Geostatistics Toronto 2021: Quantitative Geology and Geostatistics

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· Springer Nature
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This open access book provides state-of-the-art theory and application in geostatistics.

Geostatistics Toronto 2021 includes 28 short abstracts, 18 extended abstracts, and 7 full articles in the fields of geostatistical theory, multi-point statistics, earth sciences, mining, optimal drilling, domains, seismic, classification uncertainty risk, and artificial intelligence and machine learning. All contributions were presented at the 11th International Geostatistics Congress held in virtually at Toronto, Canada, from July 12-16, 2021.

This book is valuable to researchers, scientists, and practitioners in geology, mining, petroleum, geometallurgy, mathematics, and statistics.


Perihal pengarang

Dr. Sebastian Alejandro Avalos Sotomayor is a Mining Engineer and Master in Mining from Universidad de Chile and Ph.D. from Queen’s University. Currently, he is a Postdoctoral Fellow at Queen’s University. With 9 years of experience, he focuses on the application of conventional and advanced predictive modeling techniques in geometallurgical modeling.

Dr. Julian Maximiliano Ortiz Cabrera is a Mining Engineer from Universidad de Chile and Ph.D. from University of Alberta. Currently, he is Head and Associate Professor at Queen’s University, where he teaches geostatistics and surface mining courses and conducts research related to ore body estimation and simulation and geometallurgical modeling. He has over 20 years of consulting experience in ore body modeling, predictive geometallurgy, and technology adoption.

R. Mohan Srivastava obtained his B.Sc. from Massachsetts Institute of Technology and M.Sc. Geostatistics from Stanford University. He has more than 40 years of experience as a geostatistician. He is author of the book “An Introduction to Applied Geostatistics” and of more than 50 technical articles on theory and practice. In mining, his consulting work spans project development from exploration through to short-term production planning.

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