014 Alges Sampling 2011 Cmcc v2 Comp

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Advanced reverse circulation drilling as a replacement

to blast hole sampling: increasing short term planning

profitability at Cerro Colorado copper mine

Eduardo J. Magri, Julin M. Ortiz (Universidad de Chile)

Rodrigo Moya, Andrs Salazar (Compaa Minera Cerro Colorado)


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Outline

Introduction Cerro Colorado Operation

Cerro Colorado Geology

Methodology

Results Conclusions


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Introduction


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Motivation

Cerro Colorado is a producing open pit mine (~55 ktpd of ore)

This presentation is an attempt to evaluate the economic impact ofreplacing blast hole sampling by advanced RC drilling for shortterm planning, this includes:

Impact of reducing the sampling errors (precision and bias)

Definition of the spacing of the advanced drilling grid

Impact of the grade control methodology and estimation parameters

Impact of the misclassification of geological units (clays)

The approach is based on building conditional simulations ofgrade distributions, simulating the sampling and grade controlprocedures, and evaluating the resulting profit.


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Cerro Colorado Operation


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Cerro Colorado is a porphyry copper deposit located in the Tarapaca Region of Chile

(lat. 2002'S, long. 6915'W), 120 km East of the city of Iquique, at an elevation of2600 m

It belongs to a belt of porphyry copper deposits in the Central Andes

The operation was started by Ro Algom Ltd. in 1994.

Cerro Colorado is an operation of BHP Billiton Pampa Norte, a business unit that alsoincludes Minera Spence located in the Antofagasta Region.

Mining is done by open pit, extracting oxides and sulphides

Background information


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Mining includes oxides and secondary enrichment Ore throughput: 52-55 Ktpd & 19.2 Mtpa

Rock extraction / Stripping ratio: 90 Mtpa / 1: 3.7

Ore Process: Heap leaching and SX-EW Ore type: oxide, secondary sulphide and MSH (mixed of secondary sulphide

& hypogene copper). Ore mineralogy: chrysocolla, brochantite, chalcocite and covellite.


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Metallurgical recovery: 69% Geometallurgical short term planning model considers blending of different clays

Production FY11: 90.5 Kt of Cu Cathodes

Plant capacity (design): 130 Ktpy of Cu Cathodes

Reserves (Probable + Proven): 167.9 Mt @ 0.65% TCu & 0.36% SCu. (c.o.g: 0.3%TCu)


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Background information


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Cerro Colorado 53 Ma

MetallogenicsBelts


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Regional Geology


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Cerro Colorado is a porphyry copper deposit located in the north-south metallogenic belt, dated from the paleocene-inferior eocene.

The regional geology consists of a andesitic volcanoclasticsequence, from the Cretaceous (Cerro Empexa formation), intrudedby tonalitic and quartz-monzonitic fases from the lower tertiary(porphyries and breccias). These units are covered by volcanic andsedimentary deposits from the Pliocene (ignimbrites and gravel fromthe Altos de Pica formation).

The copper mineralization is related to intrusive events through a

trend NE to EW, in a series of sub horizontal bodies (West sector)and more complex units (East sector) of copper oxides, supergenecopper sulphides and primary copper sulphides in depth. Theextension is approximately 2.3 km in length in the EW direction and1.5 km in the NS direction.


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MineralizationAltos de Pica

60m av-

Lch: 25-75m thick.

CuS/CuT > 0.5 25-125 m thick.

Cu leached >=80 % 10-100 m thick.

Cu leached: 50 79 %

Cu leached< 50 %

(Br-Cr)

(Cs-Cv)

(Cs-Cv-Cpy)

(Cpy>>Cs-Cv)

Gravel - Ignimbrites

Leach cap

Cu Oxides

Supergene sulphides

Mixt sulphides

Primary sulphides

Waste


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Lithological units

Porphyry

Breccia

Andesite


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Lithological units

Porphyry

Breccia

Andesite

Gravel

Ignimbrite

CerroColorado


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Mineralization units

Cerro ColoradoSulphidesOxides

Hypogene MSH


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Alteration units

Cerro Colorado

Potassic Alt.North sector

PhyllicAlt.

