Algorithmic integration of geological uncertainty in pushback designs for complex multiprocess open pit mines

Abstract

Conventional open pit mine design methods ignore geological uncertainty in terms of metal content and material types which can impact the quantities processed in multiple process mining operations. A stochastic framework permits the use of geological simulations to quantify geological uncertainty; however, existing models have either not been extended to pushback design for mines with multiple elements, multiple materials and multiple destinations, or are limited in their ability to incorporate joint local uncertainty represented through sets of geological simulations. This work aims to integrate grade and material uncertainty in pushback design for open pit mines. Two formulations are proposed to modify existing pushback designs to reduce risk in terms of the amounts of material going to each destination, while maintaining similar pushback sizes when compared to the original design. The proposed formulations are applied at BHP Billiton's Escondida Norte mine, Chile, and show a 35-61% reduction in variability in terms of quantities of material sent to the various processes.

Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach

“…This temperature acts as a control parameter of the same units as the cost function. Previous implementation of simulated annealing in mine planning have demonstrated its ability to improve mine production scheduling and pit designs in terms of expected NPV and meeting production targets (Albor & Dimitrakopoulos, 2009;Godoy, 2003;Goodfellow & Dimitrakopoulos, 2013;Leite & Dimitrakopoulos, 2007). Because of this, simulated annealing was chosen among other metaheuristics to solve the problem of optimizing multipit mining complexes while accounting for geological uncertainty.…”

“…2). Several efficient methodologies have been developed in stochastic environments for the mine production scheduling problem (Bendorf & Dimitrakopoulos, 2013;Godoy, 2003;Godoy & Dimitrakopoulos, 2004;Goodfellow & Dimitrakopoulos, 2013;Lamghari & Dimitrakopoulos, 2012;Lamghari, Dimitrakopoulos, & Ferland, 2013;Montiel & Dimitrakopoulos, 2013). The integration of multiple activities during optimization in deterministic frameworks include the work of Hoerger, Seymour, and Hoffman (1999); Wharton (2007); Whittle (2007); Whittle (2010a); Whittle (2010).…”

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

“…Recent work focuses on the development of optimization engines to solve extremely large combinatorial problems involving the complete value chain in Post-print mining complexes (e.g. Goodfellow and Dimitrakopoulos 2013). Combinatorial optimization techniques, such as simulated annealing (e.g.…”

Quantifying the Impacts of Uncertainty

“…The impacts of these types of uncertainty can be quantified by standard applications of geostatistical simulation. Dimitrakopoulos and co-workers have made significant contributions to the integration of in-situ grade and geological uncertainty into optimization algorithms (e.g., Dimitrakopoulos et al 2002;Goodfellow and Dimitrakopoulos 2013).…”