Skip to main content
Log in

Finite Element Solvers for Biot’s Poroelasticity Equations in Porous Media

  • Special Issue
  • Published:
Mathematical Geosciences Aims and scope Submit manuscript

A Correction to this article was published on 26 April 2021

This article has been updated

Abstract

We study and compare five different combinations of finite element spaces for approximating the coupled flow and solid deformation system, so-called Biot’s equations. The permeability and porosity fields are heterogeneous and depend on solid displacement and fluid pressure. We provide detailed comparisons among the continuous Galerkin, discontinuous Galerkin, enriched Galerkin, and two types of mixed finite element methods. Several advantages and disadvantages for each of the above techniques are investigated by comparing local mass conservation properties, the accuracy of the flux approximation, number of degrees of freedom (DOF), and wall and CPU times. Three-field formulation methods with fluid velocity as an additional primary variable generally require a larger number of DOF, longer wall and CPU times, and a greater number of iterations in the linear solver in order to converge. The two-field formulation, a combination of continuous and enriched Galerkin function space, requires the fewest DOF among the methods that conserve local mass. Moreover, our results illustrate that three out of the five methods conserve local mass and produce similar flux approximations when conductivity alteration is included. These comparisons of the key performance indicators of different combinations of finite element methods can be utilized to choose the preferred method based on the required accuracy and the available computational resources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Change history

References

  • Abou-Kassem J, Islam M, Farouq-Ali S (2013) Petroleum reservoir simulations. Elsevier, London

    Google Scholar 

  • Adler J, Gaspar F, Hu X, Ohm P, Rodrigo C, Zikatanov L (2019) Robust preconditioners for a new stabilized discretization of the poroelastic equations. Preprint arXiv:1905.10353

  • Almani T, Kumar K, Dogru A, Singh G, Wheeler M (2016) Convergence analysis of multirate fixed-stress split iterative schemes for coupling flow with geomechanics. Comput Methods Appl Mech Eng 311:180–207

    Google Scholar 

  • Alnaes M, Blechta J, Hake J, Johansson A, Kehlet B, Logg A, Richardson C, Ring J, Rognes M, Wells G (2015) The FEniCS project version 1.5. Arch Numer Softw 3(100):12

    Google Scholar 

  • Arnold D, Brezzi F, Fortin M (1984) A stable finite element for the Stokes equations. Calcolo 21(4):337–344

    Google Scholar 

  • Ayuso B, Georgiev I, Kraus J, Zikatanov L (2009) Preconditioning techniques for discontinuous Galerkin methods discretizations for linear elasticity equations

  • Balay S, Abhyankar S, Adams M, Brown J, Brune P, Buschelman K, Dalcin L, Dener A, Eijkhout V, Gropp W, Kaushik D, Knepley M, May D, McInnes L, Mills R, Munson T, Rupp K, Sanan P, Smith B, Zampini S, Zhang H, Zhang H (2018) PETSc users manual. Technical report ANL-95/11—revision 3.10, Argonne National Laboratory

  • Ballarin F, Rozza G (2019) Multiphenics-easy prototyping of multiphysics problems in FEniCS. Version: 0.2.0. https://gitlab.com/multiphenics/multiphenics

  • Bazilevs Y, Hughes T (2007) Weak imposition of Dirichlet boundary conditions in fluid mechanics. Comput Fluids 36(1):12–26

    Google Scholar 

  • Biot M (1941) General theory of three-dimensional consolidation. J Appl Phys 12(2):155–164

    Google Scholar 

  • Biot M, Willis D (1957) The elastic coefficients of the theory of consolidation. J Appl Mech 15:594–601

    Google Scholar 

  • Bisdom K, Bertotti G, Nick H (2016) A geometrically based method for predicting stress-induced fracture aperture and flow in discrete fracture networks. AAPG Bull 100(7):1075–1097

    Google Scholar 

  • Bouklas N, Landis C, Huang R (2015a) Effect of solvent diffusion on crack-tip fields and driving force for fracture of hydrogels. J Appl Mech 82(8):081007

    Google Scholar 

  • Bouklas N, Landis C, Huang R (2015b) A nonlinear, transient finite element method for coupled solvent diffusion and large deformation of hydrogels. J Mech Phys Solids 79:21–43

    Google Scholar 

  • Cao T, Sanavia L, Schrefler B (2016) A thermo-hydro-mechanical model for multiphase geomaterials in dynamics with application to strain localization simulation. Int J Numer Methods Eng 107(4):312–337

    Google Scholar 

  • Castelletto N, White J, Tchelepi H (2015) Accuracy and convergence properties of the fixed-stress iterative solution of two-way coupled poromechanics. Int J Numer Anal Methods Geomech 39(14):1593–1618

    Google Scholar 

  • Castelletto N, White J, Ferronato M (2016) Scalable algorithms for three-field mixed finite element coupled poromechanics. J Comput Phys 327:894–918

    Google Scholar 

  • Chen Z (2007) Reservoir simulation: mathematical techniques in oil recovery, vol 77. SIAM, New York

    Google Scholar 

  • Choo J (2018) Large deformation poromechanics with local mass conservation: an enriched Galerkin finite element framework. Int J Numer Methods Eng 116(1):66–90

    Google Scholar 

  • Choo J (2019) Stabilized mixed continuous/enriched Galerkin formulations for locally mass conservative poromechanics. Comput Methods Appl Mech Eng 357:112568

    Google Scholar 

  • Choo J, Borja R (2015) Stabilized mixed finite elements for deformable porous media with double porosity. Comput Methods Appl Mech Eng 293:131–154

    Google Scholar 

  • Choo J, Lee S (2018) Enriched Galerkin finite elements for coupled poromechanics with local mass conservation. Comput Methods Appl Mech Eng 341:311–332

    Google Scholar 

  • Coussy O (2004) Poromechanics. Wiley, New York

    Google Scholar 

  • Deng Q, Ginting V, McCaskill B, Torsu P (2017) A locally conservative stabilized continuous Galerkin finite element method for two-phase flow in poroelastic subsurfaces. J Comput Phys 347:78–98

    Google Scholar 

  • Du J, Wong R (2007) Application of strain-induced permeability model in a coupled geomechanics–reservoir simulator. J Can Pet Technol 46(12):55–61

    Google Scholar 

  • Ern A, Stephansen A (2008) A posteriori energy-norm error estimates for advection–diffusion equations approximated by weighted interior penalty methods. J Comput Math 2008:488–510

    Google Scholar 

  • Ern A, Stephansen A, Zunino P (2009) A discontinuous Galerkin method with weighted averages for advection–diffusion equations with locally small and anisotropic diffusivity. IMA J Numer Anal 29(2):235–256

    Google Scholar 

  • Ferronato M, Castelletto N, Gambolati G (2010) A fully coupled 3-D mixed finite element model of biot consolidation. J Comput Phys 229(12):4813–4830