Potassic Alt.Phase 5 low

grade

Topography Phase 7Extreme

north sector

Phyllic chloriticAlt.In deeper levels


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SE view of current pit Blue line A-A: Orientation of sections

A

A


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Ore type units

2000 msnm

2600 msnm

CURRENTPIT

CURRENT

PIT

HYPOGENE

OXIDES

LEACHED

CAP

SECONDARYSULPHIDES

TRANSITIONALSULPHIDES

GRAVEL

A A


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Lithological units

2600 msnm

2000 msnm

CURRENT

PITCURRENTPIT

PORPHYRY

IGNEOUSBRECCIA

IGNEOUS

BRECCIA

PORPHYRYIGNIMBRITE

IGNIMBRIT

EGRAVEL

A A


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Clay units (ARC)

CURRENT PIT

CURRENT PIT

2000 msnm

2600 msnm

ARC9

ARC1

ARC7

ARC7

ARC7

ARC4

ARC

2

ARC1

ARC

6

ARC8

ARC8

ARC

1

ARC7

ARC8

ARC1

ARC Description

1-2-3-9 Detrimental clays

4-5 Clays with moderate effect

6-7-8 Clays that do not affect the process

A A


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Alteration units

CURRENT PIT

CURRENT PIT

2600 msnm

2000 msnm

PHYLLIC

PHYLLIC

PHYLLIC

POTASSIC

POTASSIC

CHLORITIC

ARGILLIC

GRAVELS

CHLORITIC

A A


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Methodology


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Goals

Evaluate the effect of: Information quality:

blast hole sampling error (current) vs advanced RC drilling and sampling(proposed)

Effect of systematic bias

Effect of improving the accuracy of geologcial interpretation

Information quantity:

Blast hole spacing (current) vs different advanced drilling grid spacings(proposed)

Estimation method:

Inverse distance squared weighting (current) vs Ordinary Kriging (proposed)

Estimation parameters


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Methodology

Inputs: Long term planning model UGCUT, Density, ARC (clays)

Drill hole 10.0 m composite database Total copper (CuT), soluble copper (CuS) Solubility ratio (RSol)

Duplicate blast hole data

Total copper (CuT), soluble copper (CuS) Economic and operational parameters (costs, commodity price, W/O ratio,

recovery functions, acid consumption, etc.)

Considerations: Long term geological attributes are fixed (UGCUT, Density, ARC)

Drill hole data are used to infer statistical distribution of the variables and

variograms to be used in simulation Sampling errors for CuT, CuS are inferred from duplicate blast hole data

Output: Simulated realizations at point support of CuT, RSol CuS (dense

spacing)


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Methodology

Definition of the study volume East 71700-73900 2200 m

North 82900-84100 1200 m

Elevation 2270-2530 260 m

Geological units and clay units:

UGCUT Description

2 Oxides

3 Oxides

4 Sulphides

5 Sulphides

ARC Description

1-2-3-9 Detrimental clays

4-5 Clays with moderate effect

6-7-8 Clays that do not affect the process

Long Term


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MethodologyLong Term

Model

Drill holedatabase

Blast holedatabase


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Methodology

Sampling errors: Calculated from duplicated blast hole data


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Duplicate blast hole data - CuS

Error = 24.3%


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Duplicate blast hole data CuS > 0.1%

Error = 15.0%


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Duplicate blast hole data - CuT

Error = 19.9%


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Duplicate blast hole data CuT > 0.1%

Error = 14.0%


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Duplicate data by range

Sampling errors by range of values

Range of grades

Mean Relative Error

(%)

CuS CuT

Average of duplicates > = 0.1% 15.02 13.97Average of duplicates > = 0.0 y < 0.1% 29.04 31.39

