This book provides a practical perspective of all the processes involved in estimating mineral resources and reserves, including mine-to-mill reconciliation. It provides an integrated step-by-step explanation of processes for performing each step, including insight from academic and industry practitioners. Each chapter details a specific aspect of the estimation processes in a practical manner. It contains examples and case studies to illustrate the practical application of geostatistics in mineral resource estimation, mineral reserve conversion, and reconciliation.
Features
- Provides a step-by-step guide with over 10,000 lines of Python code for hands-on demonstration, from start to finish, for both linear and non-linear geostatistical methods.
- Explains practical geostatistics processes and functionality.
- Simplifies explanation of mathematical /statistical concepts and application.
- Discusses generalised examples to aid the process steps.
- Reviews processes involved in the mineral resources' estimation and ore reserve conversion.
This book is intended for third-year and postgraduate students in Mineral Resources Management, Geology, Spatial Statistics, and Mining Engineering, as well as practising professionals.
Glen Nwaila is the Director of the Wits Mining Institute and Adjunct Professor at the School of Geosciences, University of the Witwatersrand (Wits). Prof. Nwaila's research focuses on improving ore characterisation and modelling to enhance selective mineral resource extraction, minimize environmental impacts, increase profitability, and maximize natural resource utilisation. Specifically, he and his students work on geometallurgy, machine learning, and spatial data analytics research projects related to multiscale and multivariate data integration, big remote sensing, and geochemical data analysis to enable optimal decision-making in the presence of uncertainty. His research interests are (1) the genesis and evaluation of ore deposits, (2) machine learning applied to geoscience and extractive metallurgy, (3) metal accounting, and (4) process optimisation in hydrometallurgical plants. The emphasis of his most recent work has been on the impact of digital transformation in the mining industry and the move toward dry labs and data banks for process simulation and gamification.
Leon Tolmay is the Founder and Managing Director of Tolmay Enterprises and an associate of SmartMin. He has more than 42 years of practical geostatistics in the mining and metals industry. Before founding Tolmay Enterprises, Leon served as Chief Evaluator in charge of Geostatistics and Evaluation for the Sibanye-Stillwater Gold Division, responsible for all resource and reserve modelling and classification. Prior to joining Sibanye Stillwater, Leon was a lead geostatistics consultant for Goldfields. He also worked as a mining surveyor. Throughout his career, Leon has created several geostatistics training guides and taught geostatistics as a guest lecturer in institutes of higher learning. Leon spent the early years of his career under the mentorship of Prof Danie Krige (School of Mining Engineering, University of the Witwatersrand).
Mark Burnett has more than 30 years of experience in the mining industry, including mineral exploration, shaft sinking, managing the geological and mineral resource estimation functions on operational mines, mergers, acquisitions, and asset disposal. Mark is currently part of the Pan European Reserves and Resources Reporting Committee's (PERC) Executive and is one of PERC's representatives on the Committee for Mineral Reserves International Reporting Standards (CRIRSCO). Mark has an MSc degree in Mineral Resource Management from the University of the Free State (South Africa) and an Honours degree in Geology from the University of the Witwatersrand. Mark is a registered Chartered Geologist (CGeol) with the Geological Society of London and a registered European Geologist (EurGeol) with the European Federation of Geologists.