    Google Scholar 

  • Ferronato M, Franceschini A, Janna C, Castelletto N, Tchelepi H (2019) A general preconditioning framework for coupled multiphysics problems with application to contact-and poro-mechanics. J Comput Phys 398:108887

    Google Scholar 

  • Frigo M, Castelletto N, Ferronato M (2019) A relaxed physical factorization preconditioner for mixed finite element coupled poromechanics. SIAM J Sci Comput 41(4):B694–B720

    Google Scholar 

  • Girault V, Wheeler M, Almani T, Dana S (2019) A priori error estimates for a discretized poro-elastic–elastic system solved by a fixed-stress algorithm. Oil Gas Sci Technol Rev IFP Energ Nouvelles 74:24

    Google Scholar 

  • Haga J, Osnes H, Langtangen H (2012) On the causes of pressure oscillations in low permeable and low compressible porous media. Int J Numer Anal Methods Geomech 36(12):1507–1522

    Google Scholar 

  • Hansbo P (2005) Nitsche’s method for interface problems in computational mechanics. GAMM Mitteilungen 28(2):183–206

    Google Scholar 

  • Hong Q, Kraus J (2017) Parameter-robust stability of classical three-field formulation of biot’s consolidation model. Preprint arXiv:1706.00724

  • Honorio H, Maliska C, Ferronato M, Janna C (2018) A stabilized element-based finite volume method for poroelastic problems. J Comput Phys 364:49–72

    Google Scholar 

  • Jaeger J, Cook NG, Zimmerman R (2009) Fundamentals of rock mechanics. Wiley, Berlin

    Google Scholar 

  • Juanes R, Jha B, Hager B, Shaw J, Plesch A, Astiz L, Dieterich J, Frohlich C (2016) Were the May 2012 Emilia–Romagna earthquakes induced? A coupled flow-geomechanics modeling assessment. Geophys Res Lett 43(13):6891–6897

    Google Scholar 

  • Kadeethum T, Nick H, Lee S, Richardson C, Salimzadeh S, Ballarin F (2019a) A novel enriched Galerkin method for modelling coupled flow and mechanical deformation in heterogeneous porous media. In 53rd US rock mechanics/geomechanics symposium, New York, NY, USA. American Rock Mechanics Association

  • Kadeethum T, Salimzadeh S, Nick H (2019b) An investigation of hydromechanical effect on well productivity in fractured porous media using full factorial experimental design. J Petrol Sci Eng 181:106233

    Google Scholar 

  • Kadeethum T, Jørgensen T, Nick H (2020a) Physics-informed neural networks for solving inverse problems of nonlinear Biot’s equations: batch training. In 54th US rock mechanics/geomechanics symposium, Golden, CO, USA. American Rock Mechanics Association

  • Kadeethum T, Jørgensen T, Nick H (2020b) Physics-informed neural networks for solving nonlinear diffusivity and Biot’s equations. PLoS ONE 15(5):e0232683

    Google Scholar 

  • Kadeethum T, Nick H, Lee S, Ballarin F (2020c) Flow in porous media with low dimensional fractures by employing Enriched Galerkin method. Adv Water Resour 142:103620

    Google Scholar 

  • Kadeethum T, Salimzadeh S, Nick H (2020d) Well productivity evaluation in deformable single-fracture media. Geothermics 87:101839

    Google Scholar 

  • Kim J, Tchelepi H, Juanes R (2011) Stability and convergence of sequential methods for coupled flow and geomechanics: fixed-stress and fixed-strain splits. Comput Methods Appl Mech Eng 200(13–16):1591–1606

    Google Scholar 

  • Kumar S, Oyarzua R, Ruiz-Baier R, Sandilya R (2020) Conservative discontinuous finite volume and mixed schemes for a new four-field formulation in poroelasticity. ESAIM Math Model Numer Anal 54(1):273–299

    Google Scholar 

  • Lee S, Wheeler M (2017) Adaptive enriched Galerkin methods for miscible displacement problems with entropy residual stabilization. J Comput Phys 331:19–37

    Google Scholar 

  • Lee S, Wheeler M (2018) Enriched Galerkin methods for two-phase flow in porous media with capillary pressure. J Comput Phys 367:65–86

    Google Scholar 

  • Lee S, Woocheol C (2019) Optimal error estimate of elliptic problems with Dirac sources for discontinuous and enriched Galerkin methods. Appl Numer Math 150:76–104

    Google Scholar 

  • Lee S, Wheeler M, Wick T (2016) Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model. Comput Methods Appl Mech Eng 305:111–132

    Google Scholar 

  • Lee J, Mardal K, Winther R (2017) Parameter-robust discretization and preconditioning of Biot’s consolidation model. SIAM J Sci Comput 39(1):A1–A24

    Google Scholar 

  • Lewis R, Schrefler B (1998) The finite element method in the static and dynamic deformation and consolidation of porous media. Wiley, Berlin

    Google Scholar 

  • Liu R, Wheeler M, Dawson C, Dean R (2009) Modeling of convection-dominated thermoporomechanics problems using incomplete interior penalty Galerkin method. Comput Methods Appl Mech Eng 198(9–12):912–919

    Google Scholar 

  • Liu J, Tavener S, Wang Z (2018) Lowest-order weak Galerkin finite element method for Darcy flow on convex polygonal meshes. SIAM J Sci Comput 40(5):B1229–B1252

    Google Scholar 

  • Macminn C, Dufresne E, Wettlaufer J (2016) Large deformations of a soft porous material. Phys Rev Appl 5(4):1–30

    Google Scholar 

  • Murad M, Loula A (1994) On stability and convergence of finite element approximations of Biot’s consolidation problem. Int J Numer Methods Eng 37(4):645–667

    Google Scholar 

  • Murad M, Borges M, Obregon J, Correa M (2013) A new locally conservative numerical method for two-phase flow in heterogeneous poroelastic media. Comput Geotech 48:192–207

    Google Scholar 

  • Nick H, Raoof A, Centler F, Thullner M, Regnier P (2013) Reactive dispersive contaminant transport in coastal aquifers: numerical simulation of a reactive Henry problem. J Contam Hydrol 145:90–104

    Google Scholar 

  • Nitsche J (1971) Uber ein variationsprinzip zur losung von dirichlet-problemen bei verwendung von teilraumen, die keinen randbedingungen unterworfen sind. Abhandlungen aus dem mathematischen Seminar der Universität Hamburg 36(1):9–15

    Google Scholar 

  • Nordbotten J (2014) Cell-centered finite volume discretizations for deformable porous media. Int J Numer Methods Eng 100(6):399–418

    Google Scholar 

  • Pain C, Saunders J, Worthington M, Singer J, Stuart-Bruges W, Mason G, Goddard A (2005) A mixed finite-element method for solving the poroelastic Biot equations with electrokinetic coupling. Geophys J Int 160(2):592–608

