MINE3120 REPORT
Ore Body Modeling and Resource Estimation
Lecturer: Mr. Dr Basil Beamish Due Date: 6th June 2011

The University of Queensland St Lucia, QLD 4067

TO: MINE3120 Course Coordinator School of Engineering University of Queensland Brisbane QLD 4072 Attn: Dr Basil Beamish

Dear Sir,

Please find attached a copy of our Orebody Modelling and Resource Estimation report as requested. Hopefully this report will meet your expectations, however if you have any queries or concerns, please do not hesitate in contacting us.

Sincerely

STATEMENT OF ORIGINALITY

“We hereby declare that this report is our own work and that it contains, to the best or our knowledge and belief no material previously published or written by another person nor material which to a substantial extent has been submitted for another course, except where due acknowledgement is made in the report.”

Chern Gan __________________________________________________

Lucy Fraser __________________________________________________

Marcel Coquerand __________________________________________________

Michael Rigby __________________________________________________

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SUMMARY
The Datamine software package was used to estimate the total resource of this copper deposit with gold mineralization. Data taken from the 26 boreholes was then subjected to the Kriging, Inverse Power of Distance and Nearest Neighbour methods to model final tonnages of copper and ounces of gold. The main lithology of the area around the resource consists of soil, sandstone, siltstone, breccia and basalt from the surface. Each method of estimation produced the same total tonnage of the resource, which was estimated to be 3,907,200 tonnes. The Kriging estimation technique estimated the resource to contain 161,166 oz of gold and 425,885 tonnes of copper. At current spot prices for gold and copper (US$1500/oz and US$9000/t) the Kriging method values the resource to contain US$ 248 million of gold and US$ 3.98 billion of copper for a total valuation of US$ 4.23 billion. Using the Nearest Neighbour estimation technique the resource contains 182,018 oz of gold and 484,493 tonnes of copper. This values the resource to contain US$ 280 million of gold and US$ 4.40 billion of copper for a total valuation of US$ 4.68 billion. The Nearest Neighbour method produced the largest resource estimate. The final method in estimating the resource done using the Inverse Power of Distance method which estimated the resource to contain 154,760 oz of gold and 426,885 tonnes of copper. This valued the resource to contain US$ 238 million of gold and US$ 3.87 billion of copper for a total valuation of US$ 4.11 billion. The Inverse Power of Distance method produced the most conservative resource estimate out of all the techniques used. The range of these results used to estimate this copper deposit indicates that the total valuation of this deposit lies between US$ 4.11 and US$ 4.68 billion, which composes of 154,760 to 182,018 ounces of gold and 426,885 to 484,493 tonnes of copper using the results of the Inverse Power of Distance method as a lower-bound estimate and the Nearest Neighbour method as an upper-bound estimate of the resource.

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TABLE OF CONTENTS
SUMMARY ............................................................................................................................................................ i 1. 2. 2.1 2.2 2.3 2.4 3. 3.1 3.2 3.3 4. 4.1 4.2 4.3 5. INTRODUCTION ......................................................................................................................................... 1 METHOD: USING THE DATAMINE SOFTWARE PACKAGE ....................................................................... 2 Validate, Desurvey and Composite ...................................................................................................... 2 Orebody Modlling ................................................................................................................................ 4 Grade Interpolation .............................................................................................................................. 7 Resource Calculation ......................................................................................................................... 11 RESOURCE ESTIMATION RESULTS........................................................................................................ 12 Inverse Power of Distance Estimation Technique ............................................................................. 12 Kriging Estimation Technique ........................................................................................................... 13 Nearest Neighbour Estimation Technique ......................................................................................... 14 RESOURCE EVALUATION ....................................................................................................................... 15 Inverse Distance of a Power Valuation of the Resource .................................................................... 15 Kriging Valuation of the Resource .................................................................................................... 16 Nearest Neighbour Valuation of the Resource .................................................................................. 16 CONCLUSIONS ....................................................................................................................................... 17

REFERENCES .................................................................................................................................................... 18 APPENDICES ..................................................................................................................................................... 19 1. 2. BLOCK MODELS .................................................................................................................................... 19 BLOCK MODELS WITH COPPER MINERALIZATION ................................................................................ 21

