blue; (right) model coloured by

classification category

Domain 8 This domain has previously been classified as Indicated and thus remains so. Infill drilling to approximately 25 x 25 m in the north, an area previously with restricted access has increased the confidence of the model in this area. Domains 9 and 10, namely Mamba and Tiger are both classified as Exploration Targets. The resource classification categories in the model are coded as follows:

Table 52 Model classification categories

Classification category in model Description

1 Measured

2 Indicated

3 Inferred

4 Exploration Target

2014 additional Inferred area


103

15.2. Classification Validation

The sampling to volume ratio was calculated by domain and classification category. The results in Table 53 below show that generally speaking the domains with the higher sampling ratios are classified have higher levels of classification categories.

Table 53 Sampling to volume relationship by domain

Sampling/Volume Ratio (x104)

Domain % by tonnes

Total Tonnage Meas Ind Inf

Exp Target

1.80 A lens 8 43 32 17 49 660 507

0.78 B East lens - 75 11 14 63 364 559

1.01 B West lens - 83 13 4 67 578 836

0.20 C lens - - 15 85 83 687 481

3.74 T Central lens 11 65 24 - 5 891 155

1.30 Kaya - 10 90 - 3 086 551

0.22 Bruce lens - - 22 78 15 759 415

8.94 Bruce Terrace lens - 100 - - 869 234

1.38 Mamba - - - 100 1 741 545

0.85 Tiger - - - 100 6 758 588

The mean SOR by classification category and domain were calculated as shown in Table 54.

Table 54 Mean Slope of Regression by domain and classification field

Domain Domain Description

Slope of Regression

Measured Indicated Inferred Exploration

Target

1 A lens 0.91 0.45 0.22 0.16

2 B lens East 0.91 0.87 0.69

3 B lens West 0.58 0.26

4 C lens 0.70 0.26

5 T Central lens 0.94 0.86 0.52

6 Kaya 0.93 0.76

7 Bruce lens 0.40 0.14

8 Bruce Terrace lens 0.90

9 Mamba 0.41

10 Tiger 0.37


104

15.3. Key Criteria for Resource Classification

Classification of the estimates on a block-by-block basis in terms of confidence is only one component of the overall classification. The JORC Code, 2012 Edition, supplies Table 1, a “Checklist of Assessment and Reporting Criteria” for the purposes of summarising all key criteria affecting the confidence in the resource. The sections of the JORC table relevant to this report have been completed and supplied as Appendix 4.

15.4. Reconciliation with Previous Models

The addition of the new target Tiger, has increased the mineralised inventory by approximately 6.4 Mt at 0.2% Cu for 13 .7 kt of contained metal. This new target is classified as Exploration Target and does not form part of the Mineral Resource for Omitiomire as stipulated by the JORC code. The Tiger target is approximately 1 km from the main mineralised deposit and is a separate target at this stage of the development of Omitiomire deposit. Overall the mineral inventory at 0 % cut-off has decreased by 2% tonnes, though there has been a 4% increase in grade and corresponding 3% increase in contained metal, as summarised in Table 55.

Table 55 Model comparison with previous model with no cut-off - ALL DOMAINS

2014 Model 2012 Model % Difference

Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal

Measured 4 427 281 0.85 37 525 - - -

Indicated 130 052 765 0.43 555 436 142 930 164 0.41 585 411 -9% 4% -5%

Inferred 51 966 153 0.47 242 633 52 600 255 0.46 241 702 -1% 2% 0%

Exp Target 111 951 672 0.51 570 195 107 710 848 0.50 541 840 4% 1% 5%

Total 298 397 872 0.47 1 405 789 303 241 267 0.45 1 368 953 -2% 4% 3%

Considering only the Measured, Indicated and Inferred categories, there is a 5% decrease in the total tonnage from the 2012 model, the grade increased by 6% and 1% increase in the contained metal. This is summarised in Table 56 below.

Table 56 Model comparison with previous model for Measure, Indicated and Inferred - ALL DOMAINS

2014 Model 2012 Model % Difference

Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal

Measured 4 427 281 0.85 37 525 - - -

Indicated 130 052 765 0.43 555 436 142 930 164 0.41 585 411 -9% 4% -5%

Inferred 51 966 153 0.47 242 633 52 600 255 0.46 241 702 -1% 2% 0%

Total 186 446 199 0.45 835 594 195 530 419 0.42 827 113 -5% 6% 1%


105

16. Resource Tabulations

The following Resources are derived from the block model om_mod_201408_final. Table 57 represents the Measured and Indicated Resources of the Omitiomire deposit between cut-offs 0 and 0.5 % at increments of 0.05 %.

Table 57 Omitiomire Measured and Indicated Resources

Cut-off grade (%) Tonnes Grade Metal

(t) (%) (t)

0 134 480 046 0.44 592 961

0.05 134 376 115 0.44 592 916

0.1 133 197 272 0.44 591 976

0.15 127 661 470 0.46 584 645

0.2 114 285 052 0.49 561 015

0.25 97 807 337 0.54 523 762

0.3 84 139 863 0.58 486 433

0.35 72 664 755 0.62 449 124

0.4 61 105 639 0.66 405 907

0.45 50 370 613 0.72 360 150

0.5 42 349 925 0.76 322 189

Table 58 represents the Inferred Resources at cut-offs between 0 and 0.5 % at 0.05 % increments.

