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.
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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.
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Destinos, gastos y plazos de envíoLibrería: Prior Books Ltd, Cheltenham, Reino Unido
Paperback. Condición: Like New. First Edition. 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. Nº de ref. del artículo: 210018
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Librería: Chequamegon Books, Washburn, WI, Estados Unidos de America
Paperback. Condición: Very Good+. Cover corners are lightly bumped; front cover down long edge has a slight bend; various page corners are creased. ; Standford Geostatistical Modeling Software (SGeMS). Provides step-by-step instructions to using SGeMS algorithms, while explaining the underlying theory, demonstrates the implementation of the various algorithms, discusses their potential limitations, and helps the user make informed decisions about the choice of one algorithm over another. ; 6 3/4 x 9 3/4"; 264 pages. Nº de ref. del artículo: 114054
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. reprint edition. 264 pages. 9.50x6.50x0.75 inches. In Stock. This item is printed on demand. Nº de ref. del artículo: __1107403243
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Condición: Good. Item in good condition and has highlighting/writing on text. Used texts may not contain supplemental items such as CDs, info-trac etc. Nº de ref. del artículo: 00089977062
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PF. Condición: New. Nº de ref. del artículo: 6666-IUK-9781107403246
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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, . Nº de ref. del artículo: 127684921
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Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 286. Nº de ref. del artículo: 263065641
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