Statistical Inversion of Absolute Permeability in Single-phase Darcy Flow

Thilo Strauss, Xiaolin Fan, Shuyu Sun, Taufiquar Khan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


In this paper, we formulate the permeability inverse problem in the Bayesian framework using total variation (TV) and fp (0 < p δ 2) regularization prior. We use the Markov Chain Monte Carlo (MCMC) method for sampling the posterior distribution to solve the ill-posed inverse problem. We present simulations to estimate the distribution for each pixel for the image reconstruction of the absolute permeability.
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Number of pages10
StatePublished - Jun 1 2015


Dive into the research topics of 'Statistical Inversion of Absolute Permeability in Single-phase Darcy Flow'. Together they form a unique fingerprint.

Cite this