A methodology for pseudo-genetic stochastic modeling of discrete fracture networks

Bonneau, François; Henrion, Vincent; Caumon, Guillaume; Renard, Philippe; Sausse, Judith

doi:10.1016/j.cageo.2013.02.004

Cited by 31 publications

(17 citation statements)

References 31 publications

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“…Different fracture sets can have different geometrical (e.g., size, aperture, and density) and mineralogical (infill material and quantity) properties and thus may have different impacts on the hydrology of the system [ Agosta et al , ]. In addition, numerical models of fracture systems and their associated fluid pathways in reservoirs can be constrained by the assumed probability distributions of aperture, length, and density of each fracture set [e.g., Dershowitz and Einstein , ; Bonneau et al , ], which thus need to be assessed carefully. Analogue outcrop studies can provide extensive and detailed fracture system characterization but may not be directly comparable to conditions in reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

et al. 2017

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Acoustic borehole televiewer (BHTV) logs provide measurements of fracture attributes (orientations, thickness, and spacing) at depth. Orientation, censoring, and truncation sampling biases similar to those described for one‐dimensional outcrop scanlines, and other logging or drilling artifacts specific to BHTV logs, can affect the interpretation of fracture attributes from BHTV logs. K‐means, fuzzy K‐means, and agglomerative clustering methods provide transparent means of separating fracture groups on the basis of their orientation. Fracture spacing is calculated for each of these fracture sets. Maximum likelihood estimation using truncated distributions permits the fitting of several probability distributions to the fracture attribute data sets within truncation limits, which can then be extrapolated over the entire range where they naturally occur. Akaike Information Criterion (AIC) and Schwartz Bayesian Criterion (SBC) statistical information criteria rank the distributions by how well they fit the data. We demonstrate these attribute analysis methods with a data set derived from three BHTV logs acquired from the high‐temperature Rotokawa geothermal field, New Zealand. Varying BHTV log quality reduces the number of input data points, but careful selection of the quality levels where fractures are deemed fully sampled increases the reliability of the analysis. Spacing data analysis comprising up to 300 data points and spanning three orders of magnitude can be approximated similarly well (similar AIC rankings) with several distributions. Several clustering configurations and probability distributions can often characterize the data at similar levels of statistical criteria. Thus, several scenarios should be considered when using BHTV log data to constrain numerical fracture models.

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Section: Introductionmentioning

confidence: 99%

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

et al. 2017

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“…As it has been shown in the literature (e.g., Mace, 2006;Davy et al, 2013;Bonneau et al, 2013), geomechanical control over the fracture growth, relative position, and interaction are very important. Here, these interactions are not considered because the aim of the paper is to show how the implicit method can be used to rotate the fractures within the structures.…”

Section: Discussionmentioning

confidence: 99%

“…Other authors use geomechanical models in which the fractures grow during the deformation process, and the complex interactions between themtruncation of fracture sets against each other, already existing fractures damage zone and shadow zone (Olson, 1993) -can be modeled (Maerten et al, 2000), but these models are very difficult to condition by field observations, and need high computational resources. More recently, hybrid (combined stochastic and geomechanical) models have been proposed (Mace, 2006), as well as pseudo-genetic models (Bonneau et al, 2013;Davy et al, 2013). These techniques mimic the complex interactions between fractures without solving all the complexity of the fracturing physics.…”

Section: Introductionmentioning

confidence: 99%

Stochastic fracture generation accounting for the stratification orientation in a folded environment based on an implicit geological model

Borghi

Renard

Fournier

et al. 2015

Engineering Geology

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a b s t r a c t Keywords:Geological modeling Discrete fracture network (DFN) Stochastic modeling Structural geology This paper presents a new approach in generating stochastic discrete fracture networks. The particularity of the approach is that it allows us to simulate the theoretical families of fractures that are expected in a folded environment. The approach produces fractures that are consistent with the local stratigraphic orientation. The fractures are modeled as simple rectangular planar objects. When they are modeled, they are rotated according to the local stratigraphic orientation. As the stratigraphy is modeled using an implicit approach, we use the gradient of this geological potential field to retrieve the information about the geological orientation. The fracture number and size are following user-defined probability density functions.

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“…As argued in the review of Pyrcz et al (2015), these models make it possible to consider genetic principles such as erosion, progradation and aggradation of sedimentary deposits in an automatic way. Similarly, pseudo-process-based models have also been proposed in the area of fracture modeling to approximate mechanical interactions and truncations that occur during fracture growth (Bonneau et al 2013;Davy et al 2013;Srivastava et al 2005). At a larger scale, a recent trend has been to simulate possible stochastic geometries where the number and the connectivity of faults is variable (Aydin and Caers 2017;Cherpeau et al 2010Cherpeau et al , 2012Cherpeau and Caumon 2015;Holden et al 2003;Julio et al 2015a).…”

Section: Object Uncertaintymentioning

confidence: 99%

Geological Objects and Physical Parameter Fields in the Subsurface: A Review

Caumon

2018

Handbook of Mathematical Geosciences

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Geologists and geophysicists often approach the study of the Earth using different and complementary perspectives. To simplify, geologists like to define and study objects and make hypotheses about their origin, whereas geophysicists often see the earth as a large, mostly unknown multivariate parameter field controlling complex physical processes. This chapter discusses some strategies to combine both approaches. In particular, I review some practical and theoretical frameworks associating petrophysical heterogeneities to the geometry and the history of geological objects. These frameworks open interesting perspectives to define prior parameter space in geophysical inverse problems, which can be consequential in under-constrained cases.

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A methodology for pseudo-genetic stochastic modeling of discrete fracture networks

Cited by 31 publications

References 31 publications

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

Stochastic fracture generation accounting for the stratification orientation in a folded environment based on an implicit geological model

Geological Objects and Physical Parameter Fields in the Subsurface: A Review

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