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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.
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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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 264
- Erscheinungstermin: 20. August 2024
- Englisch
- Abmessung: 234mm x 156mm x 19mm
- Gewicht: 603g
- ISBN-13: 9781032599267
- ISBN-10: 103259926X
- Artikelnr.: 70150700
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 264
- Erscheinungstermin: 20. August 2024
- Englisch
- Abmessung: 234mm x 156mm x 19mm
- Gewicht: 603g
- ISBN-13: 9781032599267
- ISBN-10: 103259926X
- Artikelnr.: 70150700
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.
1. Setting the Scene for Mineral Resources Estimation. 2. A Brief History
of Mining Geostatistics. 3. Sampling for Mineral Resources Estimation. 4.
Geological Considerations in Mineral Resources Estimation. 5. Preliminary
Mineral Resources Estimation Processes. 6. Mineral Resources and Mineral
Reserves Estimation Process. 7. Post-Mineral Resources Estimation
Processes. 8. Nonlinear Geostatistical Methods and Conversion of Mineral
Reserves. 9. Grade Control in Mineral Resources Management and Mine
Planning. 10. Mine-to-Mill Reconciliation for Efficiency, Resource
Utilisation, and Profitability. 11. Cut-Off Grade, Net Present Value, and
Profit Margin Optimisation.
of Mining Geostatistics. 3. Sampling for Mineral Resources Estimation. 4.
Geological Considerations in Mineral Resources Estimation. 5. Preliminary
Mineral Resources Estimation Processes. 6. Mineral Resources and Mineral
Reserves Estimation Process. 7. Post-Mineral Resources Estimation
Processes. 8. Nonlinear Geostatistical Methods and Conversion of Mineral
Reserves. 9. Grade Control in Mineral Resources Management and Mine
Planning. 10. Mine-to-Mill Reconciliation for Efficiency, Resource
Utilisation, and Profitability. 11. Cut-Off Grade, Net Present Value, and
Profit Margin Optimisation.
1. Setting the Scene for Mineral Resources Estimation. 2. A Brief History
of Mining Geostatistics. 3. Sampling for Mineral Resources Estimation. 4.
Geological Considerations in Mineral Resources Estimation. 5. Preliminary
Mineral Resources Estimation Processes. 6. Mineral Resources and Mineral
Reserves Estimation Process. 7. Post-Mineral Resources Estimation
Processes. 8. Nonlinear Geostatistical Methods and Conversion of Mineral
Reserves. 9. Grade Control in Mineral Resources Management and Mine
Planning. 10. Mine-to-Mill Reconciliation for Efficiency, Resource
Utilisation, and Profitability. 11. Cut-Off Grade, Net Present Value, and
Profit Margin Optimisation.
of Mining Geostatistics. 3. Sampling for Mineral Resources Estimation. 4.
Geological Considerations in Mineral Resources Estimation. 5. Preliminary
Mineral Resources Estimation Processes. 6. Mineral Resources and Mineral
Reserves Estimation Process. 7. Post-Mineral Resources Estimation
Processes. 8. Nonlinear Geostatistical Methods and Conversion of Mineral
Reserves. 9. Grade Control in Mineral Resources Management and Mine
Planning. 10. Mine-to-Mill Reconciliation for Efficiency, Resource
Utilisation, and Profitability. 11. Cut-Off Grade, Net Present Value, and
Profit Margin Optimisation.