This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a known velocity covariance function. In the hierarchical model, we represent (random) concentration in terms of its cross-sectional average and a variation function. We derive a one-dimensional stochastic advection-dispersion-type equation for the average concentration and a stochastic Poisson equation for the variation function, as well as expressions for the effective velocity and dispersion coefficient. We observe that velocity fluctuations enhance dispersion in a non-monotonic fashion: the dispersion initially increases with correlation length ?, reaches a maximum, and decreases to zero at infinity. Maximum enhancement can be obtained at the correlation length about 0.25 the size of the porous media perpendicular to flow.
Revised: August 24, 2020 |
Published: September 28, 2017
Citation
Xu Z., and A.M. Tartakovsky. 2017.Method of model reduction and multifidelity models for solute transport in random layered porous media.Physical Review E 96, no. 3:Article No. 033314.PNNL-SA-119187.doi:10.1103/PhysRevE.96.033314