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LIST OF FIGURES
Figure 1 Validating and desurveying of drillholes ............................................................................................. 2 Figure 2 Orebody string polygon ........................................................................................................................ 3 Figure 3 Composited drillholes .......................................................................................................................... 3 Figure 4 Creating tag strings............................................................................................................................... 4 Figure 5 Orebody wireframe .............................................................................................................................. 5 Figure 6 Orebody wireframe in visualiser mode ................................................................................................ 5 Figure 7 Orebody block model ........................................................................................................................... 7 Figure 8 Basic grade interpolation files selection for gold ................................................................................. 7 Figure 9 basic grade interpolation fields input for gold ..................................................................................... 8 Figure 10 basic grade interpolation parameters input for gold using Inverse Distance to a Power method ...... 8 Figure 11 Basic grade interpolation files selection for copper ........................................................................... 9 Figure 12 basic grade interpolation fields input for copper ................................................................................ 9 Figure 13 Optimising block model ..................................................................................................................... 9 Figure 14 Final block model using Inverse Distance of a Power method showing gold grade ....................... 10 Figure 15 Evaluating block model .................................................................................................................... 11 Figure 16: Inverse Power of Distance method highlighting Gold grades ........................................................ 12 Figure 17: Kriging method highlighting Gold grades ...................................................................................... 13 Figure 18: Nearest Neighbour method highlighting Gold grades .................................................................... 14 Figure 22: Wireframe ....................................................................................................................................... 19 Figure 20: Block Model with Boreholes and Contours .................................................................................... 20 Figure 21: Inverse Power of Distance method highlighting Copper mineralization ........................................ 21 Figure 22: Kriging method highlighting Copper mineralization ...................................................................... 21 Figure 23: Nearest Neighbour method highlighting Copper mineralization .................................................... 22

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LIST OF TABLES
Table 1 Statistical results of wireframe points ................................................................................................... 6 Table 2 Input values for prototype model........................................................................................................... 6 Table 3: Inverse Power of Distance Results ..................................................................................................... 12 Table 4: Kriging Results ................................................................................................................................... 13 Table 5: Nearest Neighbour Results ................................................................................................................. 14 Table 6: Inverse Power of Distance Evaluation ............................................................................................... 15 Table 8: Nearest Neighbour Evaluation ........................................................................................................... 16 Table 7: Kriging method Evaluation ................................................................................................................ 16

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1. INTRODUCTION
To be sent!! I will send this tonight as I have run out of time to go over it at the moment.

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2. METHOD: USING THE DATAMINE SOFTWARE PACKAGE
2.1 Validate, Desurvey and Composite

The orebody resource estimation was calculated using a software package called Studio 3. A new project was created and all the source files are imported into the project database, creating five corresponding database file, which are collars, surveys, assays, zones and lithology. The drillhole database files were then desurveyed, validated and composited. The input files for the validating and desurveying process is shown in Figure 1. The desurveyed files contain the computed 3D position and orientation of each drillhole sample along with the sample assay and lithology log information. The output file of this process will be used to composite the drillholes.

Figure 1 Validating and desurveying of drillholes

3 Before the compositing process can begin, the geological form of the orebody was interpreted by outlining the orebody boundaries on each section, creating a string polygon for each section. However, the orebody string polygon file was included as part of the source file and is shown in Figure 2.

Figure 2 Orebody string polygon

Compositing is a standard processing technique for regularizing either the length or the vertical height of the samples. The drillhole data was composited down the drillhole using composite length interval of 5 m, minimum composite length of 0.02 m. The zone of compositing within was set to ‘rock’. Figure 3 shows the new composited drillholes, where the colour of red and cyan in the drillholes showing the interception with the orebody.

Figure 3 Composited drillholes

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2.2

Orebody Modlling

In order to create an orebody block model, a wireframe of the orebody was created using the string polygons provided. Tag strings were created at both ends of the polygons and another on the top surface of the orebody, shown in Figure 4.

Figure 4 Creating tag strings

Using the link strings and end link commands, the lines from the polygons are connected, sealing the surface of the polygons and creating the wireframe model of the orebody, shown in Figure 5 and 6. It is important to note that very precise placement of the wireframes is needed to have an accurate model of the data points. Final resource calculations will ultimately be determined on the accuracy of this modelling process.

