Uncertainty Quantification in Scale‐Dependent Models of Flow in Porous Media. Issue 11 (19th November 2017)

• Record Type: Journal Article
• Authors: Tartakovsky, A. M.; Panzeri, M.; Tartakovsky, G. D.; Guadagnini, A.
• Is Part Of: Water resources research. Volume 53:Issue 11(2017)
• Page Start: 9392
• Page End: 9401
• Publication Date: 2017-11-19
• Subjects: flow in porous media -- randomness -- uncertainty quantification -- scale dependence; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2017WR020905
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Equations governing flow and transport in randomly heterogeneous porous media are stochastic and scale dependent. In the moment equation (ME) method, exact deterministic equations for the leading moments of state variables are obtained at the same support scale as the governing equations. Computable approximations of the MEs can be derived via perturbation expansion in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for standard deviation smaller than one. Here, we consider steady‐state saturated flow in a porous medium with random second‐order stationary conductivity field. We show it is possible to identify a support scale η ∗, where the typically employed approximate formulations of MEs yield accurate (statistical) moments of a target state variable. Therefore, at support scale η ∗ and larger, MEs present an attractive alternative to slowly convergent Monte Carlo (MC) methods whenever lead‐order statistical moments of a target state variable are needed. We also demonstrate that a surrogate model for statistical moments can be constructed from MC simulations at larger support scales and be used to accurately estimate moments at smaller scales, where MC simulations are expensive and the ME method is not applicable. Plain Language Summary: Equations governing flow and transport in randomly heterogeneous porous media are stochastic and scale dependent. In the moment equation method, exact deterministic equations for the leading moments of state variables are obtained at the same support scale as the governing equations. Computable approximations of these equations can be derived via perturbation expansion in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for standard deviation smaller than one. Here, we consider steady‐state saturated flow in a porous medium with random second‐order stationary conductivity field. We show it is possible to identify a support scale, where the typically employed approximate formulations of moment equations yield accurate moments of a target state variable. Key Points: Solution of flow equations is scale dependent Accuracy of uncertainty quantification methods is scale dependent We rigorously define relevant scales and present methods to obtain accurate solutions at both large and small scales