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Robbie Rowe

SensOre

robbie.rowe@sensore.com.au

 

Abstract:

Use of AI with Geoscience Data around a Mine Site to Extend the Mine Prospectivity and Mine Life through Prediction

 

Adoption of Machine Learning (ML) and AI technologies by the mining industry has been steadily increasing since at least 2000, resulting in performance improvement and efficiency gains. Although application of the same technologies to geoscience, specifically mineral exploration, has lagged behind mining, engineering and mineral processing, there has been a growing interest ML and AI application to exploration. The reason for this increasing interest in quantitative, prediction based technology is the search for new ways of working to address declining discovery rates, diminishing mineral reserves and falling mining grades that have occurred over the last 50 years.

 

One of the challenges to wider uptake of ML and AI to geoscience for mineral exploration is the need to fuse rock property data sources associated with geoscience disciplines, namely geology, geophysics and geochemistry. The lessons from other successful ML and AI deployments are that the more uncorrelated data sets are available the better ML and AI can perform. Ingesting each rock property data source or layer onto a common architecture enables an ML and AI approach to identify specific signals or fingerprints in data which can then be used in a probabilistic prediction approach. These ‘Machine Augmented Exploration’ models can be developed at the required scale of application from regional greenfield, through brownfield at camp, to mine scale targeting. Discovery of additional reserves within the economic influence of a mine extends the operations Life of Mine, maximising the utilisation of processing infrastructure, benefiting all stakeholders and contributing to a more sustainable mining industry.

Bio:

Economic geoscientist with plus 30 years of experience in mineral targeting, exploration and mining.

Since 2018 Robbie has been working on the application and deployment of Machine Learning to mineral exploration. In late 2019 he commenced as founding COO with SensOre Ltd.

 

Prior to 2018 he provided strategic and technical advice to industry, research and government organisations associated with the mineral resources sector. During this time, Robbie assisted technology testing in the Deep Exploration Technologies Cooperative Research Centre and coordinated Amira’s UNCOVER industry Roadmap, launched in 2018. The Roadmap focused on developing solutions to improve mineral discovery performance, specifically in deeper or covered terranes.

 

Robbie is former VP Exploration - Australia Asia Pacific Africa region for Barrick Gold Corporation, where he spent 15 years in executive and technical roles in gold and copper exploration, large resource development projects and mining operations.

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