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Figure 5 Orebody wireframe

Figure 6 Orebody wireframe in visualiser mode

6 The statistics for the wireframe points were computed. The purpose of this step is to obtain the range at which the orebody lies. This information is then used to adjust for a more suitable range when creating the block model. The statistical results computed are shown in Table 1.

Table 1 Statistical results of wireframe points

Minimum (m)

Maximum (m)

Range (m)

X Y Z

7929 6499 251

8108 6700 377

178 201 126

Creating a block model starts with creating and defining a new prototype model using the determined origin, cell dimensions and number of cell blocks along each axis. A new prototype model was created and defined using the input values shown in Table 2. A mined out field was not required in this process and sub cells were used. The completed orebody block model is shown in Figure 7.

Table 2 Input values for prototype model

Origin (m) X Y Z 7900 6400 240

Cell Dimensions (m) 5 5 5

Number of cell blocks 60 80 32

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Figure 7 Orebody block model

2.3

Grade Interpolation

At this stage of the process, the block model does not contain grade information of gold or copper. To provide grade information of gold and copper, the block model was interpolated using inverse distance to a power. Using the basic grade interpolation command, the gold grade was interpolated into the block model. The files selections were done according to Figure 8, where mea_ore and mea_dhc refer to the block model created in the previous step and the composited drillholes data respectively. The “VALUE” selection box shown in Figure 9 refers to the commodity grade interpolated into the block model, which is gold.

Figure 8 Basic grade interpolation files selection for gold

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Figure 9 basic grade interpolation fields input for gold

The value shown in Figure 10 refers to the interpolation method used, the value 2 being Inverse Distance to a Power method.

Figure 10 basic grade interpolation parameters input for gold using Inverse Distance to a Power method

At this stage of the process, the block model only has information of the gold grade. The next step is to interpolate the copper grade into the block model. This step is similar to the previous step of interpolating the gold grade into the block model. The input files are the block model with gold grade and the composited drillholes, as show in Figure 11 and the value to be interpreted was set to copper as shown in Figure 12. This step is also done using inverse distance to a power method.

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Figure 11 Basic grade interpolation files selection for copper

Figure 12 basic grade interpolation fields input for copper

The next step is to optimise the sub-blocks in the block model. Figure 13 shows that the input file is the block model with both gold and copper grade and the output file will be the final block model which is used to calculate the resource tonnage.

Figure 13 Optimising block model

10 An appropriate legend was set up for the gold grade for the final block model, shown in Figure 14. A separate set of legends was also set up for copper to better illustrate its grade distribution.

Figure 14 Final block model using Inverse Distance of a Power method showing gold grade

At this stage of the process, the final block model with appropriate legends has been interpolated using the Inverse Distance to a Power estimation technique. The grade interpolation process is repeated using the Nearest Neighbour and ordinary Kriging method to obtain different interpolated results along with different legends.

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2.4

Resource Calculation

The average grade and total tonnage of the resource can now be calculated. This is done by evaluating inside the string which was drawn around the final block model created in the previous steps. This step is done for the three final block model obtained. The evaluation settings are shown in Figure 15. A default density of 3.2 was applied.

Figure 15 Evaluating block model

From this, the total resource tonnage of gold and copper is calculated.

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3. RESOURCE ESTIMATION RESULTS
3.1 Inverse Power of Distance Estimation Technique

Figure 16: Inverse Power of Distance method highlighting Gold grades

Table 3: Inverse Power of Distance Results Category [ABSENT] [0.01,0.599] [0.599,0.736] [0.736,0.832] [0.832,0.927] [0.927,1.031] [1.031,1.162] [1.162,1.305] [1.305,1.468] [1.468,1.771] [1.771,14.583] TOTAL Tonnes 0 256420 337100 417580 434420 397780 410160 404100 392840 439960 416680 3907200 ZONE 0 1 1 1 1 1 1 1 1 1 1 1 AU (g/t) 0 0.475 0.676 0.785 0.881 0.976 1.094 1.231 1.385 1.587 2.82 1.232 CU (%) 0 0.054 0.072 0.08 0.087 0.093 0.1 0.109 0.118 0.129 0.222 0.109

