Applied Geostatistics with SGeMS: A User's Guide

Remy, Nicolas; Boucher, Alexandre; Wu, Jianbing

ISBN 10: 1107403243 / ISBN 13: 9781107403246

Verlag: Cambridge University Press, 2011

Beschreibung

In nearly new condition: firm and square with strong joints, no creases. Just a few hardly noticeable rubs. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.

Bestandsnummer des Verkäufers 210018

Bibliografische Details

• Titel: Applied Geostatistics with SGeMS: A User's Guide
• Verlag: Cambridge University Press
• Erscheinungsjahr: 2011
• Sprache: Englisch
• ISBN-10: 1107403243
• ISBN-13: 9781107403246
• Einband: Paperback
• Auflage: First Edition.
• Zustand: Like New
• Gewicht: 16 Unzen
• Verkäuferkataloge:
  • Science, Mathematics & Technology

Über diesen Titel

Inhaltsangabe

This practical book provides a detailed guide to using algorithms from the Stanford Geostatistical Modeling Software (SGeMS), an open-source computer package for solving problems involving spatially related variables. Accompanied by a CD with the software, it's a useful user-guide for Earth Science graduates, and practitioners of environmental and petroleum engineering.

Über die Autorin bzw. den Autor

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.