An efficient two-stage Markov chain Monte Carlo method for dynamic data integration
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 In this paper, we use a two-stage Markov chain Monte Carlo (MCMC) method for subsurface characterization that employs coarse-scale models. The purpose of the proposed method is to increase the acceptance rate of MCMC by using inexpensive coarse-scale runs based on single-phase upscaling. Numerical results demonstrate that our approach leads to a severalfold increase in the acceptance rate and provides a practical approach to uncertainty quantification during subsurface characterization. Copyright 2005 by the American Geophysical Union.
author list (cited authors)
Efendiev, Y., Datta-Gupta, A., Ginting, V., Ma, X., & Mallick, B.
complete list of authors
Efendiev, Y||Datta-Gupta, A||Ginting, V||Ma, X||Mallick, B