Pit Optimization on Clustered Realizations: Identifying Functional Scenarios

Abstract

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.