M10 Technical Report june10 final · 2020. 3. 6. · estimation work undertaken using SURPAC (Version 6.1.3) mining software. The M10 Mineral Resources have been classified as Inferred

Cube Resource Review, June 2010 Page 1 of 33

M10 PROJECT

RESOURCE ESTIMATE

SUMMARY TECHNICAL REPORT

July 2010

PREPARED FOR

EXCALIBUR MINING CORPORATION LIMITED

© Cube Consulting Pty Ltd

Perth, Western Australia

Cube Project: 2010_040

www.cubeconsulting.com.au

Excalibur Mining Corporation

M10 Resource Estimate – July 2010


Prepared By: Reviewed By:

Jason Harris Ted Hansen

BSc GradDip (Fin) MAIG BSc (Geology) MAusIMM

Senior Consulting Geologist Director – Geological Projects

…………………………………..... …………………...……………………

Distribution: Number of Copies

Excalibur Mining Corporation 1

Cube Consulting Pty Ltd 1

Cube Consulting Pty Ltd

ABN 84 094 321 829

Level 4, 1111 Hay Street

West Perth WA 6005

Phone: +61 8 9442 2111

Website: www.cubeconsulting.com.au




TABLE OF CONTENTS

1.0 EXECUTIVE SUMMARY ................................................................................................... 6

2.0 INTRODUCTION................................................................................................................ 8

3.0 LOCATION AND GEOLOGY ............................................................................................. 8

4.0 RESOURCE MODEL DATABASE .................................................................................... 9

4.1 DRILLING DATABASE ............................................................................................................ 9

4.2 SURVEY ............................................................................................................................ 11

4.2.1 Historical data ............................................................................................................ 11

4.2.2 Excalibur data ............................................................................................................ 11

4.3 SAMPLING AND QAQC ....................................................................................................... 11

4.4 BULK DENSITY ................................................................................................................... 12

4.5 TREATMENT OF BELOW DETECTION AND UNSAMPLED INTERVALS ......................................... 12

5.0 GEOLOGICAL AND VOLUME MODELLING .................................................................. 12

5.1 GOLD MINERALISATION ...................................................................................................... 12

6.0 COMPOSITING ............................................................................................................... 14

6.1 COMPOSITING TECHNIQUE ................................................................................................. 14

6.1.1 3D Composite File Descriptions ................................................................................. 14

6.2 MODELLING TECHNIQUE ..................................................................................................... 15

6.2.1 3D Modelling Technique ............................................................................................ 15

7.0 DESCRIPTIVE STATISTICS ........................................................................................... 15

7.1 DESCRIPTIVE STATISTICS BY GROUPED DOMAINS ................................................................ 15

7.2 HIGH GRADE CUTS ............................................................................................................ 16

8.0 VARIOGRAPHY .............................................................................................................. 16

9.0 BLOCK MODELLING AND ESTIMATION ....................................................................... 17

9.1 3D BLOCK MODEL DEFINITIONS .......................................................................................... 17

9.2 3D INTERPOLATION ............................................................................................................ 18

9.3 ESTIMATION BLOCK SIZE AND SEARCH STRATEGIES ............................................................ 19

9.3.1 Estimation Block Size ................................................................................................ 19

9.3.2 Search Strategies ...................................................................................................... 19

9.4 OXIDATION ZONES ............................................................................................................. 20

9.5 BULK DENSITY ................................................................................................................... 21

9.6 MINING DEPLETION ............................................................................................................ 21

9.7 RESOURCE CLASSIFICATION ............................................................................................... 21

9.8 MODEL VALIDATION ........................................................................................................... 21

10.0 RESOURCE CLASSIFICATION AND REPORTING ....................................................... 24




10.1 RESOURCE CLASSIFICATION ............................................................................................... 24

10.1.1 Geological Continuity and Surface Volume ............................................................. 24

10.1.2 Drilling Spacing and Mining Information .................................................................. 24

10.1.3 Data Quality ............................................................................................................ 24

10.1.4 Modelling Technique .............................................................................................. 25

10.1.5 Estimation Properties ............................................................................................. 25

10.1.6 Conclusion ............................................................................................................. 25

10.2 RESOURCE STATEMENT ..................................................................................................... 25

11.0 REFERENCES ................................................................................................................ 26

LIST OF FIGURES

Figure 3.1 Location of the Juno deposit and adjacent deposits within the Tennant Creek area ...... 9

Figure 5.1 Plan View of the M10 Resource Wireframes ............................................................... 13

Figure 5.2 Oblique View of the Resource Wireframes .................................................................. 13

Figure 9.1 Ore Zone Domain 106 Easting Validation - Au ............................................................ 22



LIST OF TABLES

Table 1.1 Total M10 Gold Resource > 0g/t Au – June 2010 ........................................................... 6

Table 1.2 Total M10 Gold Resource > 1g/t Au – June 2010 ........................................................... 7

Table 4.1 Drill Hole Database Structure ....................................................................................... 11

Table 4.2 Bulk Density Values Used. ............................................................................................ 12

