Integrating a Minerals Systems Approach with Machine Learning: A Case Study of ‘Modern Minerals Exploration’ in the Mt Woods Inlier – northern Gawler Craton, South Australia

There has been extensive exploration in the Mt Woods inlier in the northern Gawler Craton, South Australia since the 1960s, particularly for iron oxide-copper-gold (IOCG) mineralisation since the 1975 super giant Olympic Dam IOCG-U discovery by Western Mining Corporation ~150 km to the SE.

IOCG discoveries in the Gawler Craton have been largely made based on targeted discrete magnetic and/or gravity anomalies since the advent of regional geophysical datasets. Only one significant economic discovery has been made in the Mt Woods inlier – the Prominent Hill metasediment-hosted IOCG deposit in 2001 by Minotaur Resources, with no subsequent economic mineralisation encountered elsewhere in the inlier.

In an effort to accelerate the discovery of a new economic deposit, OZ Minerals opened up more than 2TB of their private geoscience data to external participants as part of the ‘Explorer Challenge’ competition in early 2019. Once registered, participants had 3 months to use the data provided, along with what was already in the public domain, to attempt to predict where the next mineral deposit in the Mt Woods inlier might be.

Integrating a minerals systems approach with machine learning (ML) has allowed the development of a series of conceptual models for targeting a range of deposit types and commodities. Exploration success based on this modern targeting approach will eventually lead to new suitable exploration strategies to discover the next generation of economic mineral deposits, particularly those concealed under cover.