A two-stage Markov chain Monte Carlo method for seismic inversion and uncertainty quantification
Abstract
Bayesian methods for full-waveform inversion allow quantification of uncertainty in the solution, including determination of interval estimates and posterior distributions of the model unknowns. Markov chain Monte Carlo (MCMC) methods produce posterior distributions subject to fewer assumptions, such as normality, than deterministic Bayesian methods. However, MCMC is computationally a very expensive process that requires repeated solution of the...
Paper Details
Title
A two-stage Markov chain Monte Carlo method for seismic inversion and uncertainty quantification
Published Date
Nov 1, 2019
Journal
Volume
84
Issue
6
Pages
R1003 - R1020
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