Coarse scale models of two-phase flow in heterogeneous reservoirs: Volume averaged equations and their relationship to existing upscaling techniques
From MaRDI portal
Publication:1299115
DOI10.1023/A:1011593901771zbMath0943.76085OpenAlexW260872158MaRDI QIDQ1299115
Publication date: 5 September 2000
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1023/a:1011593901771
two-phase flowhigher momentsaverage saturation equationcoarse scale descriptionnon-uniform coarsening of fine grid geostatistical modelpseudo-relative permeability
Hydrology, hydrography, oceanography (86A05) Flows in porous media; filtration; seepage (76S05) Liquid-gas two-phase flows, bubbly flows (76T10) Potentials, prospecting (86A20)
Related Items
Multiscale numerical methods for passive advection-diffusion in incompressible turbulent flow fields, Coarse-Grid Multiscale Model Reduction Techniques for Flows in Heterogeneous Media and Applications, A Bayesian framework for the validation of models for subsurface flows: synthetic experiments, Accurate multiscale finite element methods for two-phase flow simulations, Multiscale finite element methods for porous media flows and their applications, Analytical and variational numerical methods for unstable miscible displacement flows in porous media, A locally conservative multiscale method for stochastic highly heterogeneous flow, Error estimates for a mixed finite element discretization of a two-phase porous media flow model with dynamic capillarity, Constraint energy minimizing generalized multiscale finite element method in the mixed formulation, Generalized multiscale approximation of mixed finite elements with velocity elimination for subsurface flow, A framework for the upscaling of the electrical conductivity in the quasi-static Maxwell's equations, Ensemble level multiscale finite element and preconditioner for channelized systems and applications, Ensemble level upscaling for compositional flow simulation, Coarse-gradient Langevin algorithms for dynamic data integration and uncertainty quantification, Machine-learning-based modeling of coarse-scale error, with application to uncertainty quantification