Table 6.1 Description of zonecodes .............................................................................................. 14

Table 6.2 Summary Description Fields – 3D Composites .............................................................. 14

Table 7.1 Statistics of Individual Ore Domains of Au - 1m Composites. ........................................ 15

Table 7.2 Top Cuts for Individual Ore Domains of Au - 1m Composites ........................................ 16

Table 8.1 Variogram Model for Domain 106 – Au ........................................................................... 17



Table 9.1 3D Block Model Definition ............................................................................................ 18

Table 9.2 3D Block Model Field Names ....................................................................................... 18

Table 9.3 Summary 3D Estimation Parameters ........................................................................... 19

Table 9.4 Bulk Density Values Used ............................................................................................ 21

Table 9.5 Input Composite and Modelled Mean Grades by Domain ............................................. 22

Table 10.1 Total M10 Gold Resource Above 0g/t Au Tabulation – June 2010 .............................. 25




Table 10.2 Total M10 Gold Resource Above 1g/t Au Tabulation – June 2010 .............................. 25

LIST OF APPENDICES

1. UNIVARIATE STATISTICS BY GRADE DOMAIN 27

2. VARIOGRAM MODELS 31




1.0 EXECUTIVE SUMMARY

Cube Consulting Pty Ltd (Cube) was contracted by Excalibur Mining Corporation (EMC) to compile

an updated resource estimate for the M10 gold project. The estimation work was undertaken in

June 2010. The aim was to independently re-estimate and classify according to JORC guidelines,

the M10 gold resource based on all available information as of 17th May 2010. The re-estimation

involved refining the geological interpretation to domain the higher grade magnetite/hematite

hosted mineralisation separately from the lower grade talc chlorite siltstone hosted mineralisation.

The data and information incorporated by Cube in the estimation project includes:

• All resource definition drilling data available as of 17th May 2010, provided and validated by

EMC;

• All mining depletions available as of 17th May 2010, provided and validated by EMC;

• Mineralisation domains interpreted by Cube;

• Client input into the geological interpretation and mineralised domains.

All interpretations and mineralised domains were undertaken by Cube and reviewed by the client prior

to commencing the resource estimation. Cube believes that the current geological model for

mineralisation is fundamentally sound and provides an appropriate basis for further resource definition

drilling.

The M10 mineralisation is localised by multiple ellipsoidal or pipe-shaped quartz hematite ironstone

lenses. The mineralisation style is reminiscent of replacement bodies that have formed aligned

parallel to major cleavage, discordant to bedding, within favourable structures such as anticlinal

fold axes, cleavage zones or reverse shear zones [1].

Ordinary Kriging (OK) of one metre downhole composites were used for estimating gold within the

high grade and low grade domains. The 3D block model consisted of 1m N x 10m E x 10m RL parent

cells which were sub-celled down to 0.25m N x 2.5m E x 2.5m RL to control volume.

Cube have classified and reported the resource in accordance with The 2004 Australasian Code

for Reporting of Mineral Resources and Ore Reserves (JORC Code).

A summary of total M10 Mineral Resources above a 0g/t Au cut-off as of June 2010 is shown in

Table 1.1

Category Volume Tonnes Au g/t Au (oz)

Inferred 146,900 485,000 4.2 65,200

TOTAL 146,900 485,000 4.2 65,200

Table 1.1 Total M10 Gold Resource > 0g/t Au – June 2010




A summary of total M10 Resources above 1g/t Au cut-off as of June 2010 is shown in Table 1.2

Category Volume Tonnes Au g/t Au (oz)

Inferred 146,600 483,000 4.2 65,200

TOTAL 146,600 483,000 4.2 65,200

Table 1.2 Total M10 Gold Resource > 1g/t Au – June 2010

All tonnage, grade and ounce values have been rounded down to relevant significant figures.

Slight errors may occur due to this rounding of values.




2.0 INTRODUCTION

Cube Consulting Pty Ltd (Cube) was contracted by Excalibur Mining Corporation (EMC) to review

and update the resource estimate for the M10 Gold project. This update incorporated additional

drilling data, a more rigorous domaining of high and low grade mineralised zones and a different

estimation technique. The initial M10 resource was undertaken by Excalibur in August 2008.

Cube is an Australian owned company providing geological and mining engineering consulting

services and software systems to the resources and industrial sectors. The organisation is well

resourced with an established office in Perth, Western Australia and has undertaken work for a

number of substantial clients. Cube Consulting comprises a team of technical professionals

dedicated to providing excellence of services in their field of expertise.

The work for EMC was completed by Jason Harris BSc MAIG and Ted Hansen BSc MAusIMM.

Ted Hansen is the Director of Cube and has over 30 years experience in exploration, mining and

evaluation of mineral commodities in Australia and overseas. He has sufficient experience with

this style of mineralisation to qualify as a Competent Person as defined in the 2004 Edition of the

‘AUSIMM Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves’.