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3.2

Kriging Estimation Technique

Figure 17: Kriging method highlighting Gold grades

Table 4: Kriging Results Category [ABSENT] [-0.196,0.497] [0.497,0.66] [0.66,0.779] [0.779,0.885] [0.885,1.009] [1.009,1.145] [1.145,1.328] [1.328,1.59] [1.589,2.056] [2.056,17.395] TOTAL Tonnes 0 269540 300800 368180 428580 424800 414540 414220 425700 428460 432340 3907200 ZONE 0 1 1 1 1 1 1 1 1 1 1 1 AU (g/t) 0 0.314 0.586 0.724 0.831 0.947 1.073 1.233 1.45 1.79 3.205 1.283 CU (%) 0 0.037 0.064 0.076 0.084 0.091 0.1 0.109 0.122 0.141 0.246 0.112

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3.3

Nearest Neighbour Estimation Technique

Figure 18: Nearest Neighbour method highlighting Gold grades

Table 5: Nearest Neighbour Results Category [ABSENT] [0,0.3192] [0.3192,0.604] [0.604,0.836] [0.836,1.02] [1.02,1.2124] [1.2124,1.631] [1.631,2.66] [2.66,28.52] TOTAL Tonnes 0 993160 419260 389300 375760 444880 425880 422820 436140 3907200 ZONE 0 1 1 1 1 1 1 1 1 1 AU (g/t) 0 0.053 0.473 0.695 0.919 1.123 1.396 2.063 6.488 1.449 CU (%) 0 0.023 0.058 0.076 0.093 0.108 0.126 0.169 0.458 0.124

Block models highlighting the Copper mineralization as a percentage of the deposit can be viewed in Appendix 2.

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4. RESOURCE EVALUATION
In valuing the resource using the three estimation techniques, the results taken from Section 4 were then used to calculate the commercial value of the gold and copper on the commodities market. For this calculation current spot prices were used. Fluctuations around the current market spot rate of US$ 1500/oz of gold and US$ 9000/tonne of copper will affect the following valuations. To avoid any downside risk associated with market price volatility, a recommended strategy would be to hedge these current market prices for copper and gold.

4.1

Inverse Distance of a Power Valuation of the Resource

The Inverse Distance of a Power method valued the resource the most conservatively in contrast to the Kriging and Nearest Neighbour methods. Using the Inverse Distance of a Power method, this copper deposit contains a US$ 4.1 billion resource.

Table 6: Inverse Power of Distance Evaluation Total Resource (US$) $0.00 $131,895,130.74 $231,904,751.08 $319,889,575.75 $362,496,372.68 $355,487,979.03 $395,045,855.61 $425,008,867.27 $448,298,982.18 $550,461,690.18 $899,013,704.26 $4,109,559,015.78

Category Au (g) Au (Oz) [ABSENT] 0.00 0.00 [0.01,0.599] 121,799.50 3,915.85 [0.599,0.736] 227,879.60 7,326.33 [0.736,0.832] 327,800.30 10,538.78 [0.832,0.927] 382,724.02 12,304.58 [0.927,1.031] 388,233.28 12,481.70 [1.031,1.162] 448,715.04 14,426.19 [1.162,1.305] 497,447.10 15,992.92 [1.305,1.468] 544,083.40 17,492.28 [1.468,1.771] 698,216.52 22,447.66 [1.771,14.583] 1,175,037.60 37,777.46 TOTAL 4,813,670.40 154,759.50

Cu (t) 0.00 13,846.68 24,271.20 33,406.40 37,794.54 36,993.54 41,016.00 44,046.90 46,355.12 56,754.84 92,502.96 425,884.80

Au (US$) Cu (US$) $0.00 $0.00 $6,028,809.54 $125,866,321.20 $11,279,543.08 $220,625,208.00 $16,225,399.75 $303,664,176.00 $18,944,004.08 $343,552,368.60 $19,216,700.43 $336,271,278.60 $22,210,415.61 $372,835,440.00 $24,622,546.27 $400,386,321.00 $26,930,941.38 $421,368,040.80 $34,560,194.58 $515,901,495.60 $58,161,797.86 $840,851,906.40 $238,266,183.78 $3,871,292,832.00

