Authors: Pierce, ME; Stonestreet, P; Orrego, C; Tennant, D; Garza-Cruz, TV; Furtney, J; Thielsen, C

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DOI https://doi.org/10.36487/ACG_repo/2205_71

Cite As:
Pierce, ME, Stonestreet, P, Orrego, C, Tennant, D, Garza-Cruz, TV, Furtney, J & Thielsen, C 2022, 'Development of rock mass strength block models at Cadia East mine', in Y Potvin (ed.), Caving 2022: Fifth International Conference on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 1033-1046, https://doi.org/10.36487/ACG_repo/2205_71

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Abstract:
Block models of rock mass strength have been developed at Cadia East mine to support forecasting of excavation performance. This paper describes four key aspects of the workflow that have enabled forecasting of rock mass strength throughout the entire orebody: 1) high density measurements of the spatial variability in intact and defected rock strength, derived from systematic point load testing of core from select boreholes; 2) continuous estimates of core-scale rock strength along all boreholes (including those with no or low density testing), enabled by application of machine learning to all available geological and geotechnical data, 3) estimation of tunnel-scale rock mass strength from the local statistical distribution of core-scale strengths, enabled by synthetic rock mass (SRM) testing, and 4) development of an integrated litho-structural model and the implementation of a structural trend to estimate block variables.

Keywords: cave mining, systematic point load testing, machine learning, synthetic rock mass, rock mass strength, block modelling

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