Cube generated a validated corrected historic database for Juno which includes the M10 drill data

based on an original database supplied by Excalibur and dated October 2009. The more recent

Excalibur drilling data was combined with the validated database into a single resource database

suitable for estimation of the M10 and Juno mineralisation.

All drilling and geological interpretation data available up to 17th May 2010 was incorporated into

the estimate.

Estimates of gold and bulk density, were carried out for all interpreted mineralised domains with all

estimation work undertaken using SURPAC (Version 6.1.3) mining software.

The M10 Mineral Resources have been classified as Inferred and reported in accordance with The

2004 Australasian Code for Reporting of Mineral Resources and Ore Reserves (JORC Code).

3.0 LOCATION AND GEOLOGY

The M10 project is located 5km southeast of Tennant Creek in the Northern Territory. The M10 is

located underneath the Juno deposit (Figure 3.1).

The M10 ore body lies within the Warramunga Group which comprises sediments, volcanic lavas and

volcaniclastic sediments. The known mineralisation in this area is contained in the Carraman

Formation and consists of felsic graywackes and shales [2]. The mineralisation occurs within

lenticular, ellipsoidal or pipelike bodies rich in magnetite and/or hematite. These are replacement

bodies which cut across sedimentary structures and have been referred to as "ironstones" by

previous workers. Sediments in the middle section of the Carraman Formation contain a greater

proportion of hematite than magnetite and are termed the hematite facies. Economic

concentrations of ore minerals occur in these ironstone bodies only when located within the hematite

facies. The magnetite-hematite bodies are favourably situated in second order anticlinal folds,

especially in domal positions or within faults or shear zones [2].

Tennant Creek-type ironstone bodies grade upwards from chloritic alteration into stringer zones of

chlorite-magnetite, coalescing higher into massive ore bearing magnetite +/- hematite, topped with




talc-dolomite-magnetite alteration. The distinct metal zonation is Au-Bi-Cu passing upwards

through the ironstone body. Chemically reactive host rocks (i.e. ironstone, hematitic shales)

commonly intersect the replacement zone [1].

Figure 3.1 Location of the Juno deposit and adjacent deposits within the Tennant Creek

area

4.0 RESOURCE MODEL DATABASE

4.1 Drilling Database

Cube generated a validated and corrected historic drill database for Juno which includes the M10

drill data, based on an original database supplied by Excalibur and dated October 2009. All

historical Geopeko digital drilling data was validated by cross checking the collar coordinates,

assays, downhole survey information and geology for all available historic hard copy drilling files

against the digital database.

As a result of this initial validation, significant differences were found between the original

database, as supplied to Cube and the historic hard copy data, as acquired by Excalibur. These

differences were systematically corrected by Cube prior to the commencement of the resource

updates and involved;

• Re-transformation of all the historical drilling data, and underground development from local

imperial mine grid to MGA94 grid system;

• Correction of historical hole azimuths to MGA94 bearings;

• Metric conversion of imperial measurements for both length and assay values, truncated to

1 and 2 decimal places respectively.

• Routine checking for overlapping intervals, negative and missing assays, or assays outside

of expected range.




The more recent Excalibur drilling data was combined with the validated database into a single

resource database (juno_20100517.mdb) suitable for estimation of the M10 and Juno

mineralisation. A description of the MS Access database and the relevant tables and fields used

by Cube is shown in Table 4.1.

TABLE FIELD DESCRIPTION

collar 847 records

hole_id Hole Id

max_depth Total Hole Depth (metres)

y Collar Northing (MGA94 zone 53)

x Collar Easting (MGA94 zone 53)

z Grid Collar RL (AHD)

hole_path Hole de-survey method

hole_type DD or RC or RCD or UGDD or RAB

flag old (historic), val (validation), infill

survey

3,597 records

hole_id Hole Id

depth_m Downhole Survey Depth (metres)

dip Dip of Hole trace

azi_local Local imperial mine grid hole azimuth

azi_mag Magnetic bearing of hole azimuth

azi_mga MGA94_55 hole azimuth

azi_mga_gyro MGA94_55 hole azimuth (gyro reading)

instrument Downhole survey instrument

assay

19,362 records

hole_id Hole Id

depth_from Interval Depth From (metres)

depth_to Interval Depth To (metres)

samp_id Sample Id

cube_au 1st Gold Assay g/t - Numerical

cube_cu 1st Copper Assay % - Numerical

cube_bi 1st Bismuth Assay % - Numerical

geology

6,574 records

hole_id Hole Id



litho Summarised Lithology Code

litho_Major Original Lithology Code

bulk_density

2,834 records

hole_id Hole Id



cube_BD Bulk density measurement (g/cm3)

data_source Density measurement source, NAL or EXM

zonecode_au

1,127 records

hole_id Hole Id



zonecode Mineralised Intercept Code for Gold




Table 4.1 Drill Hole Database Structure

4.2 Survey

4.2.1 Historical data

Excalibur digitised all historical drill hole collar and mined void outlines from the original Geopeko

mine development plans and assay/geology drilling plans and sections. These were compared

with digital files and used where collar data was not available from the hard copy drilling logs.

