Operationalising remote data acquisition in block caving: a case study at Oyu Tolgoi

Authors: Kennett, R; Allan, M; Preller, D; Cronin, J Download Paper Open access courtesy of:

DOI https://doi.org/10.36487/ACG_repo/2645_34

Cite As:
Kennett, R, Allan, M, Preller, D & Cronin, J 2026, 'Operationalising remote data acquisition in block caving: a case study at Oyu Tolgoi', in A van As, D Cumming-Potvin & J Wesseloo (eds), Caving 2026: Proceedings of the Sixth International Conference on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 1-9, https://doi.org/10.36487/ACG_repo/2645_34



Abstract:
In the dynamic environment of high-production block cave mines, the interplay between geotechnical assurance and operational tempo is critical. The requirement for frequent, high-fidelity monitoring of cave propagation, drawpoint status and ground support integrity often conflicts with production demands, as manual inspections necessitate the stoppage of mining equipment and exposing personnel to hazards such as mud inrush or seismic events. This paper presents the results of a comprehensive remote data acquisition study conducted at the Oyu Tolgoi underground mine. The study systematically audited the site’s cave management plan, ground control management plan and trigger action response plans to evaluate the feasibility of transitioning from manual to robotic data collection. The analysis identified and characterised 126 distinct inspection and monitoring tasks currently performed by geotechnical, survey and production teams. A critical operational finding was that 95% of these mandatory tasks currently require production to cease to allow human access, creating significant ‘white space’ in the operational cycle. We outline the methodology used to map these tasks against the capabilities of current off-the-shelf mobile robotic platforms (quadrupedal and tracked). The case study details the selection process for deploying remote systems into the hostile mining environment to perform specific high-value tasks, including post-blast apex inspections and automated tunnel and drawpoint inspections. The study concludes that integrating ruggedised mobile robotics is not merely a safety initiative to remove personnel from hazardous areas; it is a production enabler. By allowing data acquisition to occur concurrently with mucking operations, the mine can achieve higher-resolution geotechnical datasets without compromising the extraction rate, effectively decoupling safety monitoring from production interruptions.

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