Geostatistical Methods for Reservoir Geophysics / Advances in Oil and Gas Exploration & Production (PDF)
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This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers extensive geostatistical background information, including detailed descriptions of the main geostatistical tools traditionally used in Earth related sciences to infer the spatial distribution of a given property of interest. This framework is then directly linked with applications in the oil and gas industry and how it can be used as the basis to simultaneously integrate geophysical data (e.g. seismic reflection data) and well-log data into reservoir modeling and characterization. All of the cutting-edge methodologies presented here are first approached from a theoretical point of view and then supplemented by sample applications from real case studies involving different geological scenarios and different challenges. The book offers a valuable resource for students who are interested in learning more about the fascinating world of geostatistics and reservoir modeling and characterization. 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.
Amilcar Soares is Full Professor at the Instituto Superior Técnico (University of Lisbon) in Portugal and Visiting Professor at some other schools at UAE and Brasil. He is coordinator of the group for Modelling Petroleum Reservoirs, from CERENA (Research Center) at IST. He is the coordinator of the Petroleum Engineering PhD and Master programs of IST. His most recent R&D work is focused on geostatistical methods applied to seismic characterization of oil reservoirs, reservoir engineering and geomechanical modelling of oil reservoirs.
- Autoren: Leonardo Azevedo , Amílcar Soares
- 2017, 1st ed. 2017, 141 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319532014
- ISBN-13: 9783319532011
- Erscheinungsdatum: 07.04.2017
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- Dateiformat: PDF
- Grösse: 9.65 MB
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