Down-hole survey measurements for the Geopeko underground drilling is limited. When

undertaken, holes were surveyed at 50 foot intervals (~15m) using an acid-etch tube where only

the inclination of the hole recorded was recorded and the azimuth assumed from the collar pick-up.

A Tropari instrument and a Magnetic Single Shot Camera were also used in a few instances with

limited magnetic azimuths available.

Any surface holes were surveyed using a Magnetic Single Shot Camera (photo) on 15-30m

intervals.

4.2.2 Excalibur data

All Excalibur drill hole collars, any surface historical holes and existing infrastructure that could be

located were surveyed for accurate coordinates by Brian Blakeman Surveys (BBS) in February

2010. Measurements were carried out by the use of RTK DGPS equipment based on the MGA94-

35 grid, using the GDA94 datum and based on established control points on site.

All Excalibur drill holes were down-hole surveyed by RC and diamond drilling contractors using a

Flexit multi-shot tool every 30m while drilling. A magnetic susceptibility tool was also utilised to

define areas of magnetic wall-rock which could affect azimuth readings. Any erratic readings

affected by highly magnetic units were discarded and a appropriate azimuth assumed to best

reflect the overall curvature of the hole. Any changes to the original survey data are documented

in the comments field in the survey table of the drillhole database.

4.3 Sampling and QAQC

Historical drill sampling was performed on half core split into four-foot intervals and assayed for

gold, bismuth, copper at the Assay Laboratories of Peko Mines NL and also by Australian Mineral

Development Laboratories (Large 1974).

Excalibur selected core for sampling on generally 1 metre intervals, which was cut longitudinally,

utilising half cut NQ core and quarter cut HQ core. Sharp contacts visually logged in the core were

used as sample boundaries in some cases resulting in samples less than the nominal one metre

length. Pre-collar RC sampling for Excalibur consisted of samples speared from the reject bulk

sample composited into 4m down-hole intervals into 3-5kg calico bags and dispatched to the

zonecode_cu

556 records

hole_id Hole Id



zonecode Mineralised Intercept Code for Copper




laboratory on a routine basis. Assay samples (1m cone split) for any visually mineralised (i.e.

elevated susceptibility, visible iron oxide or sulphide enrichment, chlorite alteration or high density)

or intervals that returned >0.1 g/t Au were also submitted for analysis.

This estimate is based predominantly on historical drilling data only for which no QAQC is

available.

Although no independent checks have been conducted by Cube, it is Cube’s opinion that the

drilling and sample data is appropriate and of sufficient quality to allow an industry standard

interpretation, resource interpolation and resource classification under the guidelines set out in the

JORC code.

4.4 Bulk Density

Bulk density was assigned based on mineralised domains and oxidation state. There were no

independent bulk density data for M10 and hence the assigned values were based on analysis of

the EMC bulk density data from the Juno deposit. The rock types and alteration style at M10 is

similar to that at Juno and hence the bulk densities were considered suitable for use in this

estimate.

The bulk densities that were assigned to the resource estimate are given in Table 4.2 below:

Domain Code Bulk Density

(g/cm3)

Background BKGR 2.7

Mineralised Domain (Fresh) OREF 3.3

Table 4.2 Bulk Density Values Used.

4.5 Treatment of Below Detection and Unsampled Intervals

Below detection assays in the database were treated as zeros and unsampled intervals in the

database had grades of half of the nominal detection inserted (0.005g/t Au). This was based on

the assumption that during the geological logging process, the interval was deemed as not being

mineralised and hence was not sampled.

5.0 GEOLOGICAL AND VOLUME MODELLING

5.1 Gold Mineralisation

The mineralised domains were outlined using a 0.5 g/t Au cut off. This grade cut off approximates the

low grade talc chlorite boundary as well as defines continuity of the mineralised domains. A

mineralised zone was modelled only if it was present on a minimum of two adjacent sections and

defined by a minimum of 2 drillholes within the zone.

All available drillhole data was used for the interpretation of the mineralised zones.




Figure 5.1 Plan View of the M10 Resource Wireframes

Figure 5.2 Oblique View of the Resource Wireframes




6.0 COMPOSITING

6.1 Compositing Technique

In the M10 drillhole database, a unique code for drill intercepts within the mineralised domains was

added to the database table ZONECODE. The process of coding the database was carried out by

manually identifying the appropriate downhole interval to be coded and assigning a unique code

according to the enclosing wireframe.

ZoneCode DTM File Object Number

106 ore_m10.dtm 6

107 ore_m10.dtm 7

108 ore_m10.dtm 8

Table 6.1 Description of zonecodes

It is important to use composites rather than raw sample intervals when estimating so as to ensure

that all data has the same sample support. Composites were extracted at 1m downhole lengths

allowing 0.5m or more to be included as legitimate composites. Residual samples less than 0.5m

were included in the estimate as statistical analysis showed that the populations were not

significantly different. The main consideration for selecting 1m downhole composites was that it

was the most used sampling interval for recent drilling.

