This work aims to describe the spatial distribution of flow from characteristics of the underlying pore structure in heterogeneous porous media. Thousands of two-dimensional samples of polydispersed granular media are used to (1) obtain the velocity field via direct numerical simulations, and (2) conceptualize the pore network as a graph in each sample. Analysis of the flow field allows us to distinguish preferential from stagnant flow regions and to quantify how channelized the flow is. Then, the graph's edges are weighted by geometric attributes of their corresponding pores to find the path of minimum resistance of each sample. Overlap between the preferential flow paths and the predicted minimum resistance path determines the accuracy in individual samples. An evolutionary algorithm is employed to determine the "fittest" weighting scheme (here, the channel's arc length to pore throat ratio) that maximizes accuracy across the entire dataset while minimizing over-parameterization. Finally, the structural similarity of neighboring edges is analyzed to explain the spatial arrangement of preferential flow within the pore network. We find that connected edges within the preferential flow subnetwork are highly similar, while those within the stagnant flow subnetwork are dissimilar. The contrast in similarity between these regions increases with flow channelization, explaining the structural constraints to local flow. The proposed framework may be used for fast characterization of porous media heterogeneity relative to computationally expensive direct numerical simulations.
机构:
Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R China
Tang, Y. B.
Zhao, J. Z.
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Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R China
Zhao, J. Z.
Bernabe, Y.
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MIT, Dept Earth Atmospher & Planetary Sci, Cambridge, MA 02139 USASouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R China
Bernabe, Y.
Li, M.
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Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu, Peoples R China