Footprint and Economic Envelope Calculation for Block/Panel Caving Mines Under Geological Uncertainty Emilio Vargas, CSIRO Chile , Delphos Universidad de Chile Nelson Morales, Delphos-AMTC, Universidad de Chile Xavier Emery, AMTC, Universidad de Chile
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Footprint and Economic Envelope Calculation for Block/Panel Caving
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Footprint and Economic Envelope Calculation for Block/Panel Caving Mines Under Geological Uncertainty Emilio Vargas, CSIRO Chile , Delphos Universidad de Chile Nelson Morales, Delphos-AMTC, Universidad de Chile Xavier Emery, AMTC, Universidad de Chile
Introduction
• Traditional underground mine planning methods are based upon deterministic data, therefore plans and decisions may not be robust.
• Including the uncertainty in the resource model and risk analysis in early stages of the project allows making better decisions.
Methodology
1. Develop a procedure for calculating the economic outline of a block/panel caving mine (deterministic case).
2. Generate block model scenarios of the deposit
3. Validate the procedure results against existing tools.
4. Assess geological uncertainty impact on the outline by running the procedure over the scenarios.
PCBC Geovia
Scope
• Strategic mine planning.
• The envelope calculation is applicable for a Block/Panel Caving mine.
• The geological uncertainty is incorporated using conditional geostatistical simulations of a real orebody.
• Dilution is modelled using Laubscher’s approach
Footprint and Outline Computation
Algorithm 1/3
Block Model
Footprint Envelope
• Ultimate Pit Algorithm
MineLink
Algorithm 2/3
Footprint
• For each level:
– Calculate position discounted profit
– Calculate economic value, tonnage and area
• Find optimum level
Validate results with PCBC
3.85
4.32
3.17
3.78
3.95
4.52
3.78
2.30
Ore
co
lum
n
Surf
ace
Algorithm 3/3
Economic Envelope (Outline)
• Cut block model given the economic footprint data
• Compute different slope precedence depending on the level
• Calculate outline using an inverse ultimate pit algorithm
• The kriging grade scenario has one of the worst accumulated footprint economic value for almost all levels.
• Given the 1,000 scenarios, to find the economic footprint in the first level has a probability of 20%, and a 17% near the 50th level, meanwhile to find it in upper levels has a very low probability.
• The economic envelope found using the kriged block model has an economic value below the expected value of the 1,000 scenarios.
Conclusions
• Given the risk analysis, with a 5% risk the economic value of the outline could be 46% less or more than the expected value for the pessimist or optimist scenario respectively (760 MUSD).
• The production level should be placed at the deepest level, which is more likely to be the economic level and the envelope value is near the expected value, better than the kriging’s model result.
• A risk approach in early stages of a mine project allows to take a better decision in terms of the upside and downside potential.
References
• Dimitrakopoulos R., 2011, ‘Stochastic Optimization For Strategic Mine Planning: A Decade of Developments’.
• Diering T., 2000, ‘PC-BC: A Block Cave Design and Draw Control System’.
• Elkington T., Bates L. and Richter O., 2012, ‘Block Caving Outline Optimisation’.
• Diering T., Richter O. and Villa D., 2008, ‘Block Cave Production Scheduling Using PCBC’.
• Vargas M., Morales N. and Rubio E., 2009, ‘A short term mine planning model for open-pit mines with blending constraints’.
• Emery X., Lantuéjoul C., 2006, ‘TBSIM: A computer program for conditional simulation of three-dimensional Gaussian random fields via the turning bands method’.
• Vielma J., Espinoza D. and Moreno E., 2009, ‘Risk control in ultimate pits using conditional simulations’.
Footprint and Economic Envelope Calculation for Block/Panel Caving Mines Under Geological Uncertainty Emilio Vargas, CSIRO Chile, Delphos Universidad de Chile Nelson Morales, Delphos-AMTC, Universidad de Chile Xavier Emery, AMTC, Universidad de Chile