6.1.1 3D Composite File Descriptions

Below is a summary of the descriptive fields stored within the 3D composite string files.

Field Value

Y Northing

X Easting

Z RL

D1 Au

D2 Hole id

D3 Depth_from

D4 Depth_To

D6 Length

D11 Au Cut

Table 6.2 Summary Description Fields – 3D Composites




6.2 Modelling Technique

6.2.1 3D Modelling Technique

Cube believes that several key features need to be addressed by the 3D modelling technique used

at M10 include:

• Mineralised thickness is variable typically ranging from a few metres to tens of metres;

• Considerable variations in geological characteristics and grade tenor;

• Raw sample intervals are variable in length and small relative to the thickness of the mineralised domain;

• There is a possibility of some mining selectivity within the mineralised domain;

• Drill spacing is variable from less than 10m N x 10m E to greater than 40m N x 20m E.

For the reasons outlines above it was decided to adopt a 3D modelling technique using equal

length downhole composites. In cases where there is insufficient data to estimate the grade of the

domain, the average grade of the composites from within that domain was used as the grade

applied.

7.0 DESCRIPTIVE STATISTICS

7.1 Descriptive Statistics by Grouped Domains

The statistics for each domain have been compiled separately. The composites within a particular

domain were used only for the estimation of that domain. No work was undertaken by Cube to

determine if there are different statistical outcomes between different sample types. Hence all

these different sample types are combined for resource estimation.

The basic descriptive statistics for the combined 1m downhole composites within the individual ore

domains are summarised below in Table 7.1 with associated plots for the main domains in

Appendix 1.

106 107 108

Number 128 96 41

Minimum 0.001 0.078 0.23

Maximum 46.1 64.02

9

17.86

2 Raw Mean 4.024 5.708 3.933

Median 1.433 1.66 1.454

Std. Dev 7.788 10.48

6

4.812

Variance 60.65

1

109.9

64

23.16

Coeff Var 1.935 1.837 1.224

Table 7.1 Statistics of Individual Ore Domains of Au - 1m Composites.




7.2 High Grade Cuts

Based on an examination of tabulated statistics, histograms (Appendix 1) and 3D spatial location,

Cube identified outliers which required top-cutting. The top cuts for individual ore domains are

shown in Table 7.2 below.

Domain Top Cut (g/t)

106 30

107 30

108 15

Table 7.2 Top Cuts for Individual Ore Domains of Au - 1m Composites

8.0 VARIOGRAPHY

The variogram modelling process followed by Cube involves the following steps:

• Calculate and model the omnidirectional or downhole variogram on the 1m composites to characterise the Nugget Effect for each domain;

• Calculate variograms in 3D to identify the plane of greatest continuity. Calculate a fan of variograms within the plane of greatest continuity to identify the direction of maximum continuity within the plane. Model the variogram in the direction of maximum continuity and the orthogonal directions;

• During the directional variography step, techniques such as modelling the relative variograms (Pairwise only) and the exclusion of extreme values to reduce the noise to improve the clarity of 1m composited variograms were used when models were difficult to fit;

• Varying lag distances in the Major, Semi-Major and Minor directions maybe utilised to optimise the cleanest variogram for each these directions.

Due to the small number of data that is available from some of the domains useful variograms

were unable to be fitted to the domains in the dataset. The variogram that was used was an

omnidirectional variogram that was calculated for the 500 Au zone in the Juno estimation [6]. As

the statistics for the 500 Au zone in Juno is the most similar to those in the M10 deposit it was

decided to use this variogram for the estimation. As the mineralisation style is very similar

between these two ore bodies and are in such close proximity the mode of formation and variation

are very likely to be similar. The orientation directions where changed to align with the lodes within

the M10 deposit and anisotrophy was applied to help restrict the effect of composites orientated

cross-strike in the orebody.

Below is a summary of the variography for Au in the domains of the M10 resource. The actual

variogram model is included in Appendix 2.




Sill

Relative

Variance

%

Range Azimuth

(East/West) Plunge Dip

Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 80 0 90 1 2

Structure2 25 0.18 20.6 80 0 90 1 2

Table 8.1 Variogram Model for Domain 106 – Au

Sill

Relative

Variance

%

Range Azimuth


Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 70 0 90 1 2

Structure2 25 0.18 20.6 70 0 90 1 2


Sill

Relative

Variance

%

Range Azimuth


Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 75 0 90 1 2

Structure2 25 0.18 20.6 75 0 90 1 2


9.0 BLOCK MODELLING AND ESTIMATION

9.1 3D Block Model Definitions

A single 3D block model was created and the definition is shown in Table 9.1 and a list of field

names and descriptions for the model are shown in Table 9.2




Minimum Maximum Model Extent

Easting 420400 420550 150

Northing 7821260 7821330 70

RL -230 -50 -180

Parent Cell X m 10 Min Sub-Cell X m 2.5

Parent Cell Y m 1 Min Sub-Cell Y m 0.25

Parent Cell Z m 10 Min Sub-Cell Z m 2.5

Table 9.1 3D Block Model Definition

Field Name Description

x X Block Centroid

y Y Block Centroid

z Z Block Centroid

au_kv kriging variance of au estimate

avg_dist average distance of samples used in the estimate

density insitu bulk density

dist distance of nearest sample

domain ore domain>0, waste=0

mined mined=0, insitu=1

num_samp number of samples used in the estimate

weath ORET, OREF, BKGR

Rescat Resource category (1=measured, 2=indicated, 3=inferred, 4=not

assigned)