Table 58 Omitiomire Inferred Resources


(t) (%) (t)

0 51 966 153 0.47 242 633

0.05 51 943 482 0.47 242 627

0.1 51 614 987 0.47 242 331

0.15 49 466 018 0.48 239 508

0.2 46 146 032 0.51 233 781

0.25 39 098 770 0.56 217 261

0.3 36 500 200 0.58 210 085

0.35 31 584 161 0.61 193 805

0.4 28 274 105 0.64 181 381

0.45 24 900 440 0.67 167 002

0.5 21 403 924 0.70 150 436

Table 59 represents the Measured, Indicated and Inferred Resources at cut-offs between 0 and 0.5 % at 0.05 % increments.

Table 59 Omitiomire Measured, Indicated and Inferred Resources


(t) (%) (t)

0 186 446 199 0.45 835 594

0.05 186 319 596 0.45 835 543

0.1 184 812 259 0.45 834 307

0.15 177 127 488 0.47 824 153

0.2 160 431 084 0.50 794 796

0.25 136 906 107 0.54 741 023

0.3 120 640 063 0.58 696 518

0.35 104 248 916 0.62 642 929

0.4 89 379 743 0.66 587 288

0.45 75 271 053 0.70 527 152

0.5 63 753 849 0.74 472 625


106

The Resources at 0.25 % cut-off for the unconstrained model (om_mod_201408_final) are as follows:

Table 60 Omitiomire Indicated and Inferred Resources at 0.25 %

Cut-off %

Measured Indicated Inferred Total

Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal

(t) (%) (t) (t) (%) (t) (t) (%) (t) (t) (%) (t)

0.25 4 427 281 0.85 37 525 93 380 056 0.52 486 237 39 098 770 0.56 217 261 136 906 107 0.54 741 023

16.1. Resource Tabulations by Domain

The Resources at 0.25 % cut-off, by domain, excluding Exploration Targets Mamba and Tiger (D9 and 10).

Table 61 Resources by domain

Domain

Measured Indicated Inferred Total

Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal Tonnes Grade Metal

(t) (%) (t) (t) (%) (t) (t) (%) (t) (t) (%) (t)

1 3 796 690 0.82 31 020 21 140 747 0.62 130 574 14 050 811 0.60 84 347 38 988 248 0.63 245 940

2 43 844 453 0.57 249 428 7 099 301 0.61 43 119 50 943 754 0.57 292 547

3 23 497 336 0.34 80 474 965 409 0.37 3 529 24 462 745 0.34 84 003

4 10 750 481 0.58 62 368 10 750 481 0.58 62 368

5 630 591 1.03 6 505 3 746 675 0.47 17 498 1 415 918 0.48 6 856 5 793 185 0.53 30 859

6 292 004 0.41 1 197 2 175 016 0.34 7 403 2 467 020 0.35 8 601

7 2 641 835 0.36 9 639 2 641 835 0.36 9 639

8 858 840 0.82 7 065 858 840 0.82 7 065

Total 4 427 281 0.85 37 525 93 380 056 0.52 486 237 39 098 770 0.56 217 261 136 906 107 0.54 741 023


107

16.2. Grade Tonnage Curves

Grade tonnage curves for Measured and Indicated material in Figure 82 below.

Figure 82 Grade tonnage curves of Measured and Indicated material

Grade tonnage curves for Measured, Indicated and Inferred material, in Figure 83

Figure 83 Grade tonnage curves for Measured, Indicated and Inferred material


108

Grade tonnage curves for the total inventory (including Exploration Target), in Figure 84.

Figure 84 Total inventory: Measured, Indicated, Inferred and Exploration Target


109

16.2.1. Grade Tonnage Curves by Domain

The following grade tonnage curves are for the Measured, Indicated and Inferred material for the main Domains 1, 2, 3 and 4. Note: Only Domain 1, A lens, contains Measured material

Figure 85 Domain 1 grade tonnage curves



110




111

17. Exploration Target Material

The following Table 62 represents the tonnage, grade and metal Exploration Target material which is not sufficiently drilled to enable an Inferred or greater confidence level and cannot be included in the Mineral Resource inventory. The figures have been rounded to reflect the uncertainty in the estimate.

Table 62 Exploration Target material for Omitiomire grade and tonnage table


(Mt) (%) (kt)

0 112.0 0.5 570

0.05 111.8 0.5 570

0.1 110.9 0.5 569

0.15 108.3 0.5 566

0.2 103.0 0.5 557

0.25 96.2 0.6 541

0.3 89.6 0.6 523

0.35 73.0 0.6 467

0.4 66.7 0.7 443

0.45 62.0 0.7 424

0.5 59.2 0.7 410

Exploration Target material at a cut-off grade of 0.25% Cu is reported to be in the range of 76 to 155 Mt for 430 to 650 Kt of metal between 0.4 and 0.6 % grade. This represents areas that have been drilled but do not meet the confidence criteria for resource classification. The material this relates to is an extension to the currently defined mineralised zones of the deposit and Exploration Targets, Mamba and Tiger, in close proximity to the west and south west respectively of the deposit. The potential quantity and grade of the Exploration Target material remains conceptual in nature and may or may not be realised in the future.


