Review of the deterministic modelling of deformation zones and fracture domains at the site proposed for a spent nuclear fuel repository, Sweden, and consequences of structural anisotropy

Stephens, Michael B.; Follin, Sven; Petersson, Jesper; Isaksson, Hans; Juhlin, Christopher; Simeonov, Assen

doi:10.1016/j.tecto.2015.03.027

Cited by 26 publications

(19 citation statements)

References 26 publications

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“…The fracture characteristics can be quantified by using various statistical parameters, including the fracture orientation, length, shape, and permeability alongside the fracture intensity and 25 connectivity (Bonnet et al, 2001;Botros et al, 2008;Bour et al, 2002;Koike et al, 2015;Stephens et al, 2015). These commonly used parameters represent fracture networks at sites of interest and bridge gaps between limited field observations and flow and transport implementations for site-specific issues.…”

Section: Introductionmentioning

confidence: 99%

Stochastic modeling of flow and conservative transport in threedimensional discrete fracture networks

Lee¹,

Ni²,

Lin³

et al. 2018

Preprint

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Section: Introductionmentioning

confidence: 99%

Stochastic modeling of flow and conservative transport in threedimensional discrete fracture networks

Lee¹,

Ni²,

Lin³

et al. 2018

Preprint

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“…With increasingly available computer power, 3-D modelling or geometrical visualizations have become widespread, as they can be performed on a desktop computer (e.g. Bistacchi et al, 2008;Caumon et al, 2009;Hassen et al, 2016;Sausse et al, 2010;Stephens et al, 2015). 3-D models widely serve as a basis for subsequent investigations, such as stress modelling or fluid flow modelling (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…3-D models widely serve as a basis for subsequent investigations, such as stress modelling or fluid flow modelling (e.g. Hassen et al, 2016;Stephens et al, 2015). Explicit structural modelling can further be subdivided into stochastic and deterministic methods.…”

Section: Introductionmentioning

confidence: 99%

“…Deterministic approaches yield a single output for input parameters, analogous to drawing a map (e.g. Stephens et al, 2015), whereas as in stochastic approaches parameters are defined by a probabilistic density function with a component of randomness (e.g. Cherpeau and Caumon, 2015;González-Garcia and Jessell, 2016;Jørgensen et al, 2015;Koike et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Methods and uncertainty estimations of 3-D structural modelling in crystalline rocks: a case study

et al. 2017

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Abstract. Exhumed basement rocks are often dissected by faults, the latter controlling physical parameters such as rock strength, porosity, or permeability. Knowledge on the threedimensional (3-D) geometry of the fault pattern and its continuation with depth is therefore of paramount importance for applied geology projects (e.g. tunnelling, nuclear waste disposal) in crystalline bedrock. The central Aar massif (Central Switzerland) serves as a study area where we investigate the 3-D geometry of the Alpine fault pattern by means of both surface (fieldwork and remote sensing) and underground ground (mapping of the Grimsel Test Site) information. The fault zone pattern consists of planar steep major faults (kilometre scale) interconnected with secondary relay faults (hectometre scale). Starting with surface data, we present a workflow for structural 3-D modelling of the primary faults based on a comparison of three extrapolation approaches based on (a) field data, (b) Delaunay triangulation, and (c) a best-fitting moment of inertia analysis. The quality of these surface-data-based 3-D models is then tested with respect to the fit of the predictions with the underground appearance of faults. All three extrapolation approaches result in a close fit ( > 10 %) when compared with underground rock laboratory mapping. Subsequently, we performed a statistical interpolation based on Bayesian inference in order to validate and further constrain the uncertainty of the extrapolation approaches. This comparison indicates that fieldwork at the surface is key for accurately constraining the geometry of the fault pattern and enabling a proper extrapolation of major faults towards depth. Considerable uncertainties, however, persist with respect to smaller-sized secondary structures because of their limited spatial extensions and unknown reoccurrence intervals.

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Section: Introductionmentioning

confidence: 99%

Methods and uncertainty-estimations of 3D structural modelling in crystalline rocks: A case study

Schneeberger¹,

Varga²,

Egli³

et al. 2017

Preprint

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show abstract

Review of the deterministic modelling of deformation zones and fracture domains at the site proposed for a spent nuclear fuel repository, Sweden, and consequences of structural anisotropy

Cited by 26 publications

References 26 publications

Stochastic modeling of flow and conservative transport in threedimensional discrete fracture networks

Stochastic modeling of flow and conservative transport in threedimensional discrete fracture networks

Methods and uncertainty estimations of 3-D structural modelling in crystalline rocks: a case study

Methods and uncertainty-estimations of 3D structural modelling in crystalline rocks: A case study

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