    Google Scholar 

  • Peaceman D (2000) Fundamentals of numerical reservoir simulation, vol 6. Elsevier, Berlin

    Google Scholar 

  • Phillips P, Wheeler M (2007a) A coupling of mixed and continuous Galerkin finite element methods for poroelasticity I: the continuous in time case. Comput Geosci 11(2):131

    Google Scholar 

  • Phillips P, Wheeler M (2007b) A coupling of mixed and continuous Galerkin finite element methods for poroelasticity II: the discrete-in-time case. Comput Geosci 11(2):145–158

    Google Scholar 

  • Riviere B, Tan J, Thompson T (2017) Error analysis of primal discontinuous Galerkin methods for a mixed formulation of the Biot equations. Comput Math Appl 73(4):666–683

    Google Scholar 

  • Rodrigo C, Hu X, Ohm P, Adler J, Gaspar F, Zikatanov L (2018) New stabilized discretizations for poroelasticity and the Stokes’ equations. Comput Methods Appl Mech Eng 341:467–484

    Google Scholar 

  • Salimzadeh S, Nick H (2019) A coupled model for reactive flow through deformable fractures in enhanced geothermal systems. Geothermics 81:88–100

    Google Scholar 

  • Salimzadeh S, Nick H, Zimmerman R (2018) Thermoporoelastic effects during heat extraction from low-permeability reservoirs. Energy 142:546–558

    Google Scholar 

  • Scovazzi G, Wheeler M, Mikelic A, Lee S (2017) Analytical and variational numerical methods for unstable miscible displacement flows in porous media. J Comput Phys 335:444–496

    Google Scholar 

  • Sokolova I, Bastisya M, Hajibeygi H (2019) Multiscale finite volume method for finite-volume-based simulation of poroelasticity. J Comput Phys 379:309–324

    Google Scholar 

  • Terzaghi K (1951) Theoretical soil mechanics. Chapman And Hall, London

    Google Scholar 

  • Vermeer P, Verruijt A (1981) An accuracy condition for consolidation by finite elements. Int J Numer Anal Methods Geomech 5(1):1–14

    Google Scholar 

  • Vik H, Salimzadeh S, Nick H (2018) Heat recovery from multiple-fracture enhanced geothermal systems: the effect of thermoelastic fracture interactions. Renew Energy 121:606–622

    Google Scholar 

  • Vinje V, Brucker J, Rognes M, Mardal K, Haughton V (2018) Fluid dynamics in syringomyelia cavities: Effects of heart ate, CSF velocity, CSF velocity waveform and craniovertebral decompression. Neuroradiol J 31:1971400918795482

    Google Scholar 

  • Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, Burovski E, Peterson P, Weckesser W, Bright J, van der Walt SJ, Brett M, Wilson J, Millman KJ, Mayorov N, Nelson ARJ, Jones E, Kern R, Larson E, Carey CJ, Polat İ, Feng Y, Moore EW, VanderPlas J, Laxalde D, Perktold J, Cimrman R, Henriksen I, Quintero EA, Harris CR, Archibald AM, Ribeiro AH, Pedregosa F, van Mulbregt P (2020) SciPy 1.0 Contributors. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nat Methods 17:261–272. https://doi.org/10.1038/s41592-019-0686-2

    Article  Google Scholar 

  • Wang H (2017) Theory of linear poroelasticity with applications to geomechanics and hydrogeology. Princeton University Press, Princeton

    Google Scholar 

  • Wheeler M, Xue G, Yotov I (2014) Coupling multipoint flux mixed finite element methods with continuous Galerkin methods for poroelasticity. Comput Geosci 18(1):57–75

    Google Scholar 

  • White J, Borja R (2008) Stabilized low-order finite elements for coupled solid-deformation/fluid-diffusion and their application to fault zone transients. Comput Methods Appl Mech Eng 197(49–50):4353–4366

    Google Scholar 

  • White J, Borja R (2011) Block-preconditioned Newton–Krylov solvers for fully coupled flow and geomechanics. Comput Geosci 15(4):647

    Google Scholar 

  • White J, Castelletto N, Tchelepi H (2016) Block-partitioned solvers for coupled poromechanics: a unified framework. Comput Methods Appl Mech Eng 303:55–74

    Google Scholar 

  • Zdunek A, Rachowicz W, Eriksson T (2016) A five-field finite element formulation for nearly inextensible and nearly incompressible finite hyperelasticity. Comput Math Appl 72(1):25–47

    Google Scholar 

  • Zhao Y, Choo J (2020) Stabilized material point methods for coupled large deformation and fluid flow in porous materials. Comput Methods Appl Mech Eng 362:112742

    Google Scholar 

Download references

Acknowledgements

This research has received financial support from the Danish Hydrocarbon Research and Technology Centre under the Advanced Water Flooding program. The computational results in this work were produced by the multiphenics library (Ballarin and Rozza 2019), which is an extension of FEniCS (Alnaes et al. 2015) for multiphysics problems. We acknowledge the developers of and contributors to these libraries. SL is supported by the National Science Foundation under Grant No. NSF DMS-1913016. The authors would like to thank Dr. Solomon Seyum for constructive criticism of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. Kadeethum.

Appendices

Appendices

In these appendices, we describe the fully discretized formulation of each method listed in Table 1.

Continuous Galerkin (CG) Method

We begin by defining the finite element space for the continuous Galerkin (CG) method for a vector-valued function

$$\begin{aligned} {\mathscr {U}}_{h}^{{\mathrm {CG}}_{k}}\left( {\mathscr {T}}_{h}\right) :=\left\{ \varvec{\psi _u} \in {\mathbb {C}}^{0}({\varOmega }{; {\mathbb {R}}^d}) :\left. \varvec{\psi _u}\right| _{T} \in {\mathbb {Q}}_{k}(T{; {\mathbb {R}}^d}), \forall T \in {\mathscr {T}}_{h}\right\} , \end{aligned}$$
(37)

where k indicates the order of polynomials, \({\mathbb {C}}^0({\varOmega }{; {\mathbb {R}}^d})\) denotes the space of vector-valued piecewise continuous polynomials, and \({\mathbb {Q}}_{k}(T{; {\mathbb {R}}^d})\) is the space of polynomials of degree at most k over each element T. For our problem, the vector-valued displacement field is approximated using CG space. Next, the CG space for scalar-valued functions is defined as

$$\begin{aligned} {\mathscr {P}}_{h}^{{\mathrm {CG}}_{k}}\left( {\mathscr {T}}_{h}\right) :=\left\{ \psi _p \in {\mathbb {C}}^{0}({\varOmega }) :\left. \psi _p\right| _{T} \in {\mathbb {Q}}_{k}(T), \forall T \in {\mathscr {T}}_{h}\right\} , \end{aligned}$$
(38)

for the pressure solution.

