Impact of a stochastic sequential initiation of fractures on the spatial correlations and connectivity of discrete fracture networks: STOCHASTIC SEQUENTIAL DFN SIMULATION

Francois Bonneau and Guillaume Caumon and Philippe Renard. ( 2016 )
in: Journal of Geophysical Research: Solid Earth, 121:8 (5641--5658)

Abstract

Discrete fracture networks (DFNs) are classically simulated using stochastic point processes which neglect mechanical interactions between fractures and yield a low spatial correlation in a network. We propose to emulate these interactions in three dimensions by implanting fractures using a sequential parent-daughter Poisson point process while honoring statistical characterization data. The hierarchical organization of the resulting DFNs seems consistent with the fracturing process. This has been investigated in 3D by computing the correlation dimension of DFNs. Sensitivity analysis on the input simulation parameters show that various degrees of spatial correlation emerge from this process. The connectivity of these correlated fracture networks has been investigated at several scales and compared to those described in the literature. Our study confirms that spatial correlations can affect the percolation threshold and the connectivity at a particular scale.

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BibTeX Reference

@ARTICLE{bonneauJGR2016,
    author = { Bonneau, Francois and Caumon, Guillaume and Renard, Philippe },
     title = { Impact of a stochastic sequential initiation of fractures on the spatial correlations and connectivity of discrete fracture networks: STOCHASTIC SEQUENTIAL DFN SIMULATION },
     month = { "aug" },
   journal = { Journal of Geophysical Research: Solid Earth },
    volume = { 121 },
    number = { 8 },
      year = { 2016 },
     pages = { 5641--5658 },
      issn = { 21699313 },
       url = { http://doi.wiley.com/10.1002/2015JB012451 },
       doi = { 10.1002/2015JB012451 },
  abstract = { Discrete fracture networks (DFNs) are classically simulated using stochastic point processes which neglect mechanical interactions between fractures and yield a low spatial correlation in a network. We propose to emulate these interactions in three dimensions by implanting fractures using a sequential parent-daughter Poisson point process while honoring statistical characterization data. The hierarchical organization of the resulting DFNs seems consistent with the fracturing process. This has been investigated in 3D by computing the correlation dimension of DFNs. Sensitivity analysis on the input simulation parameters show that various degrees of spatial correlation emerge from this process. The connectivity of these correlated fracture networks has been investigated at several scales and compared to those described in the literature. Our study confirms that spatial correlations can affect the percolation threshold and the connectivity at a particular scale. }
}