Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review
Top Cited Papers
- 1 September 2010
- journal article
- research article
- Published by Society of Exploration Geophysicists in Geophysics
- Vol. 75 (5), 75A165-75A176
- https://doi.org/10.1190/1.3478209
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.Keywords
This publication has 73 references indexed in Scilit:
- Understanding stochastic inversion: part 2First Break, 2006
- Understanding stochastic inversion: part 1First Break, 2006
- Quantifying the uncertainty in an AVO interpretationGeophysics, 2002
- Achievements and challenges in petroleum geostatisticsPetroleum Geoscience, 2001
- Lithologic tomography: From plural geophysical data to lithology estimationJournal of Geophysical Research, 1999
- Bayesian seismic waveform inversion: Parameter estimation and uncertainty analysisJournal of Geophysical Research, 1998
- Geostatistical inversion - a sequential method of stochastic reservoir modelling constrained by seismic dataFirst Break, 1994
- Multivariate Geostatistics: Beyond Bivariate MomentsPublished by Springer Science and Business Media LLC ,1993
- Formatting and Integrating Soft Data: Stochastic Imaging via the Markov-Bayes AlgorithmPublished by Springer Science and Business Media LLC ,1993
- BAYESIAN ESTIMATION IN SEISMIC INVERSION. PART I: PRINCIPLES1Geophysical Prospecting, 1988