Average of duplicates > = 0.1 y < 0.2% 26.71 21.53



Average of duplicates > = 0.5 y < 0.8% 18.23 17.90Average of duplicates > = 0.8 y < 1.2% 22.43 18.54

All 24.34 19.94


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Methodology

1. Ten dense simulation models were builtCoordenate Number

of points

Size (m) Min Coord

(m)

Max Coord

(m)

Extension

(m)

X (East) 1100 2.0 71700.0 73900.0 2200.0

Y (North) 600 2.0 82900.0 84100.0 1200.0

Z (Elevation) 26 10.0 2270.0 2530.0 260.0


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Methodology

2. Block average represent the truthCoordenate Number

of points

Size (m) Min Coord

(m)

Max Coord

(m)

Extension

(m)

X (East) 1100 2.0 71700.0 73900.0 2200.0

Y (North) 600 2.0 82900.0 84100.0 1200.0

Z (Elevation) 26 10.0 2270.0 2530.0 260.0

Coordenate Number of

blocks

Size (m) Min Coord

(m)

Max Coord

(m)

Extension

(m)

X (East) 220 10.0 71700.0 73900.0 2200.0Y (North) 120 10.0 82900.0 84100.0 1200.0

Z (Elevation) 26 10.0 2270.0 2530.0 260.0


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Methodology

Correlations for pairs of variables

CuT vs CuS

= 0.4 0.9


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Methodology


CuT vs RSol

= -0.3 0.3


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Methodology


CuS vs RSol

= 0.4 0.5

The variableswith lowercorrelation are

CuT / RSol


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Methodology

Implementation details: Point simulation of CuT and RSol for each unit (UGCUT) with

hard boundaries. Models are combined by geological unit.

CuS can be deduced at point support from the simulated valuesof CuT and Rsol:

CuS = RSol x CuT

Block average over grades to block support simulations of

grades at block support No ratio is ever block averaged

Reblocked models represent the truth (10 cases), which areused for comparison purposes

M h d l


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Methodology

Point simulation is done by geological unit: Declustering / Transformation

Variogram modeling

Point conditional simulation

Validation: histogram / variogram reproduction

Declustereddistributions

Gaussiandistributions

M th d l


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Methodology

Variable Unit ModelSill

contributionRange 1 Range 2 Range 3

NS_CuT 2 +3

Rotation N45E/0 N45W/0 N0/-90

Nugget 0.15

Shperical 0.55 25.0 30.0 25.0

Shperical 0.30 350.0 230.0 115.0

NS_CuT 4

Rotation N45E/0 N45W/0 N0/-90

Nugget 0.15

Shperical 0.38 90.0 85.0 65.0

Shperical 0.47 680.0 530.0 95.0

NS_CuT 5

Rotation N0/0 N90E/0 N0/-90

Nugget 0.10

Shperical 0.40 95.0 90.0 100.0

Shperical 0.50 450.0 330.0 185.0

NS_RSol 2 +3


Nugget 0.20

Shperical 0.35 40.0 40.0 35.0

Shperical 0.45 450.0 450.0 140.0

NS_RSol 4


Nugget 0.20

Shperical 0.20 85.0 85.0 70.0

Shperical 0.60 630.0 630.0 95.0

NS_RSol 5


Nugget 0.15

Shperical 0.35 90.0 90.0 130.0

Shperical 0.50 450.0 450.0 190.0

Variogrammodels

M th d l


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Methodology

Dense simulation CuT grades

M th d l


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Methodology

Block support simulation CuT grades

M th d l


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Methodology

3. Dense point simulations are sampled at different grids: 6 x 6, 8 x 8 (current blash hole grid), 10 x 10, 12 x 12, 14 x 14, 16 x 16,

18 x 18, and 20 x 20m

The exact simulated value represents a sample without error (or withnegligible RC error)

