RECONCILIATION [Modo de Compatibilidad]

7/29/2019 RECONCILIATION [Modo de Compatibilidad]

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RESOURCES, RESERVESAND RECONCILIATION

By

Harry Parker

Kadri Dagdelen

BEST PRACTICE PRINCIPLES

Resource and Reserve Estimation is a serialprocess:

- Data collection: geology, assays

- 3-dimensional geological solids model

- Exploratory data analysis

- Grade, density interpolation

- Resource classification/statement

- Mine design criteria

- Life-of-mine plans

- Reserve statement


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DATA GATHERINGDRILLING PROGRAMS

Wide-spaced drilling to identify size of theprize

Infill drilling to refine geometry, confirmore controls, establish continuity,metallurgical ore types, contaminants

Tighten spacing in risk areas:- Complex structure

- Toe of ultimate pit

- Apparent high-grade starter pits, stopes

GEOLOGICAL MODELING

3D solids modeling software continues

to advance at rapid pace But basic problem is we continue to

interpret what is on 2D plan or sectionwithout regard to adjacent sections

A big problem where data are missing;under projection is common

Painstaking manual adjustment stillrequired.


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GEOLOGICAL MODELING

When constructing other modelsfor grade, alteration, consider localgeological controls

Ensure that modeler understandsthe controls to prevent timeconsuming editing

ZINC IS STRONGLY RELATED TO PROXIMITY TOSKARN/MARBLE CONTACT AND LESS TO SKARN TYPE

--- 0.25 ---- 1.00 ---- 2.00 --- 3.00 --- 4.00 --- 5.00 ---


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ZINC DOMAINS----- 0.25 % Zn < 2.5 % Zn ----- 2.5% Zn

RESOURCE MODELINGCHOICE OF INTERPOLATION METHOD

Simple methods preferred

-Weighted averages more accuratethan polygonal

-Kriging marginally more accuratethan inverse distance

-Consider when CV < 1.5


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CHOICE OF INTERPOLATIONMETHOD OTHER CRITERIA

To be useful, the resource model should reflectselectivity of mining

Choose kriging neighborhood so distribution ofkriged grades = distribution of selective miningunits (SMUs)

SMU is smallest practical volume that can be

segregated to ore or waste Var SMUs = Var Comps Average( (h) inside

SMU)

KRIGED 20 X 20 m Blocks % Cu--- 0.25--- 0.50 --- 1.00 --- 2.00 --- 3.0 ---


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KRIGED 20 X 20 m Blocks % Cu--- 0.25--- 0.50 --- 1.00 --- 2.00 --- 3.0 ---

RECONCILIATION

Big Problem No One Wants to Talk About Often Done In Pieces May be Obscured/Invalidated by Stockpile

Accounting

Hard to Determine Measurement Problems Accounting Problems People Problems


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RECONCILIATION

Resource Model to Blastholes

Reserve Model to Ore Control

Ore Control to Mill

Reserve Model to Mill

COMPARISON OF RESOURCE MODEL AND BLASTHOLES

----- 0.25 ----- 0.50 ----- 1.00 ---- 2.00 ---- 3.00 ----- % Cu


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BLASTBLOCKS VERSUS RESOURCE MODEL

BLOCKS FOR COPPER INDICATEDBLOCKS (50 M NOMINAL SPACING)

BLASTBLOCKS VERSUS RESOURCE MODEL

BLOCKS FOR COPPER MEASUREDBLOCKS (25-30 M NOMINAL SPACING)


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CHOICE OF INTERPOLATIONMETHOD CONDITIONAL BIAS

Kriged estimates that match SMU distributionmay be locally conditionally biased

Blocks estimated to be high grade will actually

have lower grades; blocks estimated to be lowgrade will actually have higher grades

We give up accuracy and accept this bias sothat globally tonnage-grade curve matches

SMUs. Internal dilution predicted correctly.

CONDITIONAL BIAS CHECK

Some conditional bias for Indicated

No conditional bias for Measured

Recognize that block model good forquarterly, semi-annual planning. Finalore/waste selection done later usingblasthole samples.

Alternatives: Use non-linear method ORBetter: drill more close-spaced holes


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RESOURCE TO RESERVE CONVERSION ULTIMATE PIT LIMITS AND MINE PLANS

RESERVE MODEL TO ORECONTROL RECONCILIATION


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FACTORS

F1 = Grade Control Depletions

Reserve Model Depletions

F2 = Received at Mill (heads)

Delivered to Mill (grade control)

F3 = Grade Control Depletions x Received at Mill

Reserve Model Deplet. Delivered to Mill

F2 = Received at Mill (heads)

Delivered to Mill (grade control)

F1

F2

F1 = Grade Control Depletions

Reserve Model Depletions



F3


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F1

F1 = Grade Control DepletionsReserve Model Depletions

Measures Local Accuracy of Reserve ModelChecks to See if Right Support Implicit in Reserve ModelMeasures Bias of Grade Control Assays

F2 = Received at Mill (heads)Delivered to Mill (grade control)

Measures Efficiency of Mining (unplanned ore loss,

dilution)

Measures Bias Between Grade Control and Mill

F2

F1


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Measures Ability of Reserves to Predict Recoverable

Tonnage, Grade, Metal to Mill

F2

F1

F3



RECONCILIATION FOR COPPERONLY ORES 2003-2004

Statistics Mt % Cu % Zn

Resource Model Depletions 30.5 1.51 0.25

Ore Control Polygons (OCP) 32.3 1.67 0.22

Received at Mil (RAM) 30.1 1.52 0.25

Factors

F1 = OCP/Res. Mod. Depl. 1.06 1.11 0.89

F2 = RAM/OCP 0.93 0.91 1.11

F3 = RAM/Res. Mod. Depl. 0.99 1.00 0.99

Possible high bias in blast hole grades Some shift of Cu-only to Cu-Zn ores at Mill


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RECONCILIATION FOR COPPER-ZINC ORES 2003-2004

Statistics Mt % Cu % Zn

Resource Model Depletions 23.9 0.96 3.04

Ore Control Polygons (OCP) 27.1 1.07 3.21

Received at Mil (RAM) 27.6 1.01 2.61

Factors

F1 = OCP/Res. Mod. Depl. 1.13 1.11 1.05

F2 = RAM/OCP 1.02 0.94 0.81F3 = RAM/Res. Mod. Depl. 1.15 1.05 0.86

Possible high bias in blast hole grades/OC Model Amount of Cu-Zn ores more than expected Selectivity of Cu-Zn ores worse than expected

RECONCILIATION

Review Past Production Versus Models

Ideally Within 5% (Cu), 10% (Au)- Grade Control to Model Check Planned

Dilution/Ore Loss (Aim for 0%)

- Plant to Grade Control Check UnplannedDilution/Ore Loss (Within 5-10%)

If You Do Not Measure It, You Cannot ControlIt!!!!!!!!

RECONCILIATION [Modo de Compatibilidad]

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