Abstract

In this paper, we introduce a relaxed physical factorization (RPF) preconditioner for the efficient iterative solution of the linearized algebraic system arising from the mixed finite element discretization of coupled poromechanics equations. The preconditioner is obtained by using a proper factorization of the $3\times3$ block matrix and setting a relaxation parameter $\alpha$. The preconditioner is inspired by the relaxed dimensional factorization introduced by Benzi et al. [J. Comput. Phys., 230 (2011), pp. 6185--6202; Comput. Methods Appl. Mech. Engrg., 300 (2016), pp. 129--145]. A stable algorithm is advanced to compute the optimal value of $\alpha$, along with a lower bound to control the possible ill-conditioning of the $\alpha$ dependent inner blocks. Numerical experiments in both theoretical benchmarks and real-world applications are presented and discussed to investigate the RPF properties, performance, and robustness.

Keywords

  1. preconditioning
  2. Krylov subspace methods
  3. mixed finite elements
  4. poromechanics

MSC codes

  1. 65F10
  2. 65F08
  3. 65N30

Get full access to this article

View all available purchase options and get full access to this article.

References

1.
J. H. Adler, F. J. Gaspar, X. Hu, C. Rodrigo, and L. T. Zikatanov, Robust block preconditioners for Biot's model, in Domain Decomposition Methods in Science and Engineering XXIV, P. E. Bjøstad, S. C. Brenner, L. Halpern, H. H. Kim, R. Kornhuber, T. Rahman, and O. B. Widlund, eds., Lect. Notes Comput. Sci. Eng. 125, Springer, New York, 2018, pp. 3--16, https://doi.org/10.1007/978-3-319-93873-8.
2.
T. Almani, K. Kumar, A. Dogru, G. Singh, and M. F. Wheeler, Convergence analysis of multirate fixed-stress split interative schemes for coupling flow with geomechanics, Comput. Methods Appl. Mech. Engrg., 311 (2016), pp. 180--207, https://doi.org/10.1016/j.cma.2016.07.036.
3.
O. Axelsson, R. Blaheta, and P. Byczanski, Stable discretization of poroelasticity problems and efficient preconditioners for arising saddle point type matrices, Comput. Vis. Sci., 15 (2012), pp. 191--207, https://doi.org/10.1007/s00791-013-0209-0.
4.
M. Bause, F. A. Radu, and U. Köcher, Space–time finite element approximation of the Biot poroelasticity system with iterative coupling, Comput. Methods Appl. Mech. Engrg., 320 (2017), pp. 745--768, https://doi.org/10.1016/j.cma.2017.03.017.
5.
M. Benzi, S. Deparis, G. Grandperrin, and A. Quarteroni, Parameter estimates for the Relaxed Dimensional Factorization preconditioner and application to hemodynamics, Comput. Methods Appl. Mech. Engrg., 300 (2016), pp. 129--145, https://doi.org/10.1016/j.cma.2015.11.016.
6.
M. Benzi, M. Ng, Q. Niu, and Z. Wang, A Relaxed Dimensional Factorization preconditioner for the incompressible Navier-Stokes equations, J. Comput. Phys., 230 (2011), pp. 6185--6202, https://doi.org/10.1016/j.jcp.2011.04.001.
7.
L. Bergamaschi, M. Ferronato, and G. Gambolati, Novel preconditioners for the iterative solution to FE-discretized coupled consolidation equations, Comput. Methods Appl. Mech. Engrg., 196 (2007), pp. 2647--2656, https://doi.org/10.1016/j.cma.2007.01.013.
8.
L. Bergamaschi, S. Mantica, and G. Manzini, A mixed finite element-finite volume formulation of the black oil model, SIAM J. Sci. Comput., 20 (1998), pp. 970--997, https://doi.org/10.1137/S1064827595289303.
9.
L. Bergamaschi and Á. Martínez, RMCP: Relaxed Mixed Constraint Preconditioners for saddle point linear systems arising in geomechanics, Comput. Methods Appl. Mech. Engrg., 221--222 (2012), pp. 54--62, https://doi.org/10.1016/j.cma.2012.02.004.
10.
