Conditional Simulation for Mineral Resource Classification and Mining Dilution Assessment from the Early 1990s to Now

Abstract

Andre Journel joined Stanford University in 1978, and his program grew quickly to include a dozen students from the USA, Canada, Europe, and South Africa. He was instrumental in organizing the Second International Geostatistical Conference (Tahoe ’83), during which 13 papers were presented that can be linked to his group. Out of these 13 papers, 9 were mining-related, with 7 on recoverable reserves, 2 on uncertainty, 2 on conditional simulation, and 3 on nonparametric geostatistics. A significant research effort at the time was therefore directed at change of support, global and local recoveries, and uncertainty, but future trends could also be identified, such as nonparametric geostatistics and conditional simulation. This paper is a practical review of conditional simulation as a tool to improve mineral resource estimation in the areas of uncertainty, classification, and mining selectivity or dilution, based on the authors’ experience. Some practical considerations for conditional simulation are briefly discussed. Four case studies from the early 1990s to the late 2010s are presented to illustrate some solutions and challenges encountered when dealing with real-world commercial projects.