112

18. Conclusions and Recommendations

Based on the site visits conducted by Bloy, reviews of the reports available, data received and work completed to date on the project, the following are the conclusions of Bloy:

Craton have carried out systematic infill programmes since the previous MRE in 2012. The main focus has been on shallow oxide drilling particularly in the central area relating to the A and T lenses. The 25 x 25 m drilling covers an area of approximately 150 x 725 m and has built on IBML’s Phase 1 Oxide Definitive Feasibility Study which encompassed several potential pit areas throughout the deposit. Phase 1 was modelled in November 2013 as part of the Oxide Definitive Feasibility Study.

Drilling in the north of the Mamba Exploration Target has effectively closed off the mineralisation. A new target Tiger, located approximately 1 km south west of the main deposit, was discovered.

There was no major re-interpretation of the geology and the lenses remain the same as the previous model. The domain wireframes were updated for drilling and the result has been an overall reduction of 4% in volume.

There are adequate procedures in place for drilling, sampling, data capture and data storage, all of which are believed to be followed. The RC sub-sampling was witnessed and was found to follow the procedure.

Craton follow a suitable QAQC programme for the level of exploration drilling it undertakes with an insertion rate of 20% for quality control samples and submit samples for re-assay at an Umpire laboratory for both Cu and S. To be noted that the insertion rate for this time period is a little lower at 16% due to the high number of short holes. The CRM near the cut-off grade performs well and does not indicate any bias or laboratory drift. The CRM’s at other levels do not perform so well and need to be continually monitored. The repeatability of the samples is very good and there is no evidence of contamination in the sample preparation of the laboratory.

The additional drilling has allowed for the confidence to be increased sufficiently in the central 25 x 25 m drilled area to be classified as Measured. Of the total Resource, the Measured makes up 3% of the deposit, Indicated 68 % and the remaining 29% is Inferred.

The Exploration Target material adds approximately 76 to 155 Mt for 430 to 650 Kt of metal between 0.4 and 0.6 % grade. Of this the new Exploration Target Tiger constitutes 2% with the majority coming from C lens at 68%.

As has been recommended in the previous report, it is felt that a 3D geological model outlining the main structures would be beneficial to increase the confidence in the geological/mineralisation model. The location of faults strongly influences the mineralisation zones and would thus increase confidence in the local estimate. As previously recommended, to increase the confidence in the resource estimate at Bruce Terrace, infill drilling to at least 12.5 x 12.5 m should be undertaken. This is to improve the geological interpretation of this lens.


113

19. Signature Page

Peter Bloy Principal Consultant MAusIMM no: 210408

Carrie Nicholls Senior Evaluation Geologist MAusIMM no: 222584

Michael Rohwer Senior Evaluation Geologist MAusIMM no: 310140 Professional Natural Scientist, SACNASP no: 400117


114

20. References

Basil Read Matomo. (2013). Craton Mining and Exploration Definitive Feasibility Study. Hellman & Schofield Pty Ltd. (2010). Omitiomire Resource Evaluation Report. Nicholls, C. (2011). Bloy Omitiomire Resource Model - 201110. Nicholls, C. (2013). Craton Omitiomire Oxide Resource Model. Nicholls, C., & Rohwer, M. (2012). Omitiomire Resource Model. Rohwer, M., & Nicholls, C. (2012). Omitiomire Site Visit Note. Steven, N., Armstrong, R., Smalley, T., & Moore, J. (2000). First Geological Description of a Late Proterzoic

(Kibaran) Metabasaltic Andesite-hosted Chalcocite Deposit at Omitiomire, Namibia. Geology and Ore Deposits:The Great Basin and Beyond Proceedings Volume II, (pp. 711-734).


115

Appendices

Appendix 1: File Listing

Description File name

Wireframes:

Mineralised wireframes omwf_201407_mzonept,tr

Topography omwf_2014_topopt,tr

Base of oxide omwf_2014_booxpt,tr

Base of transitional omwf_2014_botranspt,tr

10m below surface omwf_2014_10mpt,tr

Drillholes:

Raw input assay drillhole file omde_201407_assay

Kriging drillhole file omdk_201407_assay_2m

Classification strings:

Domain 1 Inferred string d1c3_2012st

Domain 1 Indicated string d1c2_2012st

Domain 1 Measured string d1c1_2014st

Domain 2 & 3 Inferred string d2c3_2012st

Domain 2 & 3 Indicated string d2c2_2012st



Domain 5 Measured string d5c1_2014st



External csv files:

Domains omitdomains.csv

Variogram parameter file for Cu% om_okgr_vpar.csv

Search parameter file for Cu% om_okgr_spar.csv

Estima parameter file for Cu% om_okgr_epar.csv

Search parameter file for dynamic anisotropy om_dagr_spar.csv

Estima parameter file for dynamic anisotropy om_dagr_epar.csv

Final model file:

