journal article·2022-04Open access

Energetic formulation of large‐deformation poroelasticity

Mina Karimi, Mehrdad Massoudi, Noel Walkington, Matteo Pozzi, Kaushik Dayal

Abstract

Abstract The modeling of coupled fluid transport and deformation in a porous medium is essential to predict the various geomechanical process such as CO2 sequestration, hydraulic fracturing, and so on. Current applications of interest, for instance, that include fracturing or damage of the solid phase, require a nonlinear description of the large deformations that can occur. This paper presents a variational energy‐based continuum mechanics framework to model large‐deformation poroelasticity. The approach begins from the total free energy density that is additively composed of the free energy of the components. A variational procedure then provides the balance of momentum, fluid transport balance, and pressure relations. A numerical approach based on finite elements is applied to analyze the behavior of saturated and unsaturated porous media using a nonlinear constitutive model for the solid skeleton. Examples studied include the Terzaghi and Mandel problems; a gas–liquid phase‐changing fluid; multiple immiscible gases; and unsaturated systems where we model injection of fluid into soil. The proposed variational approach can potentially have advantages for numerical methods as well as for combining with data‐driven models in a Bayesian framework.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Hydraulic Fracturing and Reservoir Analysis · Model Reduction and Neural Networks · Rock Mechanics and Modeling

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Civil and Environmental Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA

National Energy Technology Laboratory Pittsburgh Pennsylvania USA

Center for Nonlinear Analysis Department of Mathematical Sciences Carnegie Mellon University Pittsburgh Pennsylvania USA

Department of Mechanical Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA

Funding

National Science Foundation · Army Research Office · Office of Naval Research · United States-Israel Binational Science Foundation

References (61)

Show source-provided references
1. 10.1007/s12572-009-0001-z10.1007/s12572-009-0001-z ↗
2. Spatially distributed landslide triggering analyses accounting for coupled infiltration and volume change
3. 10.1007/s11440-019-00813-x10.1007/s11440-019-00813-x ↗
4. Selvadurai APS · 2013
5. 10.1115/1.312139710.1115/1.3121397 ↗
6. 10.1017/jog.2020.1610.1017/jog.2020.16 ↗
7. 10.1016/j.cnsns.2014.10.00510.1016/j.cnsns.2014.10.005 ↗
8. 10.1002/nag.216110.1002/nag.2161 ↗
9. 10.1115/1.404592510.1115/1.4045925 ↗
10. 10.1016/j.sandf.2017.11.00810.1016/j.sandf.2017.11.008 ↗
11. 10.1029/2018JB01706210.1029/2018JB017062 ↗
12. 10.1016/j.jmps.2010.01.00910.1016/j.jmps.2010.01.009 ↗
13. vonStrengV Abi‐AklR GiovanardiB CohenT.Morphogenesis and proportionate growth: a finite element investigation of surface growth with coupled diffusion.arXiv preprint arXiv:2005.10747.2020.
14. 10.1002/nme.328210.1002/nme.3282 ↗
15. 10.1007/s10596-019-9811-710.1007/s10596-019-9811-7 ↗
16. 10.1137/17M111689110.1137/17M1116891 ↗
17. 10.1016/j.cma.2021.11397510.1016/j.cma.2021.113975 ↗
18. 10.1002/2013WR01517510.1002/2013WR015175 ↗
19. 10.1016/0309-1708(79)90025-310.1016/0309-1708(79)90025-3 ↗
20. 10.1137/19M125611710.1137/19M1256117 ↗
21. Le problem de la consolidation des matieres argileuses sous une charge
22. 10.1063/1.171288610.1063/1.1712886 ↗
23. Coussy O · 2004
24. Wang HF · 2000
25. 10.1115/1.141093510.1115/1.1410935 ↗
26. 10.1016/S0021-9290(98)00161-410.1016/S0021-9290(98)00161-4 ↗
27. 10.1029/JB078i023p0492410.1029/JB078i023p04924 ↗
28. 10.1103/PhysRevApplied.5.04402010.1103/PhysRevApplied.5.044020 ↗
29. 10.1016/j.mechmat.2011.07.01010.1016/j.mechmat.2011.07.010 ↗
30. 10.1016/j.jmps.2007.11.01010.1016/j.jmps.2007.11.010 ↗
31. 10.1016/j.cma.2004.02.01410.1016/j.cma.2004.02.014 ↗
32. 10.1016/j.cma.2003.12.06710.1016/j.cma.2003.12.067 ↗
33. 10.1002/nme.460510.1002/nme.4605 ↗
34. 10.1016/0020-7225(82)90082-910.1016/0020-7225(82)90082-9 ↗
35. 10.1016/j.ijsolstr.2005.04.04510.1016/j.ijsolstr.2005.04.045 ↗
36. 10.1007/s11242-006-9058-310.1007/s11242-006-9058-3 ↗
37. 10.1016/0020-7225(95)00089-510.1016/0020-7225(95)00089-5 ↗
38. 10.1016/0045-7825(94)00720-810.1016/0045-7825(94)00720-8 ↗
39. 10.1002/nag.253610.1002/nag.2536 ↗
40. 10.1115/1.403104910.1115/1.4031049 ↗
41. 10.1098/rspa.2010.001810.1098/rspa.2010.0018 ↗
42. 10.1016/j.jmps.2010.07.02010.1016/j.jmps.2010.07.020 ↗
43. Strang G · 1973
44. KarimiM MassoudiM DayalK PozziM.High‐dimensional nonlinear bayesian inference of poroelastic fields from pressure data.submitted 2022.10.31223/X5F95F ↗
45. 10.1017/CBO978051176295610.1017/CBO9780511762956 ↗
46. 10.1016/0167-2789(90)90015-H10.1016/0167-2789(90)90015-H ↗
47. 10.1017/CBO978051154713310.1017/CBO9780511547133 ↗
48. 10.1016/j.jmps.2013.09.02510.1016/j.jmps.2013.09.025 ↗
49. 10.1016/j.eml.2018.07.00510.1016/j.eml.2018.07.005 ↗
50. 10.1007/s10704-017-0234-y10.1007/s10704-017-0234-y ↗
51. 10.1016/j.jmps.2015.04.01010.1016/j.jmps.2015.04.010 ↗
52. 10.1016/j.jmps.2015.05.00110.1016/j.jmps.2015.05.001 ↗
53. 10.1007/3-540-26737-9_110.1007/3-540-26737-9_1 ↗
54. 10.1029/2011WR01085910.1029/2011WR010859 ↗
55. Bielinski A · 2007
56. 10.2118/1225-PA10.2118/1225-PA ↗
57. Müller I · 2009
58. 10.2118/20184-PA10.2118/20184-PA ↗
59. Oden JT · 2012
60. 10.1007/s00466-005-0685-210.1007/s00466-005-0685-2 ↗
61. 10.1016/j.cma.2003.08.00810.1016/j.cma.2003.08.008 ↗