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- W2046907657 abstract "Three-term AVO inversion can be used to estimate P-wave velocity, S-wave velocity, and density perturbations from reflection seismic data. The density term, however, exhibits little sensitivity to amplitudes and, therefore, its inversion is unstable. One way to stabilize the density term is by including a scale matrix that provides correlation information between the three unknown AVO parameters. We investigate a Bayesian procedure to include sparsity and a scale matrix in the three-term AVO inversion problem. To this end, we model the prior distribution of the AVO parameters via a Trivariate Cauchy distribution. We found an iterative algorithm to solve the Bayesian inversion and, in addition, comparisons are provided with the classical inversion approach that uses a Multivariate Gaussian prior. It is important to point out that the Multivariate Gaussian prior allows us to include the correlation of the AVO parameters in the solution of the inverse problem. The Trivariate Cauchy prior not only permits us to incorporate correlation but also leads to high-resolution (broadband) P-wave velocity, S-wave velocity, and density perturbations." @default.
- W2046907657 created "2016-06-24" @default.
- W2046907657 creator A5007988581 @default.
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- W2046907657 date "2011-05-01" @default.
- W2046907657 modified "2023-10-14" @default.
- W2046907657 title "High-resolution three-term AVO inversion by means of a Trivariate Cauchy probability distribution" @default.
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- W2046907657 doi "https://doi.org/10.1190/1.3554627" @default.
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