Adaptive multiscale MCMC algorithm for uncertainty quantification in seismic parameter estimation
Online Publication Date2014-08-05
Print Publication Date2014-08-05
Permanent link to this recordhttp://hdl.handle.net/10754/593349
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AbstractFormulating an inverse problem in a Bayesian framework has several major advantages (Sen and Stoffa, 1996). It allows finding multiple solutions subject to flexible a priori information and performing uncertainty quantification in the inverse problem. In this paper, we consider Bayesian inversion for the parameter estimation in seismic wave propagation. The Bayes' theorem allows writing the posterior distribution via the likelihood function and the prior distribution where the latter represents our prior knowledge about physical properties. One of the popular algorithms for sampling this posterior distribution is Markov chain Monte Carlo (MCMC), which involves making proposals and calculating their acceptance probabilities. However, for large-scale problems, MCMC is prohibitevely expensive as it requires many forward runs. In this paper, we propose a multilevel MCMC algorithm that employs multilevel forward simulations. Multilevel forward simulations are derived using Generalized Multiscale Finite Element Methods that we have proposed earlier (Efendiev et al., 2013a; Chung et al., 2013). Our overall Bayesian inversion approach provides a substantial speed-up both in the process of the sampling via preconditioning using approximate posteriors and the computation of the forward problems for different proposals by using the adaptive nature of multiscale methods. These aspects of the method are discussed n the paper. This paper is motivated by earlier work of M. Sen and his collaborators (Hong and Sen, 2007; Hong, 2008) who proposed the development of efficient MCMC techniques for seismic applications. In the paper, we present some preliminary numerical results.
CitationXiaosi Tan*, Richard L. Gibson Jr., Wing Tat Leung, and Yalchin Efendiev (2014) Adaptive multiscale MCMC algorithm for uncertainty quantification in seismic parameter estimation. SEG Technical Program Expanded Abstracts 2014: pp. 4665-4669. doi: 10.1190/segam2014-1256.1
PublisherSociety of Exploration Geophysicists