HR: 1340h
AN: H23F-1495    [Abstracts]
TI: MODFLOW-STO: Stochastic Modeling of Flow in Saturated Porous Media Using MODFLOW-2000
AU: * Liu, G
EM: gliu@ou.edu
AF: Mewbourne School of Petroleum and Geological Engineering The University of Oklahoma, T-301 Sarkeys Energy Center 100 Boyd St., Norman, OK 73019 United States
AU: Zhang, D
EM: donzhang@ou.edu
AF: Mewbourne School of Petroleum and Geological Engineering The University of Oklahoma, T-301 Sarkeys Energy Center 100 Boyd St., Norman, OK 73019 United States
AU: Lu, Z
EM: zhiming@lanl.gov
AF: Los Alamos National Laboratory, Hydrology, Geochemistry, and Geology Group (EES-6), MS T003, Los Alamos National Laboratory, Los Alamos, NM 87545 United States
AB: We developed a stochastic version of MODFLOW, referred to as MODFLOW-STO, for simulating flow in saturated heterogeneous porous media. The model is on the basis of an innovative combination of Karunen-Loéve decomposition, polynomial expansion and perturbation methods. The log conductivity ( lnK) field is first expanded into a series in terms of orthogonal Gaussian standard random variables with their coefficients obtained as the eigenvalues and eigenfunctions of the covariance function of lnK. Next, head h is decomposed with a perturbation expansion as the sum of h⁽ⁿ⁾, n = 0, 1, 2, _, where h⁽ⁿ⁾ represents the nth head term with respect to the standard deviation of lnK. h⁽ⁿ⁾ is further expanded into a polynomial series of (n) products of orthogonal Gaussian standard random variables whose coefficients h⁽ⁿ⁾_{i1,i2,_,in} are deterministic and can be solved recursively from low to high orders. All equations for these coefficients share the exactly same structure with the original flow equation, which allows us to use any existing groundwater simulator to quantify flow uncertainties. The U.S. Geological Survey MODFLOW-2000 model is adopted as a subroutine to compute h⁽ⁿ⁾_{i1,i2,_,in}. The mean and variance of head and flux are calculated using some simple algebraic operations on h⁽ⁿ⁾_{i1,i2,_,in}. In the current version of MODFLOW-STO, h⁽ⁿ⁾ is solved up to the third order in terms of the standard deviation of the log hydraulic conductivity. The model has been tested under a wide range of flow conditions against Monte Carlo (MC) simulations. It has been shown that MODFLOW-STO is capable of providing accurate solutions and requires much less computation effort as compared to the MC analysis. With MODFLOW-STO, subsurface flow uncertainty analysis can be conducted under general field conditions in an efficient, effective manner.
DE: 1800 HYDROLOGY
DE: 1829 Groundwater hydrology
DE: 1847 Modeling
DE: 1869 Stochastic hydrology
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: Fall Meeting 2005