Thus, we seek the approximated displacement solution (\(\varvec{u_h}\)) by discretizing the linear momentum balance Eq. (6) employing the above CG finite element spaces as done in Choo and Lee (2018), Kadeethum et al. (2019a) and Vik et al. (2018). The fully discretized linear momentum balance Eq. (6) can be defined using the following forms

$$\begin{aligned} {\mathscr {A}}_u\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \varvec{\psi _u} \right) = {\mathscr {L}}_u\left( \varvec{\psi _u} \right) , \quad \forall \varvec{\psi _u} \in {\mathscr {U}}_{h}^{{\mathrm {CG}}_{2}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(39)

at each time step \(t^n\), where

$$\begin{aligned} {\mathscr {A}}_u\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \varvec{\psi _u} \right) = \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\sigma }^{\prime }\left( \varvec{u}_{h}\right) : \nabla ^{s} \varvec{\psi _u} \, d V - \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \alpha p_{h} \varvec{I} : \nabla ^{s} \varvec{\psi _u} \, d V,\nonumber \\ \end{aligned}$$
(40)

and

$$\begin{aligned} {\mathscr {L}}_u\left( \varvec{\psi _u} \right) =\sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{f} \varvec{\psi _u} \, d V+\sum _{e \in {\mathscr {E}}_{h}^{N}} \int _{e} {{\varvec{\sigma }}_{D}} \varvec{\psi _u} \, d S, \quad \forall \varvec{\psi _u} \in {\mathscr {U}}_{h}^{{\mathrm {CG}}_{2}}\left( {\mathscr {T}}_{h}\right) . \end{aligned}$$
(41)

Here, \(\nabla ^{s}\) is a symmetric gradient operator. We can split

$$\begin{aligned} {{\mathscr {A}}_u\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \varvec{\psi _u} \right) } := a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) +b\left( p_{h}^{n}, \varvec{\psi _u} \right) , \end{aligned}$$
(42)

by using

$$\begin{aligned} a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\sigma }^{\prime }\left( \varvec{u}_{h}^n\right) : \nabla ^{s} \varvec{\psi _u} \, d V, \end{aligned}$$
(43)
$$\begin{aligned} b\left( p_{h}^{n}, \varvec{\psi _u} \right) := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} -\alpha p_{h}^n \varvec{I} : \nabla ^{s} \varvec{\psi _u} \, d V. \end{aligned}$$
(44)

For the approximated pressure solution (\(p_h\)), we solve the mass balance Eq. (10) combined with Eqs. (11) and (25) as follows

$$\begin{aligned} {\mathscr {A}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) = {\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) , \quad \forall \psi _p \in {\mathscr {P}}_{h}^{{\mathrm {CG}}_{1}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(45)

for each time step \(t^n\), where

$$\begin{aligned}&{\mathscr {A}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) \nonumber \\&\quad := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^n\psi _{p} \, d V + \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V \nonumber \\&\quad \quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \cdot \nabla \psi _{p} \, d V \nonumber \\&\quad \quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \right\} _{\delta _{e}} \cdot \llbracket \psi _p \rrbracket \, d S \nonumber \\&\quad \quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n}) \nabla \psi _{p}\right\} _{\delta _{e}} \cdot \llbracket p_h^n \rrbracket \, d S \nonumber \\&\quad \quad + {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e} \frac{\beta }{h_{e}} {\varvec{\kappa }( \varvec{u}_{h}^{n})}_{{e}} \llbracket p_h^n \rrbracket \cdot \llbracket \psi _p \rrbracket \, d S, \end{aligned}$$
(46)
$$\begin{aligned}&{\mathscr {L}}_p\left( \psi _p {; \varvec{u}_{h}^{n}} \right) \nonumber \\&\quad := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^{n-1}\psi _{p} \, d V+ \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^{n-1} \psi _{p} \, d V \nonumber \\&\quad \quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} g \psi _{p} \, d V+ {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{N}} \int _{e} q_{D} \psi _{p} \, d S \nonumber \\&\quad \quad -{\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e} \varvec{\kappa }( \varvec{u}_{h}^{n}) \nabla \psi _{p} \cdot p_{D} {\varvec{n}} \, d S \nonumber \\&\quad \quad + {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e} \frac{\beta }{h_{e}} {\varvec{\kappa }( \varvec{u}_{h}^{n})}_{{e}} \llbracket \psi _p \rrbracket \cdot p_D \varvec{n} \, d S. \end{aligned}$$
(47)

Here, again, we can split

$$\begin{aligned} {{\mathscr {A}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) } := c\left( \varvec{u}_{h}^{n}, \psi _p \right) +d\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) , \end{aligned}$$
(48)

with

$$\begin{aligned} c\left( \varvec{u}_{h}^{n}, \psi _p \right)&:= \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^n\psi _{p} \, d V, \end{aligned}$$
(49)
$$\begin{aligned} d\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right)&:= \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V \nonumber \\&\qquad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \cdot \nabla \psi _{p} \, d V \nonumber \\&\qquad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \right\} _{\delta _{e}} \cdot \llbracket \psi _p \rrbracket \, d S \nonumber \\&\qquad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n}) \nabla \psi _{p}\right\} _{\delta _{e}} \cdot \llbracket p_h^n \rrbracket \, d S \nonumber \\&\qquad + {\varDelta } t^n \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e} \frac{\beta }{h_{e}} {\varvec{\kappa }( \varvec{u}_{h}^{n})}_{{e}} \llbracket p_h^n \rrbracket \cdot \llbracket \psi _p \rrbracket \, d S. \end{aligned}$$
(50)

We note that the symmetric internal penalty approach is employed to weakly impose the Dirichlet boundary condition (Bazilevs and Hughes 2007; Nitsche 1971; Hansbo 2005). The interior penalty parameter \(\beta \) and \(h_e\) characteristic length are calculated as

$$\begin{aligned} h_{e} :=\frac{{\text {meas}}\left( T^{+}\right) +{\text {meas}}\left( T^{-}\right) }{2 {\text {meas}}(e)}. \end{aligned}$$
(51)

