Slope monitoring and data visualisation state-of-the-art – advancing to Rio Tinto Iron Ore’s Mine of the Future™

Authors: de Graaf, PJH; Wessels, SDN Download Paper

DOI https://doi.org/10.36487/ACG_rep/1308_55_deGraaf

Cite As:
de Graaf, PJH & Wessels, SDN 2013, 'Slope monitoring and data visualisation state-of-the-art – advancing to Rio Tinto Iron Ore’s Mine of the Future™', in PM Dight (ed.), Slope Stability 2013: Proceedings of the 2013 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 803-814, https://doi.org/10.36487/ACG_rep/1308_55_deGraaf



Abstract:
Rio Tinto Iron Ore’s (RTIO) Western Australian mine operations comprises 14 mines with a centralised ‘Mission Control’ Operations Centre (OC) in Perth, and currently delivers 237 Mt/a ore from over 120 individual open pits. Operational challenges in terms of implementation of effective slope monitoring systems with appropriate visibility of system health and alarm notifications needed to be addressed. The geotechnical, management and support teams are site and Perth based, and all require access to geoscience monitoring data. Historically, each site had an independent monitoring and alarming systems. Transparency of monitoring data, health checks and alarming capabilities were limited. The lack of a system to display temporal geotechnical (slope performance), and hydrogeological monitoring data, with 24/7 alarm and system health status had been identified as a ‘gap’ following a previous slope instability incident at one of the Pilbara Operations. At project inception, the need for a visualisation and management tool which had a multidisciplinary focus and integrating georeferenced geoscience monitoring data with physical models in near real time, was identified. Consequently the Geoscience Monitoring Data System (GMDS) was developed to address three main requirements: This tool is in alignment with Rio Tinto’s Mine of the Future and RTIO’s Operations Centre vision by using technology to reduce costs, increase efficiency and improve health, safety and environmental performance. It provides the functionality to manage diverse instrumentation data in a consistent, standardised approach to support RTIO’s geographically spread expansion plans.

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