Pore-scale and continuum simulations of solute transport micromodel benchmark experiments
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Energy and Environment Division
- Univ. of Texas, Austin, TX (United States). Dept. of Petroleum and Geosystems Engineering
- Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Civil and Environmental Engineering
- Univ. of Strathclyde, Glasgow (United Kingdom). Dept. of Mechanical Engineering
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Geomechanics Dept.
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Earth and Environmental Sciences Division
- Shell Global Solutions, Rijswijk (Netherlands)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab.
Four sets of nonreactive solute transport experiments were conducted with micromodels. Three experiments with one variable, i.e., flow velocity, grain diameter, pore-aspect ratio, and flow-focusing heterogeneity were in each set. The data sets were offered to pore-scale modeling groups to test their numerical simulators. Each set consisted of two learning experiments, for which our results were made available, and one challenge experiment, for which only the experimental description and base input parameters were provided. The experimental results showed a nonlinear dependence of the transverse dispersion coefficient on the Peclet number, a negligible effect of the pore-aspect ratio on transverse mixing, and considerably enhanced mixing due to flow focusing. Five pore-scale models and one continuum-scale model were used to simulate the experiments. Of the pore-scale models, two used a pore-network (PN) method, two others are based on a lattice Boltzmann (LB) approach, and one used a computational fluid dynamics (CFD) technique. Furthermore, we used the learning experiments, by the PN models, to modify the standard perfect mixing approach in pore bodies into approaches to simulate the observed incomplete mixing. The LB and CFD models used the learning experiments to appropriately discretize the spatial grid representations. For the continuum modeling, the required dispersivity input values were estimated based on published nonlinear relations between transverse dispersion coefficients and Peclet number. Comparisons between experimental and numerical results for the four challenge experiments show that all pore-scale models were all able to satisfactorily simulate the experiments. The continuum model underestimated the required dispersivity values, resulting in reduced dispersion. The PN models were able to complete the simulations in a few minutes, whereas the direct models, which account for the micromodel geometry and underlying flow and transport physics, needed up to several days on supercomputers to resolve the more complex problems.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC04-94AL85000; AC05-76RL01830; SC0001114; SC0006771
- OSTI ID:
- 1338387
- Alternate ID(s):
- OSTI ID: 1168036
OSTI ID: 1384130
OSTI ID: 1290391
OSTI ID: 1475352
- Report Number(s):
- SAND2016-12548J; 649869
- Journal Information:
- Computational Geosciences, Journal Name: Computational Geosciences Journal Issue: 4 Vol. 20; ISSN 1420-0597
- Publisher:
- SpringerCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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