GIS and Geostatistical Techniques for Groundwater Science, Venkatramanan, Senapathi
Автор: Deutsch Clayton V., Pyrcz Michael J. Название: Geostatistical Reservoir Modeling ISBN: 0199731446 ISBN-13(EAN): 9780199731442 Издательство: Oxford Academ Рейтинг: Цена: 15206.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics.
Описание: This second edition has been revised and updated. It offers flexible and documented programs that are not confined to user-friendly menus. GSLIB provides a source code that can be used as a starting point for custom programs, advanced applications, and research.
Автор: Leonardo Azevedo; Am?lcar Soares Название: Geostatistical Methods for Reservoir Geophysics ISBN: 3319532006 ISBN-13(EAN): 9783319532004 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers them a deeper understanding of the main geostatistical concepts and how geostatistics can be used to achieve better data integration and reservoir modeling.
Автор: M. Armstrong; P.A. Dowd Название: Geostatistical Simulations ISBN: 0792327322 ISBN-13(EAN): 9780792327325 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains selected contributions from the Workshop on Geostatistical Simulations, which was held in Fontainebleau, May 1993. This book raises questions such as: How are simulation methods and simulated images to be assessed? and What properties of simulated images are inherent in the methods used to obtain the images?
Автор: G. Matheron; M. Armstrong Название: Geostatistical Case Studies ISBN: 1556080190 ISBN-13(EAN): 9781556080197 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: These range from a careful variographic analysis on uranium data, through detailed studies on geologically complex deposits right up to the latest nonlinear methods applied to deposits with highly skew data distributions.
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