Geostatistics for Mineral Resource Estimation
Geostatistics is the most efficient and powerful framework to characterise, estimate and manage your mineral resource.
Geologists or mining engineers can apply geostatistics at all stages of the mine life cycle: from exploration to development, production and even for site remediation. Geostatistics offers a wide range of methodologies adapted to all commodities and styles of deposits.
Geovariances’ scientific rigour, continuous innovation and geostatistical expertise guarantee the quality of your evaluations at different stages of the development of your projects (feasibility studies, bankable studies, desktop reviews, etc.).
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Resources
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Amélioration de l’estimation des teneurs en alumine d’un gisement de kaolin à l’aide des simulations par bandes tournantes | XVe Journées de géostatistique 2021 - V. Bouchet (Imerys), M.C. Febvey (Geovariances), Hélène Binet (Geovariances), Armand Dubus (Geovariances)
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Co-kriging of log ratios: a worked alternative method | Clint Ward, Cliffs, Ute Mueller ECU
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Local Uncertainty Benchmarking – A coal case study | Written by C. Mawdesley, D. Barry, O. Bertoli and R. Saha
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Sensitivity study of the estimation variance approximation of a quotient | Comparison with Conditional Simulations in the Mn Deposit of Bangombé (Gabon)
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Data classification using geostatistical hierarchical clustering for robust and dynamic domaining
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Implication of geological domains data for modeling and estimating resources from NKout iron deposit (South-Cameroun) | Implication of geological domains data for modeling and estimating resources from NKout iron deposit (South-Cameroun)
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Full paper: On measuring the spatial sampling density of a deposit for mineral resource classification | Full paper - On measuring the spatial sampling density of a deposit for mineral resource classification by Marie-Cécile Febvey, Benjamin Martin and Jacques Rivoirard
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Poster: On measuring the spatial sampling density of a deposit for mineral resource classification | On measuring the spatial sampling density of a deposit for mineral resource classification by Marie-Cécile Febvey, Benjamin Martin and Jacques Rivoirard
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Application of Pluri-Gaussian simulations and conditional simulation for geological modelling and estimation of a nickel deposit in New Caledonia | Febvey, M C, Desassis, N, Le Guen, M and Isatelle, F, 2019 - Proceedings Mining Geology 2019, pp 135–149 (The Australasian Institute of Mining and Metallurgy: Melbourne)
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How the use of stratigraphic coordinates improves grade estimation | Rubio, Ricardo Hundelshaussen, Koppe, Vanessa Cerqueira, Costa, João Felipe Coimbra Leite, & Cherchenevski, Pablo Koury. (2015) - Rem: Revista Escola de Minas, 68(4), 471-477. https://doi.org/10.1590/0370-44672015680057