Table 9.2 3D Block Model Field Names

9.2 3D Interpolation

Cube utilised Ordinary Kriging to estimate gold into a 3D block model. All block estimates were

based on interpolation into 1m N x 10m E x 10m RL parent cells, sub celling to 0.25m N x 2.5m E x

2.5m RL to control volume. Block discretisation points were set to 2(Y) x 2(X) x 2(Z) points. The

search parameters used for individual domains are summarised below in Table 9.3.




Domain Attribute

Minimum

number of

Composites

Maximum

number of

composites

Search

Radius

Bearing, Plunge and

Dip

Anisotropy

major/semi-

major,

major/minor

106 Au 8 35 30 080/0/90 1 ; 2

107 Au 8 35 30 070/0/90 1 ; 2

108 Au 8 35 30 075/0/90 1 ; 2

Table 9.3 Summary 3D Estimation Parameters

9.3 Estimation Block Size and Search Strategies

A number of issues have been taken into consideration when deciding on an appropriate search

strategy and estimation block size, including data spacing, variogram model ranges, estimation

quality, resource classification and mine planning issues.

9.3.1 Estimation Block Size

Data spacing was the primary consideration taken into account when selecting an appropriate

estimation block size. Data spacing within the mineralised surfaces is quite variable ranging from

less than 10m x 10m to 40m x 20m. A further important consideration taken into account is the

implication of the chosen block size on mining selectivity decisions.

Cube considers it good geostatistical practice to use an estimation parent cell size that approaches

the composite spacing where possible while at the same time being mindful of potential mine

design and selectivity implications. Cube reviewed the ‘physical’ data spacing relative to the

geological envelopes to be estimated when deciding on the appropriate estimation block size.

Cube adopted a 3D estimation parent block size of 1m N x 10m E x 10m RL. Fine scale sub-

celling to 0.25m N x 2.5m E x 2.5m RL was used to assist in volume reporting.

Cube believes that mining selectivity and reserve evaluation can be reasonably based on the block

estimates selected where data density is sufficient and an appropriate search strategy has been

implemented.

9.3.2 Search Strategies

Cube have attempted to characterise the spatial continuity of the data using variography and have

sought to implement search strategies aimed at producing a robust block estimate whilst at the

same time minimising estimation error and conditional biases. Cube routinely tests several search

iterations before determining the most appropriate search strategy. A discussion regarding

optimisation of search strategies and minimising conditional bias can be found in Krige 1996 [3]

and Vann et al 2003 [4].

Fundamental to the search strategy for all estimated variables was the decision to set the minimum

number of composites to 8 for the grade domains. The minimum number of composites has been

considered by Cube as a key component of the criteria applied in determining the resource

classification. An upper limit on the number of intercept composites was also set as outlined

above. Where there is more than the maximum number of composites within the search only the




closest (maximum number) will be used. Search strategy analysis undertaken by Cube supports

the upper limits selected as adequate particularly given the variable drill spacing.

Cube initially bases search distances for the first search iteration on the analysis of theoretical

kriging weight charts generated by Surpac. An examination of these kriging weight charts provides

a good starting point for testing a search strategy as they provide a guide as to the distribution of

kriging weights for a given variogram with respect to distance along the major axis of the search

volume. Of particular interest is the approximate distance that kriging weights tend towards zero.

Cube believes that it good estimation practice to use a search volume that ensures that kriging

weights allocated to composites tend toward zero or slightly negative on the periphery of the

search.

Cube generally extends the search where there are large positive weights at the periphery and

reduces the search where there are a large proportion of negative kriging weights involved. A

limitation of these charts is that they are based on an assumption that each block is directly

informed by a composite at the block centroid and they will, therefore generally understate the

required search with respect to actual data spacing to achieve a robust block estimate.

A Quantitative Kriging Neighbourhood Analysis (QKNA) was undertaken for the chosen search

strategy specific to grade domains 106, 107 and 108.

The procedure adopted by Cube involves selecting several individual blocks representing data

configurations ranging from moderate to well informed. The aim of these tests is to optimise the

kriging search neighbourhood and maximise the quality of the kriging when dealing with a non-

exhaustive data set. A number of key criteria were captured for each selected block as follows:

• Block coordinates and dimensions;

• Estimated grade;

• Kriging variance;

• Block Dispersion variance;

• Slope of Regression of estimated blocks z*(v) and theoretical true blocks z(v);

• A listing of the actual informing intercept composites within the search volume of the block including coordinates, grades, distance from block and kriging weight;

• Statistics of the informing intercept composites including number of composites, minimum, maximum, mean, standard deviation, variance and coefficient of variation.

