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

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Abstract

André 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.

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Acknowledgements

The authors would like to thank the John Wood Group plc for permission to publish this paper. They also thank the reviewers whose comments and suggestions helped improve the paper.

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  1. Wood Canada, Suite 400, 111 Dunsmuir Street, Vancouver, BC, V6B 5W3, Canada

    Georges Verly

  2. Wood Group USA Inc, Suite 201, 9460 Double R Boulevard, Reno, NV, 89521, USA

    Harry M. Parker

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  1. Georges Verly
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Correspondence to Georges Verly.

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Verly, G., Parker, H.M. Conditional Simulation for Mineral Resource Classification and Mining Dilution Assessment from the Early 1990s to Now. Math Geosci 53, 279–300 (2021). https://doi.org/10.1007/s11004-021-09924-2

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