Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model

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External Research Organisations

  • University of Texas at Austin
  • Austrian Academy of Sciences
  • Technical University of Munich (TUM)
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Details

Original languageEnglish
Pages (from-to)111-132
Number of pages22
JournalComputer Methods in Applied Mechanics and Engineering
Volume305
Publication statusPublished - 15 Jun 2016
Externally publishedYes

Abstract

This work presents phase field fracture modeling in heterogeneous porous media. We develop robust and efficient numerical algorithms for pressure-driven and fluid-driven settings in which the focus relies on mesh adaptivity in order to save computational cost for large-scale 3D applications. In the fluid-driven framework, we solve for three unknowns pressure, displacements and phase field that are treated with a fixed-stress iteration in which the pressure and the displacement-phase-field system are decoupled. The latter subsystem is solved with a combined Newton approach employing a primal-dual active set method in order to account for crack irreversibility. Numerical examples for pressurized fractures and fluid filled fracture propagation in heterogeneous porous media demonstrate our developments. In particular, mesh refinement allows us to perform systematic studies with respect to the spatial discretization parameter.

Keywords

    Adaptive finite elements, Fluid filled fracture, Phase field, Porous media, Primal-dual active set

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Cite this

Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model. / Lee, Sanghyun; Wheeler, Mary F.; Wick, Thomas.
In: Computer Methods in Applied Mechanics and Engineering, Vol. 305, 15.06.2016, p. 111-132.

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N1 - Funding Information: The authors want to acknowledge that contributions from S. Lee were supported by funding from the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, and Office of Basic Energy Sciences , DOE Project # DE-SC0001114 . The research by M. F. Wheeler was partially supported by ConocoPhilips grant UTA 10-000444 , Statoil grant STNO-4502931834 , and T. Wick was partially supported by the Austrian Academy of Sciences , The Institute for Computational Engineering and Sciences JT Oden fellowship , and the Center for Subsurface Modeling at UT Austin . Publisher Copyright: © 2016 Elsevier B.V. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

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