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Book Chapter

Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review

By
Miguel Bosch
Miguel Bosch
1Universidad Central de Venezuela, Caracas, Venezuela. E-mail: miguel.bosch@ucv.ve; miguel.bosch@cantv.net.
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Tapan Mukerji
Tapan Mukerji
2Stanford University, Center for Reservoir Forecasting, Department of Energy Resources Engineering, Stanford, California, U.S.A. E-mail: mukerji@stanford.edu.
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Ezequiel F. Gonzalez
Ezequiel F. Gonzalez
3Shell International Exploration and Production Inc., Houston, Texas, U.S.A. E-mail: ezequiel.gonzalez@shell.com.
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Published:
January 01, 2010

Abstract

There are various approaches for quantitative estimation of reservoir properties from seismic inversion. A general Bayesian formulation for the inverse problem can be implemented in two different work flows. In the sequential approach, first seismic data are inverted, deterministically or stochastically, into elastic properties; then rock-physics models transform those elastic properties to the reservoir property of interest. The joint or simultaneous work flow accounts for the elastic parameters and the reservoir properties, often in a Bayesian formulation, guaranteeing consistency between the elastic and reservoir properties. Rock physics plays the important role of linking elastic parameters such as impedances and velocities to reservoir properties of interest such as lithologies, porosity, and pore fluids. Geostatistical methods help add constraints of spatial correlation, conditioning to different kinds of data and incorporating subseismic scales of heterogeneities.

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Contents

Geophysical References Series

Geophysics Today: A Survey of the Field as the Journal Celebrates its 75th Anniversary

Sergey Fomel
Sergey Fomel
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Society of Exploration Geophysicists
Volume
16
ISBN electronic:
9781560802273
Publication date:
January 01, 2010

GeoRef

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