QKNA was initially undertaken for the variograms defined from the data within the M10

mineralisation, but the outcomes from the QKNA did not produce parameters that would be

considered robust. This was primarily due to the limited number of samples from within this

deposit. The QKNA was repeated using the variogram from the Juno resource estimation and was

able to define more robust parameters to be used in the estimation.

9.4 Oxidation Zones

There is no oxidised material within the area that was estimated. All of the material is interpreted

as being fresh material.




The block model attribute “weath” by default is set to “BKGR”. This depicts that no oxidation state

is assigned to the surrounding waste. Blocks that were inside the ore domains were assigned a

“weath” value of “OREF”.

9.5 Bulk Density

Bulk density was assigned to blocks based on oxidation state. The values used for bulk density

were obtained from the Juno deposit. The rock types and alteration zones are similar between the

two deposits so it was considered reasonable to use these values. The bulk density values used

are given in Table 9.4 below.

Weathering Weathering Code Bulk Density

(g/cm3)

Background (waste) BKGR 2.7

Ore - Fresh OREF 3.3

Table 9.4 Bulk Density Values Used

9.6 Mining Depletion

There is no evidence of any mining depletion in this area so no depletion process was undertaken.

All the estimated blocks in this model are regarded as being insitu.

9.7 Resource Classification

The mineralised domains within the model (rescat) were flagged with a resource category where

1=Measured, 2=Indicated and 3=Inferred or 4=Unclassified. Section 10.0 describes the resource

classification process.

9.8 Model Validation

Modelled estimates have been compared to the 1m downhole composite grades for all domains.

Although these two items are not strictly comparable due to data clustering they provide a very useful

validation tool in detecting any major biases. Table 9.5 shows the comparison between input

composite means and modelled means for gold for each surface estimated.




Data Model Ratio

Domain Composite

Count

Estimated

Tonnes Au g/t Au g/t Au g/t

106 128 219,156 3.72 3.88 104%

107 96 231,407 5.08 4.58 90%

108 41 34,237 3.83 3.42 89%

Table 9.5 Input Composite and Modelled Mean Grades by Domain

Table 9.5 shows a good correlation for all the domains. The composite statistics have not been de-

clustered and may exhibit some instability in a comparison such as this. One of the beneficial

properties of ordinary kriging is that it inherently de-clusters data during block estimation. Some of the

blocks have been estimated by assigning the average grade of the composites from within a domain

as there was insufficient data to estimate all the blocks.

Below in Figures 9.1 & 9.2 are validation graphs for Au in domains 106, 107 and 108 for comparing

the composite mean grade with the estimated grade within 1m northing and 10mRL partitions. Also

plotted is the number of composites. The plots display good correlation between the composite mean

and estimated grades with the greatest differences occurring in poorly sampled areas and where the

composites display high degrees of local variation.

Figure 9.1 Ore Zone Domain 106 Easting Validation - Au

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10.0 RESOURCE CLASSIFICATION AND REPORTING

Cube has classified and reported the M10 Mineral Resources as Inferred in accordance with The

2004 Australasian Code for Reporting of Mineral Resources and Ore Reserves (JORC Code).

Cube has not undertaken any independent assaying of material from the M10 project and has

based this classification on information provided by EMC.

Total June 2010 M10 Mineral Inferred Resource above 0g/t Au Cut-off is 484,800t at 4.2 g/t Au for

65,200 ounces of gold.

10.1 Resource Classification

A range of criteria were considered when addressing the suitability of the classification boundaries

to the updated resource. The approach to classification is based on a number of papers

discussing the application of the JORC code for example Stephenson and Stoker 2001 [5]. These

criteria include:

• Geological continuity and surface volume;

• Data quality;

• Drill spacing;

• Modelling technique;

• Estimation properties including search strategy, number of informing composites, average distance of composites from blocks and kriging quality parameters such as slope of regression.

10.1.1 Geological Continuity and Surface Volume

Cube is confident in the continuity and volume of the mineralised surfaces within the appropriate

resource classification. Cube considers that geological confidence is equally as important as other

classification criteria listed above.

10.1.2 Drilling Spacing and Mining Information

Cube reviewed each lode on longitudinal projection plots showing the drill intercept locations and

mining activities. It was found that the drill spacing was varied with some well informed areas

where drill spacing is 10m apart and some areas where the drilling is 40 metres apart. Cube has

classified the resource as Inferred.

10.1.3 Data Quality

Cube has validated the database against the original hard copy drilling logs as part of the Juno

resource estimate. Cube has not undertaken any independent assaying of material from the M10

project. Due to the historical nature of the drilling database there is little to no information on

sampling/sample preparation, analytical techniques and QAQC. This highlights that the confidence

level on the data, even when closely spaced, is low. It is Cube’s assessment that on balance the

database represents an appropriate record of the drilling and sampling undertaken at the project

for an Inferred resource category.