M. A. Biot, General theory of three-dimensional consolidation, J. Appl. Phys., 12 (1941), pp. 155--164, https://doi.org/10.1063/1.1712886.
11.
M. Borregales, F. A. Radu, K. Kumar, and J. M. Nordbotten, Robust iterative schemes for non-linear poromechanics, Comput. Geosci., 22 (2018), pp. 1021--1038, https://doi.org/10.1007/s10596-018-9736-6.
12.
J. W. Both, M. Borregales, J. M. Nordbotten, K. Kumar, and F. A. Radu, Robust fixed stress splitting for Biot's equations in heterogeneous media, Appl. Math. Lett., 68 (2017), pp. 101--108, https://doi.org/10.1016/j.aml.2016.12.019.
13.
J. W. Both, K. Kumar, J. M. Nordbotten, and F. A. Radu, Anderson accelerated fixed-stress splitting schemes for consolidation of unsaturated porous media, Comput. Math. Appl., 77 (2019), pp. 1479--1502, https://doi.org/10.1016/j.camwa.2018.07.033.
14.
N. Castelletto, M. Ferronato, and G. Gambolati, Thermo-hydro-mechanical modeling of fluid geological storage by Godunov-mixed methods, Internat. J. Numer. Meth. Engrg., 90 (2012), pp. 988--1009, https://doi.org/10.1002/nme.3352.
15.
N. Castelletto, G. Gambolati, and P. Teatini, A coupled MFE poromechanical model of a large-scale load experiment at the coastland of Venice, Comput. Geosci., 19 (2015), pp. 17--29, https://doi.org/10.1007/s10596-014-9450-y.
16.
N. Castelletto, J. A. White, and M. Ferronato, Scalable algorithms for three-field mixed finite element coupled poromechanics, J. Comput. Phys., 327 (2016), pp. 894--918, https://doi.org/10.1016/j.jcp.2016.09.063.
17.
X. Chen, K. K. Phoon, and K. C. Toh, Partitioned versus global Krylov subspace iterative methods for FE solution of 3-D Biot's problem, Comput. Methods Appl. Mech. Engrg., 196 (2007), pp. 2737--2750, https://doi.org/10.1016/j.cma.2007.02.003.
18.
Z. Chen, G. Huan, and Y. Ma, Computational Methods for Multiphase Flows in Porous, Comput. Sci. Eng. 2, SIAM, Philadelphia, 2006.
19.
M. A. Christie and M. J. Blunt, Tenth SPE comparative solution project: A comparison of upscaling techniques, SPE Reserv. Eval. Eng., 4 (2001), pp. 308--317, https://doi.org/10.2118/72469-PA.
20.
S. Dana, B. Ganis, and M. F. Wheeler, A multiscale fixed stress split iterative scheme for coupled flow and poromechanics in deep subsurface reservoirs, J. Comput. Phys., 352 (2018), pp. 1--22, https://doi.org/10.1016/j.jcp.2017.09.049.
21.
S. Dana and M. F. Wheeler, Convergence analysis of two-grid fixed stress split iterative scheme for coupled flow and deformation in heterogeneous poroelastic media, Comput. Methods Appl. Mech. Engrg., 341 (2018), pp. 788--806, https://doi.org/10.1016/j.cma.2018.07.018.
22.
M. Ferronato, N. Castelletto, and G. Gambolati, A fully coupled 3-D mixed finite element model of Biot consolidation, J. Comput. Phys., 229 (2010), pp. 4813--4830, https://doi.org/10.1016/j.jcp.2010.03.018.
23.
M. Ferronato, L. Gazzola, N. Castelletto, P. Teatini, and L. Zhu, A coupled Mixed Finite Element Biot model for land subsidence prediction in the Beijing area, in Poromechanics VI, M. Vandamme, P. Dangla, J.-M. Pereira, and S. Ghabezloo, eds., American Society of Civil Engineers, 2017, pp. 182--189, https://doi.org/10.1061/9780784480779.022.
24.
M. Ferronato, G. Pini, and G. Gambolati, The role of preconditioning in the solution to FE coupled consolidation equations by Krylov subspace methods, Int. J. Numer. Anal. Methods Geomech., 33 (2009), pp. 405--423, https://doi.org/10.1002/nag.729.
25.
A. J. H. Frijns, A Four-Component Mixture Theory Applied to Cartilaginous Tissues: Numerical Modelling and Experiments, Ph.D. thesis, Technische Universiteit Eindhoven, The Netherlands, 2000.
26.