M th d l


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Methodology


M th d l


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Methodology

Samples over a 20 x 20m grid, without error added CuT grades

M th d l


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Methodology

4. A Gaussian random error is simulated and added (or subtracted) tothe actual value:

14% error for CuT

15% error for CuS

M th d l


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Methodology


M th d l


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Methodology

Samples over a 20 x 20m grid, without error added CuT grades

Methodolog


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Methodology

Samples over a 20 x 20m grid, with error added CuT grades

Methodology


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Methodology

5. Grades are estimated over 10 x 10 x 10 m blocks: Input:

CuT and CuS samples without error for a given grid spacing

CuT and CuS samples with error added for a given grid

Estimation method:

Current short term estimation plan ID2 with search radii 12.5m horizontaland 5.0m vertical, 1/6 samples

Improved estimation plan ordinary kriging with search radii 30.0mhorizontal and 5.0m vertical, 4/16 samples

Requires variograms of blast hole grades for kriging

Methodology


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Methodology

Estimated block grades by ID2, samples withouterror added CuT grades

Methodology


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Methodology

Estimated block grades by kriging, sampleswithout error added CuT grades

Methodology


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Methodology

Estimated block grades by ID2, samples with erroradded CuT grades

Methodology


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Methodology

Estimated block grades by kriging, samples witherror added CuT grades


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Methodology


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Methodology

Methodology


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Methodology

Parameters required:

Recovery function

Acid consumption: function of CuS and recovery

Drilling, sample preparation and analysis costs Sample preparation and analysis = 10.0 (US$/sample)

RC drilling cost = 20.0 (US$/m)

Blast hole drilling cost = 14 (US$/m) incluides 1 m subdrill

UG CuT UG = Ox / Sulf ARC Recov (%)

2 o 3 Ox 1, 2, 3, 9 69

2 o 3 Ox 4, 5 72

2 o 3 Ox 6, 7, 8 80

4 o 5 Sulf 1, 2, 3, 9 64

4 o 5 Sulf 4, 5 67

4 o 5 Sulf 6, 7, 8 72


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Results

Results


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Results

Results


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Results

Main result


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Current situation:BH with error + ID2 1/6

Proposed situation:RC with low error + KR 4/16


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Blast hole gridNo extra drilling cost

Any other grid spacingrequires additional drilling cost


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Reducing the error requiresRC drilling cost


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Difference due to reduction ofgeological misclassification


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Sampling error reduction andreduction in geological

misclassification pays foradditional drilling cost


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Current situation:BH with error + ID2 1/6

Proposed situation:RC with low error + KR 4/16

Results


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Results

Sensitivities showed that: 5% systematic bias results in: 8-12 million dollars when inverse distance is used

0-1 million dollars when ordinary kriging is used

Copper price does not change the recommendation and improving thegeological knowledge (from 2 to 5% misclassification) is more relevant

RC drilling cost is an important parameter, as the additional drillingrequired when an advanced grid is used, may become very costly andovercome the profit made by better knowledge (either due to bettersamples or to better interpretation)

Fluctuations due to spatial variability (between realizations) are small

compared to those due to geological interpretation: Up to 4 million dollars when inverse distance is used

Up to 1 million dollars when kriging is used

Results


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Results

Losses are more significant when using inverse distance

Implementing ordinary kriging is simple for short term plan andreduces the conditional bias

Using more samples in the estimation improves the results

RC cost is significant and should be lowered as much as possible toincrease the profit

The use of an advanced drilling grid benefits the final result in twoaspects: A more careful sampling and sample preparation procedures may be

implemented

A more detailed and accurate interpretation of the geological attributes

of the blocks may result and input in advance in the short term plan The study showed that implementing an advanced drilling grid with a

spacing of 18x18m may impact improve the profit in 130 milliondollars over the five years period evaluated.

Acknowledgements


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Acknowledgements

ALGES Lab Advanced Mining Technology Center

Universidad de Chile

Department of Mining Engineering

Universidad de Chile

Compaa Minera Cerro Colorado

Documents

014 Alges Sampling 2011 Cmcc v2 Comp