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Comparison of Four Competing Invasion Percolation Models for Gas Flow in Porous Media
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  • Ishani Banerjee,
  • Anneli Guthke,
  • Cole J.C. Van De Ven,
  • Kevin G Mumford,
  • Wolfgang Nowak
Ishani Banerjee
Universität Stuttgart

Corresponding Author:[email protected]

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Anneli Guthke
Universität Stuttgart
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Cole J.C. Van De Ven
Carleton University
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Kevin G Mumford
Queen's University
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Wolfgang Nowak
Universität Stuttgart
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Abstract

Numerous variations of Invasion-Percolation (IP) models can simulate multiphase flow in porous media across various scales (pore-scale IP to macroscopic IP); here, we are interested in gas flow in water-saturated porous media. This flow occurs either as continuous or discontinuous flow, depending on the flow rate and the porous medium’s nature. Literature suggests that IP models are well suited for the discontinuous gas flow regime; other flow regimes have not been explored. Our research compares four existing macroscopic IP models and ranks their performance in these “other” flow regimes. We test the models on a range of gas-injection in water-saturated sand experiments from transitional and continuous gas flow regimes. Using the light transmission technique, the experimental data is obtained as a time series of images in a 2-dimensional setup. To represent pore-scale heterogeneities, we ran each model version on several random realizations of the initial entry pressure field. We use a diffused version of the so-called Jaccard coefficient to rank the models against the experimental data. We average the Jaccard coefficient over all realizations per model version to evaluate each model and calibrate specific model parameters. Depending on the application domain, we observe that some macroscopic IP model versions are suitable in these previously unexplored flow regimes. Also, we identify that the initial entry pressure fields strongly affect the performance of these models. Our comparison method is not limited to gas-water systems in porous media but generalizes to any modelling situation accompanied by spatially and temporally highly resolved data.
30 Aug 2023Submitted to ESS Open Archive
08 Sep 2023Published in ESS Open Archive