Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 1 — Methodology

The focus of our study is lithology/fluid inversion with spatial coupling from prestack seismic amplitude variation with offset (AVO) data and well observations. The inversion is defined in a Bayesian setting where the complete solution is the posterior model. The prior model for the lithology/fluid (LF) characteristics is defined as a profile Markov random-field model with lateral continuity. Each vertical profile is further given as an inhomogeneous Markov-chain model upward through the reservoir. The likelihood model is defined by profile, and it relates the LF characteristics to the seismic data via a set of elastic material parameters and a convolution model. The likelihood model is approximated. The resulting approximate posterior model is explored using an efficient block Gibbs simulation algorithm. The inversion approach is evaluated on a synthetic realistic 2D reservoir. Seismic AVO data and well observations are integrated in a consistent manner to obtain predictions of the LF characteristics wi...

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