Framework to predict open pit mine failure runout

Authors: Goldstein, D; Pace, R; Jung, JD; Young, D; Le Roux, KA Download Paper Open access courtesy of:

DOI https://doi.org/10.36487/ACG_repo/2335_41

Cite As:
Goldstein, D, Pace, R, Jung, JD, Young, D & Le Roux, KA 2023, 'Framework to predict open pit mine failure runout', in PM Dight (ed.), SSIM 2023: Third International Slope Stability in Mining Conference, Australian Centre for Geomechanics, Perth, pp. 629-638, https://doi.org/10.36487/ACG_repo/2335_41



Abstract:
This paper focuses on the development of a framework implemented by Rio Tinto Iron Ore to systematically document 185 instances of slope failures in open pit mining operations located in the Pilbara region of Western Australia. With mining activities extending to deeper levels within intricate geological formations, often below the water table, the frequency and potential lethality of slope failures have escalated. While prevailing guidelines and industry standards recognise a Probability of Failure (PoF) of up to 30% for controlled benches in open pits, with no personnel at risk, the immediate attention following a fall of ground (FoG) is typically directed towards operational risk management and rehabilitation. Regrettably, the essential information pertaining to a FoG is frequently collected after the slope failure has undergone rehabilitation and operations have resumed, resulting in a delay in comprehending the underlying instability. This paper aims to rectify this issue by furnishing engineering personnel with a consistent and exhaustive dataset comprising FoG incidents. This dataset encompasses meticulous and comprehensive details including the circumstances surrounding each slope failure. The paper introduces novel empirical relationships enabling the estimation of the runout distance for slope failures in open pit iron ore mining. These relationships consider several factors including slope height and angle, rock mass conditions, geological setting, the failure mechanism and the volume of failed material. By integrating this information into geotechnical design and risk management, engineers can formulate runout predictions through failure back-analysis and calibration of PoF and material strength assumptions. The proposed data-driven approach aims to support geotechnical engineers and engineering geologists during both the design review and operational phases of mining projects. By adopting this framework, engineers can access a comprehensive dataset of FoG incidents, thereby facilitating calibrated geotechnical design and risk management practices. Ultimately, this strategy will enhance the safety and productivity of open pit mining operations.

Keywords: slope stability, slope failure, runout distance, fall of ground, reporting, geotechnical data

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