1887

Abstract

Summary

Direct numerical simulation of two-phase flow at the pore scale is computationally challenging due to high requirements on physical fidelity and because of the spatial resolution necessary to accurately represent pore geometries. In this paper, we explore how GPGPU-accelerated iterative linear solvers can help to make these simulations feasible in workflows such as relative permeability estimation. Our target application is a Cahn-Hilliard-Navier-Stokes solver that uses a discontinuous Galerkin discretization in space and an implicit discretization in time. The performance bottleneck of the application is the solution of sparse linear systems in each time step. We evaluate and compare the performance of a CPU-based iterative solver from the Trilinos package and its GPGPU-accelerated counterpart from the AMGX package. In simulations with realistic porous rock geometries, we demonstrate that the weak scalability of the two solvers are comparable. At the same time, the GPGPU-accelerated solvers are approximately forty times faster on our multi-GPGPU compute nodes, resulting in more than a four-fold speedup of the overall simulation. Our results show that GPGPUs can improve parallel efficiency in pore-scale flow simulations, and they can help to make larger simulations feasible.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201903285
2019-10-07
2024-04-24
Loading full text...

Full text loading...

References

  1. Alpak, F.O., Gray, F., Saxena, N., Dietderich, J., Hofmann, R. and Berg, S.
    [2018a] A distributed parallel multiple-relaxation-time lattice Boltzmann method on general-purpose graphics processing units for the rapid and scalable computation of absolute permeability from high-resolution 3D micro-CT images. Computational Geosciences, 22(3), 815–832.
    [Google Scholar]
  2. Alpak, F.O., Samardžic, A. and Frank, F.
    [2018b] A distributed parallel direct simulator for pore-scale two-phase flow on digital rock images using a finite difference implementation of the phase-field method. Journal of Petroleum Science and Engineering, 166, 806–824.
    [Google Scholar]
  3. Armstrong, R.T., Berg, S., Dinariev, O., Evseev, N., Klemin, D., Koroteev, D. and Safonov, S.
    [2016] Modeling of Pore-Scale Two-Phase Phenomena Using Density Functional Hydrodynamics. Transport in Porous Media, 112(3), 577–607.
    [Google Scholar]
  4. Esler, K., Mukundakrishnan, K., Natoli, V., Shumway, J., Zhang, Y. and Gilman, J.
    [2014] Realizing the potential of GPUs for reservoir simulation. In: ECMOR XIV-14th European conference on the mathematics ofoil recovery.
    [Google Scholar]
  5. Frank, F., Liu, C., Alpak, F.O., Berg, S. and Riviere, B.
    [2018a] Direct numerical simulation of flow on pore-scale images using the phase-field method. SPE Journal.
    [Google Scholar]
  6. Frank, F., Liu, C., Alpak, F.O. and Riviere, B.
    [2018b] A finite volume / discontinuous Galerkin method for the advective Cahn-Hilliard equation with degenerate mobility on porous domains stemming from micro-CT imaging. Computational Geosciences, 22(2), 543–563.
    [Google Scholar]
  7. Heroux, M.A., Bartlett, R.A., Howle, V.E., Hoekstra, R.J., Hu, J.J., Kolda, T.G., Lehoucq, R.B., Long, K.R., Pawlowski, R.P., Phipps, E.T., Salinger, A.G., Thornquist, H.K., Tuminaro, R.S., Willenbring, J.M., Williams, A. and Stanley, K.S.
    [2005] An Overview of the Trilinos Project. ACM Trans. Math. Softw., 31(3), 397–123.
    [Google Scholar]
  8. Karypis, G. and Kumar, V.
    [1998] A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs. SIAM Journal on Scientific Computing, 20(1), 359–392.
    [Google Scholar]
  9. Naumov, M., Arsaev, M., Castonguay, P., Cohen, J., Demouth, J., Eaton, J., Layton, S., Markovskiy, N., Reguly, I., Sakharnykh, N., Sellappan, V. and Strzodka, R.
    [2015] AmgX: A Library for GPU Accelerated Algebraic Multigrid and Preconditioned Iterative Methods. SIAM Journal on Scientific Computing, 37(5), S602–S626.
    [Google Scholar]
  10. Thiele, C., Araya-Polo, M., Alpak, F. and Riviere, B.
    [2019] Distributed Parallel Hybrid CPU-GPGPU Implementation of the Phase-Field Method for Accelerated High-Accuracy Simulations of Pore-Scale Two-Phase Flow. In: SPE Reservoir Simulation Conference.Society of Petroleum Engineers.
    [Google Scholar]
  11. Thiele, C., Araya-Polo, M., Alpak, F.O., Riviere, B. and Frank, F.
    [2017] Inexact hierarchical scale separation: A two-scale approach for linear systems from discontinuous Galerkin discretizations. Computers & Mathematics with Applications, 74(8), 1769–1778.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201903285
Loading
/content/papers/10.3997/2214-4609.201903285
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error