4D data management and modelling in the assessment of deep underground mining hazard

Authors: McGaughey, WJ Download Paper

DOI https://doi.org/10.36487/ACG_rep/1410_04_McGaughey

Cite As:
McGaughey, WJ 2014, '4D data management and modelling in the assessment of deep underground mining hazard', in M Hudyma & Y Potvin (eds), Deep Mining 2014: Proceedings of the Seventh International Conference on Deep and High Stress Mining, Australian Centre for Geomechanics, Perth, pp. 93-106, https://doi.org/10.36487/ACG_rep/1410_04_McGaughey



Abstract:
A framework is presented for quantitative assessment of deep underground mining hazard. It is general in the sense that it may be applied to many types of underground geotechnical and mining challenges. We present a case study illustrating the methodology from the former Xstrata Craig Mine in Sudbury, now closed, which experienced significant fault-slip rockbursting while in operation. The general approach described is statistical, based on data from a site history that quantitatively assesses correlations between falls of ground and various objectively measurable criteria. The hazard criteria are in the categories of geology, rock quality, stress, seismicity, development geometry and production sequencing, blasting, and various geotechnical monitoring systems. The criteria are modelled throughout the mine area of interest and quantitatively combined into an overall hazard index using weights established by the statistical correlation. In the Craig Mine example, several criteria in each of the major categories were modelled and combined to yield independent estimations of hazard in the ore zone and footwall. The statistical analysis clearly showed that individual hazard criteria could be quantitatively correlated to the experience offault-slip rockbursting, with significantly different results in the ore zone and footwall. Modelling the hazard criteria can be challenging, not least because many of the key criteria, and thus the resulting models, are four-dimensional. In practice the 4D nature of the problem is handled by time-stepping a 3D model. The modelling requires interpretational judgement in terms of how data such as structure, rock quality, and seismicity, often located far into the rock mass away from development, manifest hazard on the mine infrastructure where it is experienced. A 4D data management system is required to make the modelling efficient, particularly if it is set up to respond to real time data. Using the Craig Mine case study, we review the key design elements of such a 4D data management foundation, a 4D modelling system, and the 4D deep underground mining hazard assessment framework resulting from their integration.

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