10.1.4 Modelling Technique

For all domains and attributes a traditional 3D style modelling approach using Ordinary Kriging of

1m downhole composites was adopted. This modelling technique is suitable for the domains being

estimated allowing reasonable expectation of mining selectivity within the mineralised domain.

10.1.5 Estimation Properties

The search analysis described in the Section 9.3 was intended to optimise the quality of block

estimates in the zone of greatest sample density encompassing the majority of mineralised

material. Due to the variable nature of the drilling spacing there are blocks that are not directly

informed by a composite resulting in a lower slope of regression and higher kriging variance.

10.1.6 Conclusion

As with any non-rigidly defined classification there will always be some blocks within categories

that depart from defined criteria. It is the view that the final outcome must reflect a practical

combination of geological knowledge and operational experience and some estimation quality

parameters that may be more numerical in nature. This approach to classification aims to avoid

creating a complex numerically based ‘mosaic’. Cube has considered all criteria and has classified

the resource as Inferred.

10.2 Resource Statement

A summary of total Inferred M10 Mineral Resource above 0 g/t Au cut-off as of June 2010 is shown

in Table 10.1

Classification Weathering Volume Tonnes Au g/t Au Oz

Inferred Fresh 146,900 485,000 4.2 65,200

TOTAL

146,900 484,800 4.2 65,200

Table 10.1 Total M10 Gold Resource Above 0g/t Au Tabulation – June 2010

A summary of total M10 Mineral Resources above 1 g/t Au cut-off as of June 2010 is shown in

Table 10.2.

Classification Weathering Volume Tonnes Au g/t Au Oz

Inferred Fresh 146,600 484,000 4.2 65,200

TOTAL

146,600 484,000 4.2 65,200

Table 10.2 Total M10 Gold Resource Above 1g/t Au Tabulation – June 2010

All tonnage, grade and ounce values have been rounded down to relevant significant figures.

Slight errors may occur due to this rounding of values.




11.0 REFERENCES

1. Davidson GJ, and Large RR (1998). Proterozoic copper-gold deposits. AGSO Journal of Australian Geology and Geophysics, Vol. 17 No. 4.

2. Large RR (1975). Zonation of hydrothermal minerals at the Juno mine, Tennant Creek Goldfield, Central Australia. Economic Geology, Vol. 70, pp. 1387-1413.

3. Krige, D G (October 1996). A Practical Analysis of the Effects of Spatial Structure and of Data Available and Accessed on the Conditional Biases in Ordinary Kriging, in Geostatistics Wollongong 1996.

4. Vann, J., Jackson, S., Bertoli, O (September 2003). Quantitative Kriging Neighbourhood Analysis for the Mine Geologist: A description of the Method with Worked Case Examples, September 2003. Quantitative Geoscience. Perth.

5. Stephenson, P. R. and Stoker, P. T. (2001). Classification of Mineral Resources and Ore Reserves, in Mineral Resource and Ore Reserve Estimation – The AusIMM Guide to Good Practice. AUSIMM. Melbourne.

6. Shepherd A. (June 2010). Cube Juno Independent Resource Review. Cube Consulting Perth, Australia.




1. UNIVARIATE STATISTICS BY GRADE DOMAIN




Domain 106 – Normal Histogram

Domain 106– Lognormal Histogram

Domain 106– Log Probability





Domain 107 – Lognormal Histogram

Domain 107 – Log Probability





Domain 108 – Lognormal Histogram

Domain 108 – Log Probability




2. VARIOGRAM MODELS




Domain 106 – Au summary

Sill

Relative

Variance

%

Range Azimuth


Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 80 0 90 1 2

Structure2 25 0.18 20.6 80 0 90 1 2

0

0

10

10

20

20

30

30

Distance (m)

Distance (m)

0 0

50 50

100 100

150 150

Variogram : CUT AU

Variogram : CUT AU

Variogram Model - Au Zone 500

Isatis

Data/res_comp_au_2m_500

- Variable #1 : CUT AU

Experimental Variogram : in 1 direction(s)

D1 :

Angular tolerance = 90.00

Lag = 4.00m, Count = 10 lags, Tolerance = 50.00%

Model : 3 basic structure(s)

S1 - Nugget effect, Sill = 68

S2 - Spherical - Range = 5.74m, Sill = 46.23

S3 - Spherical - Range = 20.57m, Sill = 25

mikem

Mar 03 2010 15:59:11

Juno_2009_146





Sill

Relative

Variance

%

Range Azimuth


Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 70 0 90 1 2

Structure2 25 0.18 20.6 70 0 90 1 2


Sill

Relative

Variance

%

Range Azimuth


Major/ Semi

Major Ratio

Major/ Minor

Ratio

Nugget Co 68 0.49

Structure1 46 0.33 5.7 75 0 90 1 2

Structure2 25 0.18 20.6 75 0 90 1 2

Documents

M10 Technical Report june10 final · 2020. 3. 6. · estimation work undertaken using SURPAC (Version 6.1.3) mining software. The M10 Mineral Resources have been classified as Inferred