Reduced Fracture Finite Element Model Analysis of an Efficient Two-Scale Hybrid Embedded Fracture Model
KAUST DepartmentComputational Transport Phenomena Lab
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2017-06-09
Print Publication Date2017
Permanent link to this recordhttp://hdl.handle.net/10754/625064
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AbstractA Hybrid Embedded Fracture (HEF) model was developed to reduce various computational costs while maintaining physical accuracy (Amir and Sun, 2016). HEF splits the computations into fine scale and coarse scale. Fine scale solves analytically for the matrix-fracture flux exchange parameter. Coarse scale solves for the properties of the entire system. In literature, fractures were assumed to be either vertical or horizontal for simplification (Warren and Root, 1963). Matrix-fracture flux exchange parameter was given few equations built on that assumption (Kazemi, 1968; Lemonnier and Bourbiaux, 2010). However, such simplified cases do not apply directly for actual random fracture shapes, directions, orientations …etc. This paper shows that the HEF fine scale analytic solution (Amir and Sun, 2016) generates the flux exchange parameter found in literature for vertical and horizontal fracture cases. For other fracture cases, the flux exchange parameter changes according to the angle, slop, direction, … etc. This conclusion rises from the analysis of both: the Discrete Fracture Network (DFN) and the HEF schemes. The behavior of both schemes is analyzed with exactly similar fracture conditions and the results are shown and discussed. Then, a generalization is illustrated for any slightly compressible single-phase fluid within fractured porous media and its results are discussed.
CitationAmir SZ, Chen H, Sun S (2017) Reduced Fracture Finite Element Model Analysis of an Efficient Two-Scale Hybrid Embedded Fracture Model. Procedia Computer Science 108: 1873–1882. Available: http://dx.doi.org/10.1016/j.procs.2017.05.052.
SponsorsKing Abdullah University of Science and Technology (KAUST) funding supported the research reported in this publication.
JournalProcedia Computer Science