The system of equations is nonlinear (the nonlinear variable being reported after a semicolon for the sake of clarity). Thus, Newton’s method is employed in this work. The Jacobian matrix that arises from Eqs. (39) and (45) is

$$\begin{aligned} \left[ \begin{array}{c@{\quad }c}{{\mathscr {J}}_{ {uu }}} &{} {{\mathscr {J}}_{u p}} \\ {{\mathscr {J}}_{ {pu }}} &{} {{\mathscr {J}}_{ {pp }}} \end{array}\right] \left\{ \begin{array}{l}{\delta \varvec{u}_{h}} \\ {\delta p_{h}} \end{array}\right\} =-\left\{ \begin{array}{l}{R_{u}} \\ {R_{p}} \end{array}\right\} , \end{aligned}$$
(52)

where

$$\begin{aligned} \begin{aligned}&{\mathscr {J}}_{u u}:=\frac{\partial a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{u p}:=\frac{\partial b\left( p_{h}^{n}, \varvec{\psi _u} \right) }{\partial p_{h}^{n}}, \\&{\mathscr {J}}_{p u}:=\frac{\partial c\left( \varvec{u}_{h}^{n}, \psi _p \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{p p}:=\frac{\partial d\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) }{\partial p_{h}^{n}}, \end{aligned} \end{aligned}$$
(53)

and the residual vector is defined as

$$\begin{aligned} \begin{array}{l} {R_{u}:=a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) +b\left( p_{h}^{n}, \varvec{\psi _u} \right) } - {\mathscr {L}}_u\left( \varvec{\psi _u} \right) , \\ {R_{p}:=c\left( \varvec{u}_{h}^{n}, \psi _p \right) +d\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) - {\mathscr {L}}_p\left( \psi _p {; \varvec{u}_{h}^{n}} \right) . } \end{array} \end{aligned}$$
(54)

Here, \(\delta \varvec{u}_{h}\) and \(\delta p_{h}\) are Newton increments of the \(\varvec{u}_h\) and \(p_h\), respectively. The block structure for the CG method arises as follows

$$\begin{aligned} \left[ \begin{array}{l@{\quad }l}{{\mathscr {J}}_{u u}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{up}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_1}} \\ {{\mathscr {J}}_{pu}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_1}} \end{array}\right] \left\{ \begin{array}{l}{\left( \delta \varvec{u}_{h}^{n}\right) ^{{\mathrm {CG}}_2}} \\ {\left( \delta p_{h}^{n}\right) ^{{\mathrm {CG}}_1}} \end{array}\right\} = - \left\{ \begin{array}{l}{R_{u}^{ {\mathrm {CG}}_2}} \\ {R_{p}^{{\mathrm {CG}}_1}} \end{array}\right\} . \end{aligned}$$
(55)

Discontinuous Galerkin (DG) Method

For the discontinuous Galerkin (DG) method presented in Table 1, we approximate the \(\varvec{u}_h\) using the CG finite element space, Eqs. (37) and (39), but we utilize the DG finite element space to approximate the \(p_h\). The DG finite element space with the polynomial order k is given as

$$\begin{aligned} {\mathscr {P}}_{h}^{{\mathrm {DG}}_{k}}\left( {\mathscr {T}}_{h}\right) :=\left\{ \psi _p \in L^{2}({\varOmega }) :\left. \psi _p\right| _{T} \in {\mathbb {Q}}_{k}(T), \forall T \in {\mathscr {T}}_{h}\right\} , \end{aligned}$$
(56)

where \(L^{2}({\varOmega })\) is the space of the square integrable functions. This nonconforming finite element space allows us to consider discontinuous coefficients and preserves the local mass conservation. We then discretize Eqs. (10), (11), and (25) as

$$\begin{aligned} {\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) = {\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) , \quad \forall \psi _p \in {\mathscr {P}}_{h}^{{\mathrm {DG}}_{1}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(57)

for each time step \(t^n\), where

$$\begin{aligned} \begin{aligned}&{\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) \\&\quad := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^n\psi _{p} \, d V + \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V \\&\quad \quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \cdot \nabla \psi _{p} \, d V \\&\quad \quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \right\} _{\delta _{e}} \cdot \llbracket \psi _p \rrbracket \, d S \\&\quad \quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n}) \nabla \psi _{p}\right\} _{\delta _{e}} \cdot \llbracket p_h^n \rrbracket \, d S \\&\quad \quad + {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e} \frac{\beta }{h_{e}} {\varvec{\kappa }( \varvec{u}_{h}^{n})}_{{e}} \llbracket p_h^n \rrbracket \cdot \llbracket \psi _p \rrbracket \, d S. \end{aligned} \end{aligned}$$
(58)

The \({\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) \) term is similar to Eq. (47) as presented in the previous section. Next, we split

$$\begin{aligned} {{\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) } := c\left( \varvec{u}_{h}^{n}, \psi _p \right) +e\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) . \end{aligned}$$
(59)

We utilize the same definition for \(c\left( \varvec{u}_{h}^{n}, \psi _p \right) \) from the CG method, Eq. (49), but we define \(e\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) \) as

$$\begin{aligned} \begin{aligned} e\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right)&:= \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V \\&\quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \cdot \nabla \psi _{p} \, d V \\&\quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n})\left( \nabla p_{h}^n-\rho {\mathbf {g}}\right) \right\} _{\delta _{e}} \cdot \llbracket \psi _p \rrbracket \, d S \\&\quad - {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e}\left\{ \varvec{\kappa }( \varvec{u}_{h}^{n}) \nabla \psi _{p}\right\} _{\delta _{e}} \cdot \llbracket p_h^n \rrbracket \, d S \\&\quad + {\varDelta } t^n \sum _{e \in {\mathscr {E}}_h^{I} \cup {\mathscr {E}}_{h}^{D}} \int _{e} \frac{\beta }{h_{e}} {\varvec{\kappa }( \varvec{u}_{h}^{n})}_{{e}} \llbracket p_h^n \rrbracket \cdot \llbracket \psi _p \rrbracket \, d S. \end{aligned} \end{aligned}$$
(60)

Compared to \({{\mathscr {A}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) }\) from the CG method, we note that there are additional surface integral terms \(\int _{e}\cdot \, d S\) on the interior faces (\(e \in {\mathscr {E}}_h^{I}\)) in \({{\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) }\). This results in more demanding computational time when the matrix is assembled.

Again, we note that this system of equations are nonlinear forms in the displacement \(\varvec{u}_{h}^{n}\). We form the Jacobian matrix that arises from Eqs. (39) and (57) as follows

$$\begin{aligned} \left[ \begin{array}{c@{\quad }c}{{\mathscr {J}}_{ {uu }}} &{} {{\mathscr {J}}_{u p}} \\ {{\mathscr {J}}_{ {pu }}} &{} {{\mathscr {J}}_{ {pp }}} \end{array}\right] \left\{ \begin{array}{l}{\delta \varvec{u}_{h}} \\ {\delta p_{h}} \end{array}\right\} =-\left\{ \begin{array}{l}{R_{u}} \\ {R_{p}} \end{array}\right\} , \end{aligned}$$
(61)

where

$$\begin{aligned} \begin{aligned}&{\mathscr {J}}_{u u}:=\frac{\partial a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{u p}:=\frac{\partial b\left( p_{h}^{n}, \varvec{\psi _u} \right) }{\partial p_{h}^{n}}, \\&{\mathscr {J}}_{p u}:=\frac{\partial c\left( \varvec{u}_{h}^{n}, \psi _p \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{p p}:=\frac{\partial e\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) }{\partial p_{h}^{n}}, \end{aligned} \end{aligned}$$
(62)