F. J. Gaspar, F. J. Lisbona, C. W. Oosterlee, and R. Wienands, A systematic comparison of coupled and distributive smoothing in multigrid for the poroelasticity system, Numer. Linear Algebra Appl., 11 (2004), pp. 93--113, https://doi.org/10.1002/nla.372.
27.
F. J. Gaspar and C. Rodrigo, On the fixed-stress split scheme as smoother in multigrid methods for coupling flow and geomechanics, Comput. Methods Appl. Mech. Engrg., 326 (2017), pp. 526--540, https://doi.org/10.1016/j.cma.2017.08.025.
28.
V. Girault, K. Kumar, and M. F. Wheeler, Convergence of iterative coupling of geomechanics with flow in a fractured poroelastic medium, Comput. Geosci., 20 (2016), pp. 997--1011, https://doi.org/10.1007/s10596-016-9573-4.
29.
J. B. Haga, H. Osnes, and H. P. Langtangen, A parallel block preconditioner for large-scale poroelasticity with highly heterogeneous material parameters, Comput. Geosci., 16 (2012), pp. 723--734, https://doi.org/10.1007/s10596-012-9284-4.
30.
J. B. Haga, H. Osnes, and H. P. Langtangen, On the causes of pressure oscillations in low-permeable and low-compressible porous media, Int. J. Numer. Anal. Methods Geomech., 36 (2012), pp. 1507--1522, https://doi.org/10.1002/nag.1062.
31.
Q. Hong and J. Kraus, Parameter-robust stability of classical three-field formulation of Biot's consolidation model, Electron. Trans. Numer. Anal., 48 (2018), pp. 202--226, https://doi.org/10.1553/etna_vol48s202.
32.
Q. Hong, J. Kraus, M. Lymbery, and M. F. Wheeler, Parameter-Robust Convergence Analysis of Fixed-Stress Split Iterative Method for Multiple-Permeability Poroelasticity Systems, arXiv:1812.11809, 2018.
33.
R. A. Horn and C. R. Johnson, Matrix Analysis, 2nd ed., Cambridge University Press, New York, 2013.
34.
X. Hu, C. Rodrigo, F. J. Gaspar, and L. T. Zikatanov, A nonconforming finite element method for the Biot's consolidation model in poroelasticity, J. Comput. Appl. Math., 310 (2017), pp. 143--154, https://doi.org/10.1016/j.cam.2016.06.003.
35.
B. Jha and R. Juanes, A locally conservative finite element framework for the simulation of coupled flow and reservoir geomechanics, Acta Geotech., 2 (2007), pp. 139--153, https://doi.org/10.1007/s11440-007-0033-0.
36.
B. Jha and R. Juanes, Coupled multiphase flow and poromechanics: A computational model of pore pressure effects on fault slip and earthquake triggering, Water Resources Res., 5 (2014), pp. 3776--3808, https://doi.org/10.1002/2013WR015175.
37.
J. Kim, H. A. Tchelepi, and R. Juanes, Stability, accuracy and efficiency of sequential methods for coupled flow and geomechanics, SPE J., 16 (2011), pp. 249--262, https://doi.org/10.2118/119084-PA.
38.
J. Kim, H. A. Tchelepi, and R. Juanes, Stability and convergence of sequential methods for coupled flow and geomechanics: Fixed-stress and fixed-strain splits, Comput. Methods Appl. Mech. Engrg., 200 (2011), pp. 1591--1606, https://doi.org/10.1016/j.cma.2010.12.022.
39.
Y. Kuznetsov, K. Lipnikov, S. Lyons, and S. Maliassov, Mathematical modeling and numerical algorithms for poroelastic problems, in Current Trends in Scientific Computing, Z. Chen, R. Glowinski, and K. Li, eds., Contemp. Math. 329, AMS, Providence, RI, 2003, pp. 191--202, https://dx.doi.org/10.1090/conm/329.
40.
J. J. Lee, K.-A. Mardal, and R. Winther, Parameter-robust discretization and preconditioning of Biot's consolidation model, SIAM J. Sci. Comput., 39 (2017), pp. A1--A24, https://doi.org/10.1137/15M1029473.
41.
C.-J. Lin and J. J. Moré, Incomplete Cholesky factorizations with limited memory, SIAM J. Sci. Comput., 21 (1999), pp. 24--45, https://doi.org/10.1137/S1064827597327334.
42.
K. Lipnikov, Numerical Methods for the Biot Model in Poroelasticity, Ph.D. thesis, University of Houston, 2002.
43.
