A Multi-Stage Methodology for Long-Term Open-Pit Mine Production Planning under Ore Grade Uncertainty

Enrique Jelvez, Julian Ortiz, Nelson Morales Varela (), Hooman Askari-Nasab and Gonzalo Nelis
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Enrique Jelvez: Advanced Mining Technology Center, Delphos Mine Planning Laboratory & Department of Mining Engineering, Universidad de Chile, Santiago 8370448, Chile
Julian Ortiz: The Robert M. Buchan Department of Mining, Queen’s University, Kingston, ON K7L 3N6, Canada
Nelson Morales Varela: Département de Génies Civil, Géologique et des Mines, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
Hooman Askari-Nasab: Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Gonzalo Nelis: Research and Innovation in Mining Group (RIMG), DIMM—Universidad Técnica Federico Santa María, Av. Vicuña Mackena 3939, San Joaquín, Santiago 8940897, Chile

Mathematics, 2023, vol. 11, issue 18, 1-19

Abstract: The strategic planning of open pit operations defines the best strategy for extraction of the mineral deposit to maximize the net present value. The process of strategic planning must deal with several sources of uncertainty; therefore, many authors have proposed models to incorporate it at each of its stages: Computation of the ultimate pit, optimization of pushbacks, and production scheduling. However, most works address it at each level independently, with few aiming at the whole process. In this work, we propose a methodology based on new mathematical optimization models and the application of conditional simulation of the deposit for addressing the geological uncertainty at all stages. We test the method in a real case study and evaluate whether incorporating uncertainty increases the quality of the solutions. Moreover, we benefit from our integrated framework to evaluate the relative impact of uncertainty at each stage. This could be used by decision-makers as a guide for detecting risks and focusing efforts.

Keywords: geological uncertainty; geostatistics; open-pit mine production planning; surface mining; stochastic mixed-integer linear programming; uncertainty assessment (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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