and the residual vector is defined as

$$\begin{aligned} \begin{array}{l} {R_{u}:=a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) +b\left( p_{h}^{n}, \varvec{\psi _u} \right) } - {\mathscr {L}}_u\left( \varvec{\psi _u} \right) , \\ {R_{p}:=c\left( \varvec{u}_{h}^{n}, \psi _p \right) +e\left( p_{h}^{n}, \psi _p{; \varvec{u}_{h}^{n}} \right) - {\mathscr {L}}_p\left( \psi _p {; \varvec{u}_{h}^{n}} \right) , } \end{array} \end{aligned}$$
(63)

at each time step \(t^n\). The block structure for the DG method arises as follows

$$\begin{aligned} \left[ \begin{array}{l@{\quad }l} {{\mathscr {J}}_{u u}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{up}^{{\mathrm {CG}}_2 \times {\mathrm {DG}}_1}} \\ {{\mathscr {J}}_{pu}^{{\mathrm {DG}}_1 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {DG}}_1 \times {\mathrm {DG}}_1}} \end{array}\right] \left\{ \begin{array}{l} {\left( \delta \varvec{u}_{h}^{n}\right) ^{{\mathrm {CG}}_2}} \\ {\left( \delta p_{h}^{n}\right) ^{{\mathrm {DG}}_1}} \end{array}\right\} = - \left\{ \begin{array}{l}{R_{u}^{ {\mathrm {CG}}_2}} \\ {R_{p}^{{\mathrm {DG}}_1}} \end{array}\right\} . \end{aligned}$$
(64)

Enriched Galerkin (EG) Method

For the EG method presented in Table 1, we define the EG finite element space with the polynomial order k as

$$\begin{aligned} {\mathscr {P}}_{h}^{{\mathrm {EG}}_{k}}\left( {\mathscr {T}}_{h}\right) :={\mathscr {P}}_{h}^{{\mathrm {CG}}_{k}}\left( {\mathscr {T}}_{h}\right) +{\mathscr {P}}_{h}^{{\mathrm {DG}}_{0}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(65)

where the CG finite element space is enriched by \({\mathscr {P}}_{h}^{{\mathrm {DG}}_{0}}\left( {\mathscr {T}}_{h}\right) \), the piecewise constant functions. As in the previous section, we approximate the displacement (\(\varvec{u}_h\)) using the CG finite element space Eq. (39), but here the \(p_h\) is approximated by the EG finite element space Eq. (65). Thus, we seek \(p_h\) by solving

$$\begin{aligned} {\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) = {\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) , \quad \forall \psi _p \in {\mathscr {P}}_{h}^{{\mathrm {EG}}_{1}}\left( {\mathscr {T}}_{h}\right) . \end{aligned}$$
(66)

We note that the EG method employs the same bilinear \({\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) \) and linear \({\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) \) forms as the DG method. Since the EG space Eq. (65) only takes piecewise constants (DG\(_0\)) to enforce the discontinuity, several terms involving the derivatives in \({\mathscr {B}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right) \) and \({\mathscr {L}}_p\left( \psi _p; \varvec{u}_{h}^{n} \right) \) become zero. Thus, not only does the EG method have fewer degrees of freedom than DG, but it requires less computational time for assembling the matrix.

We again note that this system of equations are nonlinear forms in the displacement \(\varvec{u}_{h}^{n}\). We employ the same Jacobian matrix, Eqs. (61) and (62), and residual vector, Eq. (63), built for the DG method. The block structure used for the DG method Eq. (64), however, is decomposed into

$$\begin{aligned} \left[ \begin{array}{l@{\quad }l@{\quad }l} {{\mathscr {J}}_{u u}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{u p}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_1}} &{} {{\mathscr {J}}_{u p}^{{\mathrm {CG}}_2 \times {\mathrm {DG}}_0}} \\ {{\mathscr {J}}_{p u}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_1}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {CG}}_1 \times {\mathrm {DG}}_0}} \\ {{\mathscr {J}}_{p u}^{{\mathrm {DG}}_0 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {DG}}_0 \times {\mathrm {CG}}_1}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {DG}}_0 \times {\mathrm {DG}}_0}} \end{array} \right] \left\{ \begin{array}{l} {\left( \delta \varvec{u}_{h}^{n}\right) ^{{\mathrm {CG}}_2}} \\ {\left( \delta {p_{h}}^{n}\right) ^{{\mathrm {CG}}_1}}\\ {\left( \delta {p_{h}}^{n}\right) ^{{\mathrm {DG}}_0}} \end{array}\right\} = - \left\{ \begin{array}{l} {{R}_u^{{\mathrm {CG}}_2}} \\ {{R}_p^{{\mathrm {CG}}_1}} \\ {{R}_p^{{\mathrm {DG}}_0}} \end{array}\right\} ,\nonumber \\ \end{aligned}$$
(67)

to satisfy Eq. (66).

Raviart–Thomas Mixed Finite Element (MFE-RT) Method

For the MFE-RT method presented in Table 1, we also approximate the \(\varvec{u}_h\) using the CG finite element space [Eqs. (37) and (39)]. The mass balance Eq. (10) for the MFE-RT method is discretized by using the piecewise constant (i.e., DG finite element space Eq. (56) with \(k=0\)).

Thus, we seek \(p_h\) by solving

$$\begin{aligned} {{\mathscr {C}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n},\varvec{v}_{h}^{n}), \psi _p \right) } = {\mathscr {M}}_p\left( \psi _p \right) , \quad \forall \psi _p \in {\mathscr {P}}_{h}^{{\mathrm {DG}}_{0}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(68)

for each time step \(t^n\), where

$$\begin{aligned} \begin{aligned} {\mathscr {C}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n},\varvec{v}_{h}^{n}), \psi _p; \varvec{u}_{h}^{n} \right)&:= \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^n\psi _{p} \, d V \\&\quad + \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V \\&\quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \nabla \cdot \left( \rho \varvec{v}_{h}^{n} \right) \psi _{p} \, d V, \end{aligned} \end{aligned}$$
(69)

and

$$\begin{aligned} \begin{aligned} {\mathscr {M}}_p\left( \psi _p {; \varvec{u}_{h}^{n}} \right)&:= \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^{n-1}\psi _{p} \, d V \\&\quad + \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^{n-1} \psi _{p} \, d V \\&\quad + {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} g \psi _{p} \, d V. \end{aligned} \end{aligned}$$
(70)