P. Luo, C. Rodrigo, F. J. Gaspar, and C. W. Oosterlee, Multigrid method for nonlinear poroelasticity equations, Comput. Visual Sci., 17 (2015), pp. 255--265, https://doi.org/10.1007/s00791-016-0260-8.
44.
P. Luo, C. Rodrigo, F. J. Gaspar, and C. W. Oosterlee, On an Uzawa smoother in multigrid for poroelasticity equations, Numer. Linear Algebra Appl., 24 (2017), e2074, https://doi.org/10.1002/nla.2074.
45.
J. Mandel, Consolidation des sols (Étude mathématique), Geotechnique, 3 (1953), pp. 287--299, https://doi.org/10.1680/geot.1953.3.7.287.
46.
A. Mikelič and M. F. Wheeler, Convergence of iterative coupling for coupled flow and geomechanics, Comput. Geosci., 17 (2013), pp. 455--461, https://doi.org/10.1007/s10596-012-9318-y.
47.
D. W. Peaceman, Interpretation of well-block pressures in numerical reservoir simulation, SPE J., 18 (1978), pp. 183--194, https://doi.org/10.2118/6893-PA.
48.
P. J. Phillips and M. F. Wheeler, A coupling of mixed and continuous Galerkin finite element methods for poroelasticity I: The continuous in time case, Comput. Geosci., 11 (2007), pp. 131--144, https://doi.org/10.1007/s10596-007-9045-y.
49.
P. J. Phillips and M. F. Wheeler, A coupling of mixed and continuous Galerkin finite element methods for poroelasticity II: The discrete-in-time case, Comput. Geosci., 11 (2007), pp. 145--158, https://doi.org/10.1007/s10596-007-9044-z.
50.
K. K. Phoon, K. C. Toh, S. H. Chan, and F. H. Lee, An efficient diagonal preconditioner for finite element solution of Biot's consolidation equations, Internat. J. Numer. Methods Engrg., 55 (2002), pp. 377--400, https://doi.org/10.1002/nme.500.
51.
C. Rodrigo, X. Hu, P. Ohm, J. H. Adler, F. J. Gaspar, and L. T. Zikatanov, New stabilized discretizations for poroelasticity and the Stokes' equations, Comput. Methods Appl. Mech. Engrg., 341 (2018), pp. 467--484, https://doi.org/10.1016/j.cma.2018.07.003.
52.
E. Turan and P. Arbenz, Large scale micro finite element analysis of 3D bone poroelasticity, Parallel Comput., 40 (2014), pp. 239--250, https://doi.org/10.1016/j.parco.2013.09.002.
53.
H. A. Van der Vorst, Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems, SIAM J. Sci. Stat. Comput., 13 (1992), pp. 631--644, https://doi.org/10.1137/0913035.
54.
J. A. White and R. I. Borja, Block-preconditioned Newton--Krylov solvers for fully coupled flow and geomechanics, Comput. Geosci., 15 (2011), pp. 647--659, https://doi.org/10.1007/s10596-011-9233-7.
55.
J. A. White, N. Castelletto, and H. A. Tchelepi, Block-partitioned solvers for coupled poromechanics: A unified framework, Comput. Methods Appl. Mech. Engrg., 303 (2016), pp. 55--74, https://doi.org/10.1016/j.cma.2016.01.008.
56.
L. Zhu, Z. Dai, H. Gong, C. Gable, and P. Teatini, Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans, Stoch. Environ. Res. Risk Assessment, 30 (2016), pp. 1005--1016, https://doi.org/10.1007/s00477-015-1089-2.

Information & Authors

Information

Published In

cover image SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Pages: B694 - B720
ISSN (online): 1095-7197

History

Submitted: 9 August 2018
Accepted: 7 May 2019
Published online: 11 July 2019

Keywords

  1. preconditioning
  2. Krylov subspace methods
  3. mixed finite elements
  4. poromechanics

MSC codes

  1. 65F10
  2. 65F08
  3. 65N30

Authors

Affiliations

Funding Information

Lawrence Livermore National Laboratory https://doi.org/10.13039/100006227 : DE-AC52-07NA27344
Università degli Studi di Padova https://doi.org/10.13039/501100003500

Metrics & Citations

Metrics

Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited By

View Options

View options

PDF

View PDF

Figures

Tables

Media

Share

Share

Copy the content Link

Share with email

Email a colleague

Share on social media