Journal
TRANSPORT IN POROUS MEDIA
Volume 125, Issue 1, Pages 23-39Publisher
SPRINGER
DOI: 10.1007/s11242-017-0992-z
Keywords
Gas flow in shale; Nanopore; Stochastic; Reconstruction of porous media
Categories
Funding
- Nano Geosciences laboratory at the Bureau of Economic Geology, The University of Texas at Austin
- Mudrock Systems Research Laboratory (MSRL) consortium at the Bureau of Economic Geology, The University of Texas at Austin
- Anadarko
- BP
- Cenovus
- Centrica
- Chesapeake
- Cima
- Cimarex
- Chevron
- Concho
- ConocoPhillips
- Cypress
- Devon
- Encana
- Eni
- EOG
- EXCO
- ExxonMobil
- Hess
- Husky
- Kerogen
- Marathon
- Murphy
- Newfield
- Penn Virginia
- Penn West
- Pioneer
- Samson
- Shell
- Statoil
- Talisman
- Texas American Resources
- The Unconventionals
- U.S. Enercorp
- Valence
- YPF
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Shale samples consist of two major components: organic matter (OM) and inorganic mineral component (iOM). Each component has its distinct pore network topology and morphology, which necessitates generating a model capable of distinguishing the two media. We constructed an object-based model using the OM and iOM composition of shale samples. In the model, we integrated information such as OM population and size distribution, as well as its associated pore-size distribution. For the iOM part, we used mineralogy and pore-size information derived from X-ray diffraction, scanning electron microscopy, and nitrogen sorption measurements. Our proposed model results in millimeter-scale 2D realizations of shale samples by honoring OM and mineral types, their compositions, shapes, and size distributions. The model can capture heterogeneities smaller than 1mm. We studied the effects of different gas flow processes and found that Knudsen diffusion and gas slippage dominate the flow, but surface diffusion has little impact on total gas flow.
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