The challenges of integrating a discrete fracture network (DFN) model with a geomechanical analysis increase with the complexity of the DFN model, since a DFN model can include thousands of fractures and result in very complex configurations. Although it is now relatively easy to generate DFN models, to date, comparatively limited attention has been given to the solution of the challenging issues related to optimal mesh generation routines required for geomechanical simulation. For any integrated DFNGeomechanical approach to be efficient and reliable, there is a need to carefully consider the way in which the structural data are embedded in the geomechanical model at the required engineering scale. In this context, this paper introduces a novel method (DFNCleaner), to simplify fracture networks, while maintaining their characteristic properties. We also present, an automated tool (DFNQuality) that incorporates various metrics to measure the DFN quality, and outputs a proposed “x”, which is then used to further constrain the cleaning of the original DFN model. This paper shows example of the ability of the proposed algorithm to clean pillar DFN model, and then compares the simulation results to those obtained manually by both intermediate and experienced users of hybrid Finite-Discrete Element method codes.
Dfncleaner: A Novel Automated Approach To Improve DFN Integration for Geomechanical Analysis
Karimi Sharif, Ladan, Elmo, Davide, and Doug Stead. "Dfncleaner: A Novel Automated Approach To Improve DFN Integration for Geomechanical Analysis." Paper presented at the 2nd International Discrete Fracture Network Engineering Conference, Seattle, Washington, USA, June 2018.
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