Applied Geostatistics with SGeMS: A User's Guide - Hardcover

Remy, Nicolas; Boucher, Alexandre; Wu, Jianbing

Hardcover

ISBN 10: 0521514142 ISBN 13: 9780521514149

Publisher: Cambridge University Press, 2009

Synopsis

The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.

About this title

About the Author

Nicolas Remy received a BS in Mathematics and Physics from Ecole Nationale Superieure des Mines, Nancy, France, a MS in Petroleum Engineering from Stanford University and a PhD in geostatistics from Stanford University. He is currently a Senior Statistician at Yahoo!, leading the Data Mining and User Behavior Modeling group for the Yahoo! Media and Yahoo Communications and Communities business units. His research interests include multiple-points statistics, machine learning, graph theory and data mining. Alexandre Boucher received a B.Eng. in geological engineering from the Ecole Polytechnique de Montreal, Montreal, QC, Canada, an M.Phil. degree from the University of Queensland, Brisbane, Australia, and a Ph.D. from Stanford University, Stanford, CA. He teaches geostatistics in the Department of Environmental Earth System Sciences, Stanford University. He has taught short courses on the subject in the US and Japan. His research interests include geostatistics, data integration, remote sensing, uncertainty modeling, machine learning and probabilistic modeling of spatio-temporal phenomena. Jianbing Wu is a reservoir engineer with the Applied Reservoir Engineering group at ConocoPhillips. His research focuses on static and dynamic reservoir modeling. He received his Ph.D. in Petroleum Engineering in 2007 from Stanford University, and his ME and BS degrees in Mechanical Engineering from University of Science and Technology of China. He is currently a member of SPE, IAMG and SEG.

Edition details

• Publisher: Cambridge University Press
• Publication date: 2009
• Language: English
• ISBN 10: 0521514142
• ISBN 13: 9780521514149
• Binding: Hardcover
• Edition number: 1
• Number of pages: 284