Here, we can split Eq. (69) as

$$\begin{aligned} {{\mathscr {C}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n},\varvec{v}_{h}^{n}), \psi _p \right) } := f\left( \varvec{u}_{h}^{n}, \psi _p \right) +g\left( p_{h}^{n}, \psi _p \right) +h\left( \varvec{v}_{h}^{n}, \psi _p \right) , \end{aligned}$$
(71)

where

$$\begin{aligned} f\left( \varvec{u}_{h}^{n}, \psi _p \right):= & {} \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \alpha \nabla \cdot {\varvec{u}}_{h}^n\psi _{p} \, d V, \end{aligned}$$
(72)
$$\begin{aligned} g\left( p_{h}^{n}, \psi _p \right):= & {} \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \left( \phi c_{f}+\frac{\alpha -\phi }{K_{s}}\right) p_{h}^n \psi _{p} \, d V, \end{aligned}$$
(73)

and

$$\begin{aligned} \begin{aligned} h\left( \varvec{v}_{h}^{n}, \psi _p \right)&:= {\varDelta } t^n \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \nabla \cdot \left( \rho \varvec{v}_{h}^{n} \right) \psi _{p} \, d V. \end{aligned} \end{aligned}$$
(74)

For the velocity approximation (\(\varvec{v}_h\)), we use the RT finite element space, which is defined as

$$\begin{aligned} {\mathscr {V}}_{h}^{{\mathrm {RT}}_{k}}\left( {\mathscr {T}}_{h}\right) :=\left\{ \varvec{\psi _v} \in {\mathbb {C}}^{0}({\varOmega }) :\left. \varvec{\psi _v}\right| _{T} \in {\mathbb {Q}}_{k}(T)^m + x{\mathbb {Q}}_{k}(T), \forall T \in {\mathscr {T}}_{h}\right\} , \end{aligned}$$
(75)

\({\mathbf {q}}(x) =\left( \begin{array}{c}{q_{1}(x)} \\ {q_{2}(x)} \\ {\vdots } \\ {q_{m}(x)} \end{array}\right) +q_{0}(x) \left( \begin{array}{c}{x_{1}} \\ {x_{2}} \\ {\vdots } \\ {x_{m}} \end{array}\right) \quad \forall x:=\left( x_{1}, x_{2}, \ldots , x_{m}\right) ^{{\mathrm {T}}} \in {\varOmega }\), \({\mathbf {q}}(x) \subset {\mathbb {Q}}_{k}(T)^m\), and \(q_{0}(x) \subset {\mathbb {Q}}_{k}(T)\). We then solve the following Darcy velocity Eq. (11) to obtain \(\varvec{v}_{h}^{n}\) by

$$\begin{aligned} {\mathscr {C}}_v\left( (\varvec{v}_{h}^{n}, p_{h}^{n}),\varvec{\psi }_{v}; \varvec{u}_{h}^{n} \right) = {\mathscr {M}}_v\left( \varvec{\psi _v} \right) , \quad \forall \varvec{\psi }_{v} \in {\mathscr {V}}_{h}^{{\mathrm {RT}}_{1}}\left( {\mathscr {T}}_{h}\right) , \end{aligned}$$
(76)

where

$$\begin{aligned} {\mathscr {C}}_v\left( (\varvec{v}_{h}^{n}, p_{h}^{n}),\varvec{\psi }_{v}; \varvec{u}_{h}^{n} \right) := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} p_{h}^{n} \nabla \cdot \varvec{\psi _v} \, d V+\sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \varvec{\kappa }( \varvec{u}_{h}^{n})^{-1} \varvec{v}_{h}^{n} \varvec{\psi _v} \, d V, \nonumber \\ \end{aligned}$$
(77)

and

$$\begin{aligned} \begin{aligned} {\mathscr {M}}_v\left( \varvec{\psi _v} \right) :=&- \sum _{e \in {\mathscr {E}}_{h}^{D}} \int _{e} p_{D} \varvec{\psi }_{v} \cdot \varvec{n} \, d S. \end{aligned} \end{aligned}$$
(78)

Here, we can split

$$\begin{aligned} {{\mathscr {C}}_v\left( (\varvec{v}_{h}^{n}, p_{h}^{n},), \varvec{\psi }_v {; \varvec{u}_{h}^{n}} \right) } := i\left( p_{h}^{n}, \varvec{\psi }_v \right) + j\left( \varvec{v}_{h}^{n}, \varvec{\psi }_v{; \varvec{u}_{h}^{n}} \right) , \end{aligned}$$
(79)

where

$$\begin{aligned} i\left( p_{h}^{n}, \varvec{\psi }_v \right) := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} p_{h}^{n} \nabla \cdot \varvec{\psi _v} \, d V, \end{aligned}$$
(80)

and

$$\begin{aligned} j\left( \varvec{v}_{h}^{n}, \varvec{\psi }_v{; \varvec{u}_{h}^{n}} \right) := \sum _{T \in {\mathscr {T}}_{h}} \int _{T} \rho \varvec{\kappa }( \varvec{u}_{h}^{n})^{-1} \varvec{v}_{h}^{n} \varvec{\psi _v} \, d V. \end{aligned}$$
(81)

Similar to the CG, DG, and EG methods, we note that this system of equations are nonlinear forms for the displacement \(\varvec{u}_{h}^{n}\). We then form the Jacobian matrix that arises from Eqs. (39), (68), and (76) as follows

$$\begin{aligned} \left[ \begin{array}{c@{\quad }c@{\quad }c}{{\mathscr {J}}_{ {uu }}} &{} {{\mathscr {J}}_{up}} &{} {{\mathscr {J}}_{u v}} \\ {{\mathscr {J}}_{ {pu }}} &{} {{\mathscr {J}}_{ {pp }}} &{} {{\mathscr {J}}_{p v}} \\ {{\mathscr {J}}_{ {vu }}} &{} {{\mathscr {J}}_{vp}} &{} {{\mathscr {J}}_{v v}} \end{array}\right] \left\{ \begin{array}{l}{\delta \varvec{u}_{h}} \\ {\delta p_{h}} \\ {\delta \varvec{v}_{h}} \end{array}\right\} =-\left\{ \begin{array}{l}{R_{u}} \\ {R_{p}} \\ {R_{v}} \end{array}\right\} , \end{aligned}$$
(82)

where \(\delta \varvec{v}_{h}\) is the Newton increments of the \(\varvec{v}_h\) and

$$\begin{aligned} \begin{aligned}&{\mathscr {J}}_{u u}:=\frac{\partial a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{u p}:=\frac{\partial b\left( p_{h}^{n}, \varvec{\psi _u} \right) }{\partial p_{h}^{n}}, \quad {\mathscr {J}}_{u v}:=0, \\&{\mathscr {J}}_{p u}:=\frac{\partial f\left( \varvec{u}_{h}^{n}, \psi _p \right) }{\partial \varvec{u}_{h}^{n}}, \quad {\mathscr {J}}_{p p}:=\frac{\partial g\left( p_{h}^{n}, \psi _p \right) }{\partial p_{h}^{n}}, \quad {\mathscr {J}}_{p v}:=\frac{\partial h\left( \varvec{v}_{h}^{n}, \psi _p \right) }{\partial \varvec{v}_{h}^{n}}, \\&{\mathscr {J}}_{v u}:=0, \quad {\mathscr {J}}_{v p}:=\frac{\partial i\left( p_{h}^{n}, \varvec{\psi }_v \right) }{\partial p_{h}^{n}}, \quad {\mathscr {J}}_{v v}:=\frac{\partial j\left( \varvec{v}_{h}^{n}, \varvec{\psi }_v{; \varvec{u}_{h}^{n}} \right) }{\partial \varvec{v}_{h}^{n}}, \end{aligned} \end{aligned}$$
(83)

