Luis Martinez Tipe
This report summarizes an academic study that applied advanced mine planning methodologies to the La Cocota deposit, a large copper porphyry in northern Chile. The research quantitatively and rigorously compared traditional planning techniques with the more recent Direct Block Scheduling (DBS) approach, a concept equivalent to MiningMath’s Single-step Mine Optimization. The thesis is here presented as a structured report for technical teams and managers, emphasizing economic gains, methodological consistency, and the practical applicability of the solution.
Some true/false geostatistic and mine plan optimisation questions to warm up the brain (what do you reckon are these statements true or false?):
1. Kriging and conditional simulation are different processes that output different results.
2. N>>1 equally probable conditional simulations (realisation) of an orebody will generate N equally probable mine plans.
3. Kriging is an expected (average) metal grade block model.
4. The mine plan and design optimisation process is a non-linear process.
5. Kriging block grade model is the best block model to run the mine plan and design optimisation process where the (technical and economic) results, including the mine plan and design, are seen as expected (averages) results.
6. Run of Mine metal grade variability is because geological metal grade uncertainty.
7. Operational uncertainty has nothing to do with run of mine metal grade variability.
8. Cutbacks, or pushbacks, are generated/designed before the mine scheduling.
9. The main sources of uncertainty when planning and designing a mine project are: geological, capex, operational, and economic.
10. The mine project evaluation process (that includes the mine plan, design and valuation processes) is a forecasting process.