OK model om_mod_201408_final


116

Appendix 2: Laboratory details

Genalysis Laboratories POSTAL ADDRESS: P.O. Box 144, Gosnells, Western Australia 6990 TELEPHONE: +61 8 9251 8100 FACSIMILE: +61 8 9251 8110 Email: [email protected] Website: www.genalysis.com.au Intertek Cilandak Commercial Estate Building 103E Jl. Cilandak KKO Jakarta Selatan Jakarta Indonesia, 12560 T: +62 21 7808011 F: +62 21 7807929 Setpoint Address: 30 Electron Avenue, Isando, 1601, Johannesburg, Gauteng, South Africa Postal: P.O.Box 856, Isando, Johannesburg, Gauteng, 1600, South Africa Telephone: +27 11 923-7000 | +27 11 923-7009 Bureau Veritas BV Mineral Laboratories, Swakopmund, cnr Newton & Einstein New Industrial Area Telephone +264 64 419 440 Facsimile +264 64 419 441 ALS Global ALS Johannesburg 53 Angus Crescent Long Meadow Business Park, East Entrance Edenvale South Africa +27 11 608 0555 Letter of accreditation for Bureau Veritas, Swakopmund, Namibia:


117


118


119

Appendix 3: Variogram Models

Domain 2 – B lens east (a) Downhole direction (b) Along strike direction (c) Down dip direction


120

Domain 3 - B lens west (a) Downhole direction (b) Along strike direction



121

Domain 8 – Bruce Terrace (a) Downhole direction (b) Along strike direction



122

Appendix 4: JORC Checklist of Reporting Criteria

JORC Code, 2012 Edition – Table 1 Checklist of Assessment and Reporting Criteria

Section 1 Sampling Techniques and Data

Criteria JORC Code explanation Commentary

Sampling techniques

Nature and quality of sampling (e.g. cut channels, random chips, or specific specialised industry standard measurement tools appropriate to the minerals under investigation, such as down hole gamma sondes, or handheld XRF instruments, etc). These examples should not be taken as limiting the broad meaning of sampling.

Include reference to measures taken to ensure sample representivity and the appropriate calibration of any measurement tools or systems used.

Aspects of the determination of mineralisation that are Material to the Public Report.

In cases where ‘industry standard’ work has been done this would be relatively simple (eg ‘reverse circulation drilling was used to obtain 1 m samples from which 3 kg was pulverised to produce a 30 g charge for fire assay’). In other cases more explanation may be required, such as where there is coarse gold that has inherent sampling problems. Unusual commodities or mineralisation types (eg submarine nodules) may warrant disclosure of detailed information.

Of the 95 772 m drilled, 17 192 m is diamond core; 73 442 m is reverse circulation 4 306 m are percussive and 832 m are RAB.

Handheld XRF Niton instrumentation is used to scan a drill hole in its entirety. From this, samples are selected for assay at Bureau Veritas laboratory in Swakopmund. “Enveloping” samples (essentially un-mineralized samples above and below the interpreted mineralization) are included within the submission of a set of intervals considered potentially mineralized.

In the case of core the handheld XRF machine is passed over the core for measurement in 10 cm intervals, whereas in the case of the RC chips, the XRF instrument is mounted on a base and the sample bag placed on the plate for measurement.

The XRF instrument is calibrated before each new drillhole using three certified standards.

This method of identifying mineralization intervals has proven to be reliable and comparable (although grade-wise not directly on a 1:1 ratio) to actual assayed mineralisation.

The sampling methods, process flows and laboratory procedures for both diamond-drilled core and RC samples are extensively described within the “Sampling Methods” and “Sample Assaying” sections within the Evaluation Report (Chapters 7 and 8 respectively)

Drilling techniques

Drill type (eg core, reverse circulation, open-hole hammer, rotary air blast, auger, Bangka, sonic, etc) and details (eg core diameter, triple or standard tube, depth of diamond tails, face-sampling bit or other type, whether core is oriented and if so, by what method, etc).

Reverse circulation using 950 to 110 psi compressors; diameters vary from 134 to 119 mm.

Diamond drilling using wireline rigs. NQ diameter diamond core for assaying; ±6 geotechnical holes at HQ for SRK; 2 HQ for oxide processing test work in 2012; PQ tails undertaken through, mineralised zone for sulphide processing testwork in 2012.

Rotary Air Blast used to delineate targets, mainly Bruce Terrace and Mamba.

Majority (98%) of drillholes are vertical; inclined holes are surveyed


123


by Reflex multi-shot tool and downhole optical camera system

Drill sample recovery

Method of recording and assessing core and chip sample recoveries and results assessed.

Measures taken to maximise sample recovery and ensure representative nature of the samples.

Whether a relationship exists between sample recovery and grade and whether sample bias may have occurred due to preferential loss/gain of fine/coarse material.

Chip sample recoveries are measured by weighing entire metre sample and comparing the theoretical weight expected. These sample weights are also logged.

For RC sampling, the supervising geologist ensures a good sample recovery by approaching the drill operator when the total sample weight drops between 28-30kg, acceptable recovery is expected above 30 kg.

Core recoveries are determined by measuring recovered core length compared to expected length and a percentage recovery is calculated.

Top 2 m are expected to be poor recovery due to the unconsolidated nature of the overlying soils.

No investigation has been made into whether a relationship between sample recovery and grade exists, though there is no reason to expect one. The global core recovery would be dictated only by lithology – locally some structure may be influential. In the case of RC, the only area where this may be applicable is if there is a greater loss of fines through the cyclone during the drilling within the upper oxide material, having been weathered to fine-grained clay – however, this is unlikely to have any noticeable influence.

Logging Whether core and chip samples have been geologically and geotechnically logged to a level of detail to support appropriate Mineral Resource estimation, mining studies and metallurgical studies.

Whether logging is qualitative or quantitative in nature. Core (or costean, channel, etc) photography.

