An efficient two-stage Markov chain Monte Carlo method for dynamic data integration Academic Article uri icon


  • [1] 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.

published proceedings


author list (cited authors)

  • Efendiev, Y., Datta-Gupta, A., Ginting, V., Ma, X., & Mallick, B.

citation count

  • 97

complete list of authors

  • Efendiev, Y||Datta-Gupta, A||Ginting, V||Ma, X||Mallick, B

publication date

  • December 2005