Multiscale computation of pore-scale fluid dynamics: Single-phase flow

Direct numerical simulation (DNS) of interstitial fluid dynamics in porous media is hindered by the sheer size and complexity of the discretized equations. While reduced-complexity methods such as pore-network models (PNM) can occasionally yield satisfactory solutions at a much lower cost, they can...

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Bibliographic Details
Published in:Journal of computational physics Vol. 375; pp. 1469 - 1487
Main Authors: Mehmani, Yashar, Tchelepi, Hamdi A.
Format: Journal Article
Language:English
Published: Cambridge Elsevier Inc 15.12.2018
Elsevier Science Ltd
Subjects:
Approximation
Basis functions
Boundary conditions
Complexity
Computational fluid dynamics
Computational physics
Computer simulation
Direct numerical simulation
Domain decomposition
Fluid dynamics
Iterative correction
Iterative methods
Mathematical models
Multiscale analysis
Multiscale method
Navier-Stokes equations
Navier–Stokes equation
Parallel processing
Pore-scale modeling
Porous media
Single-phase flow
Porous media
Iterative correction
Navier–Stokes equation
Multiscale method
Domain decomposition
Pore-scale modeling
ISSN:0021-9991, 1090-2716
Online Access:Get full text
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Summary:Direct numerical simulation (DNS) of interstitial fluid dynamics in porous media is hindered by the sheer size and complexity of the discretized equations. While reduced-complexity methods such as pore-network models (PNM) can occasionally yield satisfactory solutions at a much lower cost, they can neither estimate nor control their error. We focus on the single-phase Navier–Stokes equations and develop a computationally efficient multiscale method that produces a sequence of increasingly accurate approximations to DNS. The pore-level multiscale method (PLMM) decomposes the pore space into several subdomains and constructs a set of local basis functions on them. The bases are coupled with a global interface problem to obtain an initial approximation to DNS. The approximation is excellent because subdomains coincide with physical pores in the void space and physics-informed boundary conditions are used to construct the bases. Errors in the initial approximation can be arbitrarily reduced with an iterative strategy presented. The method is parallelizable, memory efficient, and allows for different physics, models, and meshes to be incorporated within each subdomain. •Multiscale method developed for single-phase Navier–Stokes at the pore scale.•Multiscale predictions are in excellent agreement with single-scale DNS.•Iterative strategy developed for estimating and controlling multiscale errors.•Multiscale method is a more accurate alternative to pore network modeling.
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ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2018.08.045