2019
DOI: 10.1016/j.ijrmms.2018.11.003
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A geostatistical approach to estimating the parameters of a 3D Cox-Boolean discrete fracture network from 1D and 2D sampling observations

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Cited by 11 publications
(5 citation statements)
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“…In this section, the Galerkin finite element method is used to discretize the governing equations Equations ( 9) and (10). Then, the primary unknowns of concentration and fluid pressure can be calculated in a unified formulation.…”
Section: Methodsmentioning
confidence: 99%
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“…In this section, the Galerkin finite element method is used to discretize the governing equations Equations ( 9) and (10). Then, the primary unknowns of concentration and fluid pressure can be calculated in a unified formulation.…”
Section: Methodsmentioning
confidence: 99%
“…[7][8][9] In the past decades, two categories of numerical methods have been developed to model and analyze fractured porous media. The first category is the geostatistical-based methods, 10,11 which focus on investigation of statistical features of the naturally created fracture networks, as well as visualization approaches based on the statistical study. It does not consider numerical simulation of fluid dynamics and geomechanics.…”
Section: Introductionmentioning
confidence: 99%
“…Data from exposed rock faces, such as natural outcrops, excavation faces, and boreholes have proved to be useful (Tonon and Chen 2007). Among sampling techniques for deriving fracture parameters, the most utilized are in-hole images or wireline geophysical logging (Ozkaya aand Mattner 2003;Hekmatnejad et al 2019), scanline survey, circle sampling or window survey (Priest and Hudson 1981a, b;Kulatilake et al 2003;Kulatilake and Wu 1984;Einstein 1998, 2000;Song and Lee 2001;Jimenez-Rodriguez and Sitar 2006), as well as digital photogrammetry and laser scanning techniques (Elmo et al 2015;Vollgger and Cruden 2016).…”
Section: Introductionmentioning
confidence: 99%
“…The spatial structure of the fractures' support points is another fundamental aspect in DFN models. The homogeneous Poisson-Boolean point process has been widely used (Baecher et al 1977;Kulatilake and Wu 1984;Zhang and Einstein 1998;Song and Lee 2001;Jimenez-Rodriguez and Sitar 2006;Hekmatnejad et al 2019). Other types of pointsupporting processes are the doubly stochastic Poisson, or Cox, the Levy-Lee Fractal, the non-stationary Poisson and the Gibbs processes, among others.…”
Section: Introductionmentioning
confidence: 99%
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