The total length and percentage of the relevant intersections logged.

Standard pre-drilling produced drill-sheets are used as part of the logging procedures to capture drilling related information.

Standard pre-drilling produced logging sheets are used as part of the geological logging procedures to capture the geological information.

The sampling packaging is prepared pre-drilling along with the drill-log and logging sheets.

Core is photographed wet and dry.

To maintain consistency during logging, examples of all the lithologies likely to be encountered at Omitiomire are available for comparison, both as RC chip samples and as core.

The entire process of logging, sampling and sample send-off from site for a drillhole, is supervised from start to finish by one geologist, also to maintain consistency.

Mineralised intersections are generally quite visible to the specific site-experienced geologists as; 1. they have become accustomed to the tell-tale signs of certain

mineral assemblages


124


2. there is a definite tendency for mineralisation to be hosted within the darker coloured lithologies

Further confirmation of mineralised intervals is provided through the use of the handheld XRF scanner and the logging of the results. This method of identifying mineralisation has proven to be reliable and comparable (although grade-wise not directly on a 1:1 ratio) to actual assayed mineralisation.

It should be noted that CME replaced a drill contractor after spurious drill depths were being reported. All holes drilled by this contractor were re-logged entirely.

All logging is conducted quantitatively.

Sub-sampling techniques and sample preparation

If core, whether cut or sawn and whether quarter, half or all core taken.

If non-core, whether riffled, tube sampled, rotary split, etc and whether sampled wet or dry.

For all sample types, the nature, quality and appropriateness of the sample preparation technique.

Quality control procedures adopted for all sub-sampling stages to maximise representivity of samples.

Measures taken to ensure that the sampling is representative of the in situ material collected, including for instance results for field duplicate/second-half sampling.

Whether sample sizes are appropriate to the grain size of the material being sampled.

The core is orientated and marked with an orientation line. The core is sawn in half and the southern half is always submitted for assay.

Dry 1m RC samples are split using a large riffle splitter. One split is then re-riffled to a 1/16th to produce an “A” and a “B” sample. “B” samples are stored while “A” samples a split again to produce a 1 in 32 fraction, which is packaged and sent to the labs for assay if selected.

Results of rig/field duplicates are described within the “Assay QAQC” sections of the Evaluation Report – Chapter 9, sub-section 9.2.3 Duplicates”

Analysis of size fractions indicate that the RC samples are on average 89% < 2mm and as such a 1kg riffle split of 32kg is considered appropriate prior to milling

Quality of assay data and laboratory tests

The nature, quality and appropriateness of the assaying and laboratory procedures used and whether the technique is considered partial or total.

For geophysical tools, spectrometers, handheld XRF instruments, etc, the parameters used in determining the analysis including instrument make and model, reading times, calibrations factors applied and their derivation, etc.

Nature of quality control procedures adopted (eg standards, blanks, duplicates, external laboratory checks) and whether acceptable levels of accuracy (ie lack of bias) and precision have been established.

Cu and S analysis carried out by Bureau Veritas, Swakopmund, Namibia. Samples are leached using four acid total digestion and analysed by ICP-OES. The laboratories and associated assay techniques were not directly assessed but related documentation outlining these procedures are available.

As per standard practice, standard, blank and duplicate samples were added to batches of submitted samples sent to various laboratories for quality control assaying. The QC procedures and analysis are extensively outlined within the associated section 9 “Assay QAQC” of the Evaluation Report.

Comparisons of the assay results provided, by HARD and scatter plots of rig as well as lab sample duplicates indicate a satisfactory level of repeatability.


125


The results of umpire laboratory duplication indicates a satisfactory level of repeatability.

The assay results of blanks inserted during the latter half of 2007 to 2009 contain some spuriously high results. This was attributed to the use of a locally sourced white-gneissic material from a bulk-sampling pit, mistakenly believed to be completely blank. The assay associated results from 2010-2011 indicate this problem was rectified. Subsequently, within the latest campaign, the use of “blank” silica river sand as a replacement to a commercially available certified blank has proven unsuitable.

Some variability was noted within the assay results of standards submitted to particularly Genalysis in Perth during 2008-2009.

Some variability was also noted within the assay results of standards submitted subsequently 2010-2014.

Verification of sampling and assaying

The verification of significant intersections by either independent or alternative company personnel.

The use of twinned holes.

Documentation of primary data, data entry procedures, data verification, data storage (physical and electronic) protocols.

Discuss any adjustment to assay data.

Site visit observation of particular core intersections confirms the presence of significant mineralisation. Also, the recently excavated bulk sampling pit visually indicates intersection of both mineralization as well as interpreted structure.

While no twinning to specifically verify reported intersections has been conducted, continuity of both mineralisation and lithological intersections is evident across neighbouring drillholes at short drill-spacings.

Primary data entry and subsequent database cross-examination is outlined in section 10.3 Data Verification, of the Evaluation Report.

As intervals reported as “below detection” by the laboratory are identified/highlighted as a negative value, such intervals have been assigned half the detection limit value.

Location of data points

Accuracy and quality of surveys used to locate drill holes (collar and down-hole surveys), trenches, mine workings and other locations used in Mineral Resource estimation.

Specification of the grid system used.

Quality and adequacy of topographic control.

A contracted land surveyor conducts regular surveys of batches of completed holes during which the exact drill-hole locations are captured using a differential GPS.

