Structural data collection as a key input for discrete fracture network analysis

Authors: Byrne, C; Zorzi, L; Rogers, S Download Paper Open access courtesy of:

DOI https://doi.org/10.36487/ACG_repo/2335_24

Cite As:
Byrne, C, Zorzi, L & Rogers, S 2023, 'Structural data collection as a key input for discrete fracture network analysis', in PM Dight (ed.), SSIM 2023: Third International Slope Stability in Mining Conference, Australian Centre for Geomechanics, Perth, pp. 399-408, https://doi.org/10.36487/ACG_repo/2335_24



Abstract:
Accurate characterisation of the geometry and continuity of structural systems (joint, fault and vein systems) within porphyry deposits is essential during all stages of mine life. Structural systems associated with porphyry deposits are generally complex, with highly segmented fault systems, interdependencies between faults and dykes, and spatially varying vein mineralogies and intensities. These intricacies are a function of the deformational, rheological and hydrothermal history of the geological system. The generation of a comprehensive 3D geological interpretation tailored to geotechnical and hydrogeological designs and assessments requires a workflow that includes the development of a conceptual model, data collection and storage, quality control and interpretation of data. During the lifetime of an operational mine, the structural model should ideally be evolving into a comprehensive database that contains not only largescale faults (i.e. regional and mine scale) but also an insight into small-scale fabrics, represented by discrete fracture networks (DFN), that may be present in the rock mass. A significant quantity of structural information must be available to allow for the generation of DFN models for numerous fabrics in the rock mass, including open structures, mafic dykes and vein structures. The correlation between large-scale and small-scale structures is a novel modelling approach that has provided great insight into strategies for data collection and interpretation. This approach also gives a heightened level of clarity to the genetic and evolutionary relationship that can exist between structural systems and deposits themselves. This paper will present the methodology used to identify and delineate key structures, describe characterisation methodologies that have been applied, and present examples of how identification and characterisation of structural systems can successfully inform decision-making for mining operations.

Keywords: discrete fracture network, optimisation, workflow, data collection, stability, structural geology

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