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Persistent Identifier
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doi:10.15786/LSKYKF |
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Publication Date
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2026-10-13 |
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Title
| Interpretable Pressure-dependent Permeability Modeling for Confined Gas Transport in Complex Nano-Porous Media |
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Author
| Aryana, Saman A. (University of Wyoming) - ORCID: 0000-0001-9509-7420
Yang, Qian (University of Wyoming) - ORCID: 0000-0002-9616-9753
Delos, Mo K. (University of Wyoming)
Rustamov, Nijat (University of Wyoming) - ORCID: 0009-0000-2278-8060 |
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Point of Contact
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Use email button above to contact.
Rustamov, Nijat (University of Wyoming) |
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Description
| This dataset contains the processed data and analysis code for the study "Interpretable Pressure-dependent Permeability Modeling for Confined Gas Transport in Complex Nano-Porous Media". The study derives a closed-form ("white-box") model of apparent gas permeability in nano-porous media such as shale.
In this work we use a data-driven workflow to uncover the relationship between apparent gas permeability and the morphological and network-theoretic descriptors of the pore space. Over 5,000 2D porous-media images are generated at 1 nm resolution, and gas transport is modeled with the lattice Boltzmann method (LBM) on high-performance computing resources. A large set of descriptors including porosity, pore-size distribution, morphology, and network-theoretic descriptors are extracted from each sample. Feature selection is followed by symbolic regression, which produces interpretable and physically consistent correlations for permeability. The correlation is then coupled with a power-law Knudsen correction to obtain a pressure-dependent, white-box apparent-permeability model. We apply this model end-to-end on a sample of Mowry shale, covering SEM imaging, stitching, segmentation, reconstruction, and permeability prediction, and compare it with LBM simulations across two orders of magnitude in pressure. The workflow offers a route to estimating apparent permeability in shale at a fraction of the cost of direct simulation. |
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Subject
| Engineering |
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Keyword
| symbolic regression
white-box modeling
lattice Boltzmann method
Knudsen number
gas slippage
nano-porous media
digital rock
pore-network descriptors
Mowry Shale
SEM imaging |
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Topic Classification
| petroleum and chemical engineering
computational fluid dynamics
digital rock physics |
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Related Publication
| Is Supplement To: Rustamov, N., Yang, Q., Delos, M. K., & Aryana, S. A. (2026). Interpretable pressure-dependent permeability modeling for confined gas transport in complex nano-porous media. Advances in Water Resources, 105527. doi 10.1016/j.advwatres.2026.105527 https://doi.org/10.1016/j.advwatres.2026.105527 |
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Notes
| Information about funding sources that supported the collection of the data:
Mowry Shale initiative, School of Energy Resources, University of Wyoming.
Argonne Leadership Computing Facility, a U.S. Department of Energy Office of Science User Facility operated under contract DE-AC02-06CH11357. Simulations were run on Aurora through an Aurora Discretionary Allocation (Allocation ID: 15785).
Access to the Wind River FIB-SEM was provided by the Center for Advanced Scientific Instrumentation (CASI), University of Wyoming, and the Wyoming Innovation Partnership (WIP). |
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Funding Information
| School of Energy Resources, University of Wyoming: Mowry Shale initiative
Argonne Leadership Computing Facility, a U.S. Department of Energy Office of Science User Facility operated under contract DE-AC02-06CH11357: Allocation ID: 15785
Center for Advanced Scientific Instrumentation (CASI): Wind River FIB-SEM access
Wyoming Innovation Partnership (WIP): Wind River FIB-SEM access
University of Wyoming: Wind River FIB-SEM access |
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Depositor
| Rustamov, Nijat |
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Deposit Date
| 2026-10-13 |
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Date of Collection
| Start Date: 2024-01-01; End Date: 2026-09-01 |
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Software
| Python, Version: 3.11 and 3.14
PySR, Version: 1.5.10 (requires Julia)
Marlin GPU lattice Boltzmann code, Version: 0.1.0 (https://github.com/idaholab/marlin) |