Several drill-locations were verified by checking the co-ordinates displayed on the paper-hardcopy drill- or logging sheets located within the geology office on site, and looking for the corresponding BHID in the field, at the reflected co-ordinates.

Specifics of the co-ordinate grid system used as well as the Topographic control is extensively outlined within the “Survey Control” section within the Evaluation Report (sub-section 5.6.3)


126


Data spacing and distribution

Data spacing for reporting of Exploration Results.

Whether the data spacing and distribution is sufficient to establish the degree of geological and grade continuity appropriate for the Mineral Resource and Ore Reserve estimation procedure(s) and classifications applied.

Whether sample compositing has been applied.

The exploration phases of the drilling were designed on a 100m x 100m grid while a large proportion of the interpreted aerial extent of the mineralisation has been infilled to a 50m x 50m grid. Preferential oxide targets have been infilled to 25m x 25m.

Drilling has been designed to strictly maintain straight E-W drill-lines to allow for accurate section interpretations. These allow for prediction of orebody continuity that is tested by drilling. Current geological interpretation adequately defines the continuity of the orebodies and the 50m x 50m infill drilling satisfies continuity ranges expected from the variography of the orebodies.

Drill spacing is considered to hold significant weight during the assignation of Resource Classification.

Grade intervals have been composited to 2 m. The compositing was run separately within each domain (or lens) wireframe.

Orientation of data in relation to geological structure

Whether the orientation of sampling achieves unbiased sampling of possible structures and the extent to which this is known, considering the deposit type.

If the relationship between the drilling orientation and the orientation of key mineralised structures is considered to have introduced a sampling bias, this should be assessed and reported if material.

The structural control of mineralisation is well understood and drilling orientations are suitably oriented perpendicularly to such structures.

Declustering analysis as per section 11.4 within the Evaluation Report describes the potential influence of biased drill spacing and orientation. In this case, the effects seem of minimal influence.

Sample security

The measures taken to ensure sample security. A 2m high fence surrounds the camp where all drill samples are transported. All access to the camp is restricted through a 24 h manned gate where all movement of vehicles and personnel is documented upon entry and exit. CME staff transport samples for laboratory submission to the offices in Windhoek from where these are moved by registered transport to the various laboratories.

Audits or reviews

The results of any audits or reviews of sampling techniques and data. Outside of the standard site visit observation of sampling techniques and practices and the subsequent analysis of sampling QAQC data, no specific audits or review results are known of.


127

Section 3 Estimation and Reporting of Mineral Resources


Database integrity

Measures taken to ensure that data has not been corrupted by, for example, transcription or keying errors, between its initial collection and its use for Mineral Resource estimation purposes.

Data validation procedures used.

Data validation during the desurvey process checked for duplication, over-lapping samples, missing surveys and collars. Minor discrepancies were reported to the database manager who rectified them.

Database checks were made against hard copies for a total of 26 drillholes, comprising 10% of 2014 drilling and approximately 3% of the total database. One drillhole was found to be mis-logged by 1m otherwise no other errors were found.

Note that hardcopy validation occurred after processing in Datamine to ensure that manipulation of data (domaining) did not introduce error

Site visits Comment on any site visits undertaken by the Competent Person and the outcome of those visits.

If no site visits have been undertaken indicate why this is the case.

No site visit was undertaken by the primary Competent Person (Carrie Nicholls) but Michael Rohwer has undertaken two site visits, one between 13-15th February 2012 and the second from 26-30th May 2014. The purpose of these visits was to ensure that the documented procedures were being followed and allow inspection of the drilling, logging and sample storage facilities. The result of the visits was that adequate procedures were in place and that they were being correctly followed. The physical locations of a number of collars were verified using a handheld GPS.

Geological interpretation

Confidence in (or conversely, the uncertainty of ) the geological interpretation of the mineral deposit.

Nature of the data used and of any assumptions made.

The effect, if any, of alternative interpretations on Mineral Resource estimation.

The use of geology in guiding and controlling Mineral Resource estimation.

The factors affecting continuity both of grade and geology.

The geological interpretation is led by a team of experienced geologists. Numerous maps as well as a set of 50 m interval, W-E section interpretations and longer S-N sections representing the entire deposit, are continuously updated as new data is received. These, as well as regional interpretations of the geology complement the interpretation.

Confidence in the current geological interpretation is high.

Data is well spaced is from a minimum of 25 x 25 m to 100 x 200 m and coverage is adequate throughout the deposit.

Increased grade seems to be associated with deformation intensity – specifically shear-associated deformation (often tightly folded), and confined to the melanocratic schists and gneisses.

The mineralised lenses are very much controlled by dark mafic rocks, which is used in conjunction with a cut-off grade of 0.25% to


128


delineate the mineralised lenses. The light felsic rocks are generally barren.

The mineralised lenses are digitized in Datamine software taking into account faults that are interpreted on paper from drillhole analysis.

Dimensions The extent and variability of the Mineral Resource expressed as length (along strike or otherwise), plan width, and depth below surface to the upper and lower limits of the Mineral Resource.

The mineralisation occurs in 8 stacked lenses with an overall strike length of 3.7 km and a width of 1 km. The mineralisation starts from surface and has been projected to a depth of 600 m from surface. The individual lenses vary in thickness and are generally between 10-30m, though they can be up to 90 m in thickness. The deposit strikes north-south and generally dips approximately 15° to the east. See Figures 3, 4 and 10 of the report.

