The DOI matches its Crossref record; 133 of the 133 references it cites were found in a registry or an index.
Modeling of multi-scale transport phenomena in shale gas production — A critical review
Abstract
Abstract Shale gas, although unconventional, is a prospective clean energy source. Shale gas production is a complex multi-scale process with its spatial size ranging from the nanoscale to kilometer-scale. During shale production, the gas transport process involves the diffusion of dissolved gas molecules into the matrix bulk, desorption of adsorbed gas from the micropore surface, Knudsen diffusion and slip flow of free gas in the pore, and Darcy flow or even high-speed non-Darcy flow of free gas in the fracture network. Accordingly, understanding the shale gas transport process in the shale reservoirs poses a long-standing problem to researchers and engineers. Computational modeling offers an opportunity to effectively reveal the gas multi-scale transport mechanisms and accurately predict the amount of shale production. In this review, the shale gas transport process during shale gas production is firstly introduced. Thereafter, the multi-scale transport phenomena involving shale gas molecule desorption from the shale matrix at the atomic and molecular level, diffusion in the nanopore, diffusion and seepage into the micropore, and convection and mass flow in the mesoscopic pores and macropore are elucidated. Moreover, the corresponding multi-scale simulation models that describe the above phenomena and shale production are explained. The shale gas production genome model, which provides insights into the entire process of the shale gas production model, is proposed and clarified according to the multi-scale simulation models used in the shale gas production prediction. The shale gas production genome model is convenient for elucidating shale transport mechanisms and guiding shale gas reservoir exploitation.
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Cites
VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data
Momma, K., & Izumi, F. (2011) · Journal of Applied Crystallography · doi:10.1107/s0021889811038970 · Cited by 26,054
The adsorption of gases on plane surfaces of glass, mica and platinum
Langmuir, I. (1918) · Journal of the American Chemical Society · doi:10.1021/ja02242a004 · Cited by 23,242
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Jain, A., Ong, S. P., Hautier, G., Chen, W., Richards, W. D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., et al. (2013) · APL Materials · doi:10.1063/1.4812323 · Cited by 13,094
Dynamics of Fluids in Porous Media
Bear, J. (1975) · Soil Science · doi:10.1097/00010694-197508000-00022 · Cited by 9,778
LATTICE BOLTZMANN METHOD FOR FLUID FLOWS
Chen, S., & Doolen, G. D. (1998) · Annual Review of Fluid Mechanics · doi:10.1146/annurev.fluid.30.1.329 · Cited by 7,314
VESTA: a three-dimensional visualization system for electronic and structural analysis
Momma, K., & Izumi, F. (2008) · Journal of Applied Crystallography · doi:10.1107/s0021889808012016 · Cited by 6,834
Dynamics of fluids in Porous Media
Childs, E. C. (1973) · Engineering Geology · doi:10.1016/0013-7952(73)90047-1 · Cited by 6,192
Understanding Molecular Simulation: From Algorithms to Applications
Frenkel, D., Smit, B., & Ratner, M. A. (1997) · Physics Today · doi:10.1063/1.881812 · Cited by 5,059
Wales, D. J., & Doye, J. P. K. (1997) · The Journal of Physical Chemistry A · doi:10.1021/jp970984n · Cited by 3,020
Ross, D. J. K., & Marc Bustin, R. (2009) · Marine and Petroleum Geology · doi:10.1016/j.marpetgeo.2008.06.004 · Cited by 2,217
Metadata
- Authors
- Wang, H., Chen, L., Qu, Z., Yin, Y., Kang, Q., Yu, B., & Tao, W.-Q.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 262
- Pages
- 114575
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W3005964829
- Cited by
- 293
- References
- 133
- FWCI
- 21.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, H., Chen, L., Qu, Z., Yin, Y., Kang, Q., Yu, B., & Tao, W.-Q. (2020). Modeling of multi-scale transport phenomena in shale gas production — A critical review. Applied Energy. https://doi.org/10.1016/j.apenergy.2020.114575
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