Statistical Inversion of Absolute Permeability in Single-phase Darcy Flow
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Conference PaperKAUST Department
Computational Transport Phenomena LabEarth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Date
2015-06-01Online Publication Date
2015-06-01Print Publication Date
2015Permanent link to this record
http://hdl.handle.net/10754/556696
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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.Citation
Statistical Inversion of Absolute Permeability in Single-phase Darcy Flow 2015, 51:1188 Procedia Computer SciencePublisher
Elsevier BVJournal
Procedia Computer ScienceConference/Event name
International Conference on Computational Science, ICCS 2002Additional Links
http://linkinghub.elsevier.com/retrieve/pii/S1877050915010996ae974a485f413a2113503eed53cd6c53
10.1016/j.procs.2015.05.291