Estimation and modelling techniques

The nature and appropriateness of the estimation technique(s) applied and key assumptions, including treatment of extreme grade values, domaining, interpolation parameters and maximum distance of extrapolation from data points. If a computer assisted estimation method was chosen include a description of computer software and parameters used.

The availability of check estimates, previous estimates and/or mine production records and whether the Mineral Resource estimate takes appropriate account of such data.

The assumptions made regarding recovery of by-products.

Estimation of deleterious elements or other non-grade variables of economic significance (eg sulphur for acid mine drainage characterisation).

In the case of block model interpolation, the block size in relation to the average sample spacing and the search employed.

Any assumptions behind modelling of selective mining units.

Any assumptions about correlation between variables.

Description of how the geological interpretation was used to control the resource estimates.

Discussion of basis for using or not using grade cutting or capping.

The process of validation, the checking process used, the comparison of model data to drill hole data, and use of reconciliation data if available.

The estimation was of copper undertaken in Datamine by Ordinary Kriging. Two block sizes were used: 50 x 50 x 10 m for the majority of the deposit and a smaller size of 25 x 25 x 5 m in areas of 25 x 25 m drilling. The blocks were subcelled to the mineralised boundaries to 5 x 5 x 1.25 m.

The estimation was into 8 domains that were interpreted by Karl Hartman based on geological contacts and a cut-off grade of 0.25%. The B lens is interpreted as one lens but is divided and estimated as two lenses based on a grade difference between two areas. The east is of higher grade than the west. Two further domains, Mamba and Tiger, were part of the estimation. They are in close proximity to the deposit but are Exploration Targets and do not form part of the Resource.

Samples were composited to 2 m prior to estimation.

Extreme values do not generally pose a risk on this deposit though one domain (Bruce lens) had its values capped to 1.11% to decrease effect of the unsupported high values.

Not all samples are assayed and where missing assays exist they were set to half the detection level as the interval is assumed to be barren.

Variogram models for 6 of the domains were determined. Where a model could not be fitted, a model was applied based on its statistical similarity to a modelled domain.

All variogram models were double structure spherical models. All models are considered to be moderate to good quality. The nugget of the models ranged from 14% to 51%. The second search ranges along strike from 70 to 450 m; down dip from 30 to 270 m and in the


129


vertical axis 11 to 29 m (See Table 39 in report).

Search parameters for 50 x 50 x 10 m block: 90% of the second variogram range and the minimum number of samples used between 6 and 14 and the maximum between 40 and 70. A second search volume multiplying factor of 1.5 to 2 was used. Blocks with no estimates were applied a declustered mean determined by domain. See Table 44 in report.

Search parameters for 25 x 25 x 5 m block: 90% of the second variogram range and the minimum number of samples used between 6 and 14 and the maximum between 30 and 70. No second search volume was used. See Table 45 in report.

All variograms and search volumes were locally orientated by dynamic anisotropy.

Two previous Resource Models for Omitiomire have been estimated by the Competent Person. These have been used as a basis for the generation of the current Resource Model.

No other by-products are produced.

There are no deleterious elements.

Geometallurgical fields for sulphur (S%) and Percent Dark (PC_DARK) were interpolated into the model. The S% is required for oxidation distribution. PC_DARK, percent of dark rocks present, is required for use in the Dense Medium Separation during the mineral processing.

The block size was based on the drill spacing: 50 x 50 x 10 m was tested as the most suitable based on the majority of the deposit at 50 x 50 m drill spacing. The block height of 10 m was selected based on the typical thickness of the domains being between 10 and 30 m. The smaller block size of 25 x 25 x 5 m was used in areas of 25 x 25 m drilling. The aim of the smaller block size was to increase the selectivity in localised areas where close (25 x 25 m) spaced drilling was present.

Slice plots by domain were created by northing and elevation to validate the model against the drillholes and showed reasonably good correlation. The model is typically smoother than the drillholes.

Comparison of the means of the drillholes and model by domain compare well. The largest domains 1 to 4 were within 5% of the drillhole declustered means.

Visual validation onscreen in Datamine of the drillholes and model was also used to check the performance of the model, and was found


130


to give a reasonably good local estimate.

Moisture Whether the tonnages are estimated on a dry basis or with natural moisture, and the method of determination of the moisture content.

The tonnages are estimated on a dry basis.

Cut-off parameters

The basis of the adopted cut-off grade(s) or quality parameters applied.

The cut-off grade applied for the reporting of the Mineral Resources was supplied by Craton at 0.25%. At this cut-off the domains represent coherent mineralised bodies that can be modelled and amenable to mine planning. No further economic considerations were given to the adopted cut-off grade but grade tonnage curves have been supplied to examine the effect of increase in cut-off

Mining factors or assumptions

Assumptions made regarding possible mining methods, minimum mining dimensions and internal (or, if applicable, external) mining dilution. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider potential mining methods, but the assumptions made regarding mining methods and parameters when estimating Mineral Resources may not always be rigorous. Where this is the case, this should be reported with an explanation of the basis of the mining assumptions made.

The expected mining method of this deposit is by surface mining.

