A review of structural data collection methodologies for discrete fracture network generation

Authors: Sewnun, D; Wesseloo, J; Heinsen Egan, M

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DOI https://doi.org/10.36487/ACG_repo/2205_72

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Sewnun, D, Wesseloo, J & Heinsen Egan, M 2022, 'A review of structural data collection methodologies for discrete fracture network generation', in Y Potvin (ed.), Caving 2022: Proceedings of the Fifth International Conference on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 1047-1060, https://doi.org/10.36487/ACG_repo/2205_72

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Abstract:
The variability in a rock mass must be considered in geotechnical engineering analyses and designs. Discrete fracture network (DFN) modelling accounts for structural variability in a rock mass, providing a valuable tool that may be used in various geotechnical applications. DFNs provide a statistical representation of the rock mass discontinuity system by the stochastic generation of discontinuity sets. This is based on structural data collected in the field from boreholes or by mapping exposures. DFN generation therefore involves structural data collection from which discontinuity sets may be defined. Each discontinuity set within a single structural domain is characterised using statistical distributions to describe the orientation, spacing, and trace lengths of the discontinuities, which are used to provide input parameters for DFN generation. The quality of a DFN therefore relies on the quality of the field data and its interpretation. This paper reviews the various approaches available to collect structural data for DFN generation. The advantages and limitations of each method is given, and data collection and analysis strategies are outlined.

Keywords: structural data collection, discrete fracture network modelling

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