Upscaled Lattice Boltzmann Method for Simulations of Flows in Heterogeneous Porous Media

Li, Jun; Brown, Donald

Upscaled Lattice Boltzmann Method for Simulations of Flows in Heterogeneous Porous Media

Files

1740693.pdf (4.77 MB)

License

http://creativecommons.org/licenses/by/4.0/

Type

Article

Authors

Li, Jun
Brown, Donald

KAUST Department

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Numerical Porous Media SRI Center (NumPor)

Online Publication Date

2017-02-16

Print Publication Date

2017

Date

2017-02-16

Abstract

An upscaled Lattice Boltzmann Method (LBM) for flow simulations in heterogeneous porous media at the Darcy scale is proposed in this paper. In the Darcy-scale simulations, the Shan-Chen force model is used to simplify the algorithm. The proposed upscaled LBM uses coarser grids to represent the average effects of the fine-grid simulations. In the upscaled LBM, each coarse grid represents a subdomain of the fine-grid discretization and the effective permeability with the reduced-order models is proposed as we coarsen the grid. The effective permeability is computed using solutions of local problems (e.g., by performing local LBM simulations on the fine grids using the original permeability distribution) and used on the coarse grids in the upscaled simulations. The upscaled LBM that can reduce the computational cost of existing LBM and transfer the information between different scales is implemented. The results of coarse-grid, reduced-order, simulations agree very well with averaged results obtained using a fine grid.

Citation

Li J, Brown D (2017) Upscaled Lattice Boltzmann Method for Simulations of Flows in Heterogeneous Porous Media. Geofluids 2017: 1–12. Available: http://dx.doi.org/10.1155/2017/1740693.

Acknowledgements

The authors would like to acknowledge Victor Calo for his helpful discussion on the physical implications of the models. Also, they would like to thank Oleg Iliev for his helpful insights on the upscaling of porous media and validation of the computational results.