Since the modelling method was based on discrete, deterministic mineralised zones, no further modelling of internal mining dilution took place and “Recoverable Resource” techniques such as Multiple Indicator Kriging or Uniform Conditioning were not applied. As such there have been no assumptions on minimum mining dimensions introduced into these resource tabulations.

The reported Resources are not constrained within any form of resource limiting pit shell and as such there is potential for a portion of the resources to fall outside of economic pit limits

Metallurgical factors or assumptions

The basis for assumptions or predictions regarding metallurgical amenability. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider potential metallurgical methods, but the assumptions regarding metallurgical treatment processes and parameters made when reporting Mineral Resources may not always be rigorous. Where this is the case, this should be reported with an explanation of the basis of the metallurgical assumptions made.

No metallurgical factors or predictions of processing amenability have been incorporated into the model or final resource tabulations.

Environmen-tal factors or assumptions

Assumptions made regarding possible waste and process residue disposal options. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider the potential environmental impacts of the mining and processing operation. While at this stage the determination of potential environmental impacts, particularly for a greenfields project, may not always be well advanced, the status of early consideration of these potential environmental impacts should be reported. Where these aspects have not been considered this should be reported with an explanation of the environmental assumptions made.

Environmental factors have been addressed by Craton in their Definitive Feasibility Study (‘DFS’), completed on the Phase 1 oxide copper project in 2013. No assumptions have been made in the generation of the current Omitiomire resource.


131


Bulk density Whether assumed or determined. If assumed, the basis for the assumptions. If determined, the method used, whether wet or dry, the frequency of the measurements, the nature, size and representativeness of the samples.

The bulk density for bulk material must have been measured by methods that adequately account for void spaces (vugs, porosity, etc), moisture and differences between rock and alteration zones within the deposit.

Discuss assumptions for bulk density estimates used in the evaluation process of the different materials.

Gas pycnometry was used to measure the specific gravity of the drill sample pulp (already milled) materials. This technique uses gas displacement to measure volume (and hence density). The sample to be measured is sealed in the instrument compartment of known volume, helium gas is admitted, and then expanded into another compartment. The pressure, before and after expansion, is measured and used to calculate the sample volume. Dividing this volume into the sample weight gives the gas displacement density or specific gravity (SG) of the material. The value is considered representative of the full sample interval. 7 513 samples were measured throughout the deposit using this method of determination.

The majority (80%) of the measurements are taken in the mineralised zone and are therefore biased towards the dark lithologies.

Regression equations were calculated for the main rock types for the relationship between grade and density. The density was calculated for samples where no gas pycnometer measurement was taken.

Average bulk densities were assigned to the lithologies for which no density was determined.

While density determination by gas pycnometer does not take porosity into account, most samples at Omitiomire are from solid, metamorphic rocks, and thus porosity should not be considered a factor in fresh rock. Inspection of a bulk sampling box-cut and some oxide core, indicated that the oxidised material near surface is weathered to clay and that no significant porosity was introduced through oxidation of the material.

Classification The basis for the classification of the Mineral Resources into varying confidence categories.

Whether appropriate account has been taken of all relevant factors (ie relative confidence in tonnage/grade estimations, reliability of input data, confidence in continuity of geology and metal values, quality, quantity and distribution of the data).

Whether the result appropriately reflects the Competent Person’s view of the deposit.

The basis of the classification of the deposit has taken into account the slope of regression, drill spacing, quality of estimate, confidence in the local geological interpretation and confidence in geostatistical parameters.

When classifying each domain the following quantitative criteria were considered (where SOR = estimated Slope of Regression):

o Measured material - SOR ≥ 0.85, search volume = 1, generally 25 x 25 m drill spacing

o Indicated material – SOR ≥ 0.6, search volume = 1, generally 50 x 50 m drill spacing

o Inferred material – SOR < 0.6, search volume ≥ 1, drilling density 50 x 100 to 100 x 200 m


132


Each domain was classified individually using the above criteria as a nominal guideline. The confidence in the geostatistical parameters and local geological interpretation were equally important.

The result does appropriately reflect the Competent Person’s view of the deposit.

Audits or reviews

The results of any audits or reviews of Mineral Resource estimates. No audits or reviews have been undertaken on this Resource Estimate

Discussion of relative accuracy/ confidence

Where appropriate a statement of the relative accuracy and confidence level in the Mineral Resource estimate using an approach or procedure deemed appropriate by the Competent Person. For example, the application of statistical or geostatistical procedures to quantify the relative accuracy of the resource within stated confidence limits, or, if such an approach is not deemed appropriate, a qualitative discussion of the factors that could affect the relative accuracy and confidence of the estimate.

The statement should specify whether it relates to global or local estimates, and, if local, state the relevant tonnages, which should be relevant to technical and economic evaluation. Documentation should include assumptions made and the procedures used.

These statements of relative accuracy and confidence of the estimate should be compared with production data, where available.

The Slope of Regression is a measure of the quality of the estimate and was used as a check for each classification category. Whilst not all domains adhered strictly to the criteria used for the classification, the slope of regression increased for increasing classification category. See Table 54 in the report.

The sampling/volume ratio of each estimation domain was calculated. Higher-confidence classification category was associated with increasing sampling/volume ratios, which would be expected.

The statement of the resources relates to local estimates.

No mining has taken place therefore no comparison to production data can be made.

craton mining & exploration pty ltd datamine during the de-survey process. 10% of the 2014...

Documents