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4.2

Kriging Valuation of the Resource

Table 7: Kriging method Evaluation Total Resource Au (Oz) Cu (t) Au (US$) Cu (US$) (US$) 0.00 0.00 $0.00 $0.00 $0.00 1,692.29 22,842.68 $2,605,440.43 $207,639,961.20 $210,245,401.63 6,375.67 24,317.08 $9,815,911.40 $221,042,257.20 $230,858,168.60 8,698.62 29,586.80 $13,392,303.02 $268,944,012.00 $282,336,315.02 11,102.15 34,945.68 $17,092,756.96 $317,656,231.20 $334,748,988.16 16,062.15 48,047.04 $24,729,122.00 $436,747,593.60 $461,476,715.60 19,114.09 53,660.88 $29,427,862.80 $487,777,399.20 $517,205,262.00 28,043.73 71,456.58 $43,175,841.30 $649,540,312.20 $692,716,153.50 90,974.09 199,752.12 $140,062,804.90 $1,815,746,770.80 $1,955,809,575.70 182,018.28 484,492.80 $280,233,522.97 $4,404,039,552.00 $4,684,273,074.97

Category [ABSENT] [0,0.3192] [0.3192,0.604] [0.604,0.836] [0.836,1.02] [1.02,1.2124] [1.2124,1.631] [1.631,2.66] [2.66,28.52] TOTAL

Au (g) 0.00 52,637.48 198,309.98 270,563.50 345,323.44 499,600.24 594,528.48 872,277.66 2,829,676.32 5,661,532.80

4.3

Nearest Neighbour Valuation of the Resource
Table 8: Nearest Neighbour Evaluation Total Resource Au (Oz) Cu (t) Au (US$) Cu (US$) (US$) 0.00 0.00 $0.00 $0.00 $0.00 2,721.03 9,972.98 $4,189,275.59 $90,654,388.20 $94,843,663.79 5,667.04 19,251.20 $8,724,921.07 $174,993,408.00 $183,718,329.07 8,569.98 27,981.68 $13,194,253.33 $254,353,471.20 $267,547,724.53 11,450.22 36,000.72 $17,628,647.07 $327,246,544.80 $344,875,191.87 12,933.48 38,656.80 $19,912,259.61 $351,390,312.00 $371,302,571.61 14,300.37 41,454.00 $22,016,699.96 $376,816,860.00 $398,833,559.96 16,420.07 45,149.98 $25,280,182.21 $410,413,318.20 $435,693,500.41 19,845.07 51,935.40 $30,553,270.94 $472,092,786.00 $502,646,056.94 24,657.23 60,412.86 $37,962,025.21 $549,152,897.40 $587,114,922.61 44,548.64 106,355.64 $68,586,637.36 $966,772,767.60 $1,035,359,404.96 161,165.94 437,606.40 $248,129,475.48 $3,977,842,176.00 $4,225,971,651.48

Category [ABSENT] [-0.196,0.497] [0.497,0.66] [0.66,0.779] [0.779,0.885] [0.885,1.009] [1.009,1.145] [1.145,1.328] [1.328,1.59] [1.589,2.056] [2.056,17.395] TOTAL

Au (g) 0.00 84,635.56 176,268.80 266,562.32 356,149.98 402,285.60 444,801.42 510,733.26 617,265.00 766,943.40 1,385,649.70 5,012,937.60

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5. CONCLUSIONS

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REFERENCES

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APPENDICES 1. BLOCK MODELS

Figure 19: Wireframe

It is essential that a precise wireframe model is used as the foundation for any further calculations. As demonstrated in Figure 22, there is no margin of error as a careless addition (or omission) of an inappropriate (necessary) wireframe will adversely affect the 3D block model and final resource estimations.

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Figure 20: Block Model with Boreholes and Contours

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2. BLOCK MODELS WITH COPPER MINERALIZATION

Figure 21: Inverse Power of Distance method highlighting Copper mineralization

Figure 22: Kriging method highlighting Copper mineralization

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Figure 23: Nearest Neighbour method highlighting Copper mineralization