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Geostatistical Methods for Reservoir Geophysics / by Leonardo Azevedo, Amílcar Soares

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Advances in Oil and Gas Exploration & Production | SpringerLink Bücher | Springer eBook Collection Earth and Environmental SciencePublisher: Cham : Springer, 2017Description: Online-Ressource (XXVII, 141 p. 114 illus., 84 illus. in color, online resource)ISBN:
  • 9783319532011
Subject(s): Additional physical formats: 9783319532004 | Druckausg.: 978-3-319-53200-4 | Printed edition: 9783319532004 LOC classification:
  • QC801-809
DOI: DOI: 10.1007/978-3-319-53201-1Online resources: Summary: 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 modelingSummary: Introduction -- Fundamental geostatistical tools for data integration -- Simulation Models of Physical Phenomena in Earth Sciences -- Integration of geophysical data for reservoir modeling and characterization -- Data integration into geostatistical seismic inversion methodologies -- AfterwordPPN: PPN: 1658346378Package identifier: Produktsigel: ZDB-2-EES
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