An efficient two-stage Markov chain Monte Carlo method for dynamic data integration
Article first published online: 20 DEC 2005
Copyright 2005 by the American Geophysical Union.
Water Resources Research
Volume 41, Issue 12, December 2005
How to Cite
2005), An efficient two-stage Markov chain Monte Carlo method for dynamic data integration, Water Resour. Res., 41, W12423, doi:10.1029/2004WR003764., , , , and (
- Issue published online: 20 DEC 2005
- Article first published online: 20 DEC 2005
- Manuscript Accepted: 7 SEP 2005
- Manuscript Revised: 10 JUN 2005
- Manuscript Received: 26 OCT 2004
- acceptance rate
 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.