HR: 08:00h
AN: H21K-01 INVITED    [Abstracts]
TI: Efficient, Non-Intrusive Stochastic Approaches for Multiphase Flow in Porous Media
AU: * Zhang, D
EM: donzhang@usc.edu
AF: University of Southern California, Department of Civil and Environmental Engineering, Los Angeles, CA 90089, United States
AU: Li, H
EM: hengli@ou.edu
AF: University of Oklahoma, Mewbourne School of Petroleum and Geological Eng., Norman, OK 73072, United States
AB: We present an accurate and efficient stochastic modeling approach for multiphase flow in porous media. In this approach, the random log transformed permeability (or porosity) field is represented by the Karhunen-Loeve expansion and the fluid saturations and pressures are expressed by the polynomial chaos expansions. Probabilistic collocation method (PCM) is used to determine the coefficients of the polynomial chaos expansions by solving for the fluid saturations (and pressures) at different collocation points via the original partial differential equations. This approach is non-intrusive because it results in independent deterministic differential equations, which similar to the Monte Carlo method, can be implemented with existing codes or simulators. The approach is demonstrated with multiphase flow problems in heterogeneous formations with an existing deterministic simulator. The accuracy, efficiency, and compatibility of this approach are compared against Monte Carlo simulations. This study reveals that while its computational efforts are greatly reduced compared to Monte Carlo method, PCM is able to accurately estimate the statistical moments and probability density functions of the fluid saturations and pressures. Comparisons with other non-intrusive stochastic approaches are also made.
DE: 1829 Groundwater hydrology
DE: 1847 Modeling
DE: 1869 Stochastic hydrology
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: 2007 Fall Meeting