and the residual vector is defined as

$$\begin{aligned} \begin{array}{l} {R_{u}:=a\left( \varvec{u}_{h}^{n}, \varvec{\psi _u} \right) +b\left( p_{h}^{n}, \varvec{\psi _u} \right) } - {\mathscr {L}}_u\left( \varvec{\psi _u} \right) ,\\ {R_{p}:=f\left( \varvec{u}_{h}^{n}, \psi _p \right) + g\left( p_{h}^{n}, \psi _p \right) +h\left( \varvec{v}_{h}^{n}, \psi _p \right) - {\mathscr {M}}_p\left( \psi _p {; \varvec{u}_{h}^{n}} \right) , } \\ {R_{v}:= i\left( p_{h}^{n}, \varvec{\psi }_v \right) +j\left( \varvec{v}_{h}^{n}, \varvec{\psi }_v{; \varvec{u}_{h}^{n}} \right) - {\mathscr {M}}_v\left( \varvec{\psi _v} \right) .} \end{array} \end{aligned}$$
(84)

The block structure of the MFE-RT method arises as

$$\begin{aligned} \left[ \begin{array}{c@{\quad }c@{\quad }c} {{\mathscr {J}}_{u u}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{u p}^{{\mathrm {CG}}_2 \times {\mathrm {DG}}_0}} &{} 0 \\ {{\mathscr {J}}_{p u}^{{\mathrm {CG}}_2 \times {\mathrm {DG}}_0}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {DG}}_0 \times {\mathrm {DG}}_0}} &{} {{\mathscr {J}}_{p v}^{{\mathrm {DG}}_0 \times {\mathrm {RT}}_1}} \\ 0 &{} {{\mathscr {J}}_{v p}^{{\mathrm {RT}}_1 \times {\mathrm {DG}}_0}} &{} {{\mathscr {J}}_{v v}^{{\mathrm {RT}}_1 \times {\mathrm {RT}}_1}} \end{array} \right] \left\{ \begin{array}{l}{\left( \delta \varvec{u}_{h}^{n}\right) ^{{\mathrm {CG}}_2}} \\ {\left( \delta {p_{h}}^{n}\right) ^{{\mathrm {DG}}_0}} \\ {\left( \delta {\varvec{v}_{h}}^{n}\right) ^{{\mathrm {RT}}_1}} \end{array}\right\} = - \left\{ \begin{array}{l} {{R}_u^{{\mathrm {CG}}_2}} \\ {{R}_p^{{\mathrm {DG}}_0}} \\ {{R}_v^{{\mathrm {RT}}_1}} \end{array}\right\} . \end{aligned}$$
(85)

Continuous Mixed Finite Element (MFE-P2) Method

For the MFE-P2 method presented in Table 1, we utilize a similar system of equations as employed by the MFE-RT method. The displacement \(\varvec{u}_h\) is approximated by the CG finite element space, which is the same as the CG method Eq. (39). The \(p_h\) in this method is approximated by using the CG finite element space Eq. (38) with \(k=1\)

$$\begin{aligned} {\mathscr {C}}_p\left( (\varvec{u}_{h}^{n}, p_{h}^{n},\varvec{v}_{h}^{n}), \psi _p \right) = {\mathscr {M}}_p\left( \psi _p \right) , \quad \forall \psi _p \in {\mathscr {P}}_{h}^{{\mathrm {CG}}_{1}}\left( {\mathscr {T}}_{h}\right) . \end{aligned}$$
(86)

Here, the approximated velocity \(\varvec{v}_h\) is also discretized by the vector-valued CG finite element space Eq. (37) but with higher-order \(k=2\). Thus, we obtain the following for \(\varvec{v}_h\)

$$\begin{aligned} {\mathscr {C}}_v\left( (\varvec{v}_{h}^{n}, p_{h}^{n}),\varvec{\psi }_{v}; \varvec{u}_{h}^{n} \right) = {\mathscr {M}}_v\left( \varvec{\psi _v} \right) , \quad \forall \varvec{\psi }_{v} \in {\mathscr {U}}_{h}^{{\mathrm {CG}}_{2}}\left( {\mathscr {T}}_{h}\right) . \end{aligned}$$
(87)

As a result, the block structure of the MFE-RT method Eq. (85) is modified to

$$\begin{aligned} \left[ \begin{array}{c@{\quad }c@{\quad }c} {{\mathscr {J}}_{u u}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{u p}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_1}} &{} 0 \\ {{\mathscr {J}}_{p u}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_2}} &{} {{\mathscr {J}}_{p p}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_1}} &{} {{\mathscr {J}}_{p v}^{{\mathrm {CG}}_1 \times {\mathrm {CG}}_2}} \\ 0 &{} {{\mathscr {J}}_{v p}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_1}} &{} {{\mathscr {J}}_{v v}^{{\mathrm {CG}}_2 \times {\mathrm {CG}}_2}} \end{array} \right] \left\{ \begin{array}{l}{\left( \delta \varvec{u}_{h}^{n}\right) ^{{\mathrm {CG}}_2}} \\ {\left( \delta {p_{h}}^{n}\right) ^{{\mathrm {CG}}_1}} \\ {\left( \delta {\varvec{v}_{h}}^{n}\right) ^{{\mathrm {CG}}_2}} \end{array}\right\} = - \left\{ \begin{array}{l} {{R}_u^{{\mathrm {CG}}_2}} \\ {{R}_p^{{\mathrm {CG}}_1}} \\ {{R}_v^{{\mathrm {CG}}_2}} \end{array}\right\} .\nonumber \\ \end{aligned}$$
(88)

Remark 2

For both two- and three-field formulations, the Neumann boundary condition is naturally applied on the boundary faces, \(e \in {\mathscr {E}}_{h}^{N}\). For the two-field formulation, the Dirichlet boundary condition is weakly enforced on \(e \in {\mathscr {E}}_{h}^{D}\), for all CG, EG, and DG methods. On the other hand, the three-field formulation strongly applies the Dirichlet boundary conditions.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kadeethum, T., Lee, S. & Nick, H.M. Finite Element Solvers for Biot’s Poroelasticity Equations in Porous Media. Math Geosci 52, 977–1015 (2020). https://doi.org/10.1007/s11004-020-09893-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11004-020-09893-y

Keywords

Navigation