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Title: A multi-scale network method for two-phase flow in porous media

Abstract

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

Authors:
;
Publication Date:
OSTI Identifier:
22622312
Resource Type:
Journal Article
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 342; Other Information: Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-9991
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; ALGORITHMS; APPROXIMATIONS; BOUNDARY CONDITIONS; CAPILLARIES; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; FLOW RATE; FLUIDS; INTERFACES; MATHEMATICAL SOLUTIONS; PARTITION; POROUS MATERIALS; SOLUTIONS; TWO-PHASE FLOW; VISCOSITY

Citation Formats

Khayrat, Karim, and Jenny, Patrick. A multi-scale network method for two-phase flow in porous media. United States: N. p., 2017. Web. doi:10.1016/J.JCP.2017.04.023.
Khayrat, Karim, & Jenny, Patrick. A multi-scale network method for two-phase flow in porous media. United States. https://doi.org/10.1016/J.JCP.2017.04.023
Khayrat, Karim, and Jenny, Patrick. 2017. "A multi-scale network method for two-phase flow in porous media". United States. https://doi.org/10.1016/J.JCP.2017.04.023.
@article{osti_22622312,
title = {A multi-scale network method for two-phase flow in porous media},
author = {Khayrat, Karim and Jenny, Patrick},
abstractNote = {Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.},
doi = {10.1016/J.JCP.2017.04.023},
url = {https://www.osti.gov/biblio/22622312}, journal = {Journal of Computational Physics},
issn = {0021-9991},
number = ,
volume = 342,
place = {United States},
year = {Tue Aug 01 00:00:00 EDT 2017},
month = {Tue Aug 01 00:00:00 EDT 2017}
}