Geostatistical Methods for Reservoir Geophysics

ISBN-13: 9783319850887 / Angielski / Miękka / 2018 / 141 str.

Leonardo Azevedo; Amilcar Soares

Spis treści

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.- Afterword.

O autorze

Leonardo Azevedo is Professor at the Instituto Superior Técnico, Lisboa, Portugal. He received his Ph.D. in Georesources in 2013 in the same university where he developed geostatistical tools for inverting seismic reflection data. During this period, he had three short-term contracts with the industry after which he joined CGG’s Geosolutions team in Crawley (UK).  He returned to Técnico in 2015 where he teaches and develop research related with geophysical inversion, reservoir modeling and characterization, rock physics modeling and data integration.

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.

Blurb

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.