Journal of Applied Mathematics
Volume 2011 (2011), Article ID 535484, 19 pages
doi:10.1155/2011/535484
Research Article

A Parallel Stochastic Framework for Reservoir Characterization and History Matching

1Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
2Chevron ETC, San Ramon, CA 94583, USA
3ConocoPhillips, Houston, TX 77252, USA
4Institute for Computational Engineering and Sciences, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712, USA
5Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA

Received 15 December 2010; Accepted 1 February 2011

Academic Editor: Shuyu Sun

Copyright © 2011 Sunil G. Thomas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The spatial distribution of parameters that characterize the subsurface is never known to any reasonable level of accuracy required to solve the governing PDEs of multiphase flow or species transport through porous media. This paper presents a numerically cheap, yet efficient, accurate and parallel framework to estimate reservoir parameters, for example, medium permeability, using sensor information from measurements of the solution variables such as phase pressures, phase concentrations, fluxes, and seismic and well log data. Numerical results are presented to demonstrate the method.