OZ Minerals uses open data and a $1 million incentive to unearth hidden treasure
The three month long journey to data-driven discovery on the Explorer Challenge concluded on Friday 31 May 2019, with over one thousand global participants from sixty-two countries digging through more than six terabytes of public and private exploration data from OZ Minerals’ Mount Woods tenement in northern South Australia.
In addition to a A$1 million prize pool, the winning models on the Explorer Challenge will be tested in real life, with the top targets scheduled to be drilled by the end of 2019 with the prospect of unearthing the next big Australian mineral deposit.
Economic mineral deposits have become increasingly difficult to find. Explorers seek new approaches to solve this problem and develop innovative processes and ways of working that can drive up the discovery rate, and in doing so, speed up the exploration lifecycle resulting in a more sustainable and efficient future for mineral exploration.
Modern mining company OZ Minerals partnered with energy and resources open innovation platform Unearthed to deliver this unique, online crowdsourcing competition, which involved the challenge and accompanying data being made available digitally to geologists, geoscientists and data scientists from around the world, who then competed to deliver the best solution.
Congratulations to all the prize winners:
1st Prize (A$500,000): Team Guru
2nd Prize (A$200,000): DeepSightX
3rd Prize (A$100,000): Cyency
Student Team Prize (A$50,000): deCODES
Genius Prize (A$25,000): Team OreFox
Insights Prize (A$25,000): Avant Data Solutions
Data Hound Prize (A$25,000): Team Phar Lap
Fusion Prize (A$25,000): SRK Consulting
Team SRK consists of qualified structural geologists across our offices in Perth, Melbourne, Toronto and Vancouver – one of these (Dr Antoine Caté, SRK Toronto) having branched into the development of applications of Machine Learning for the mining exploration sector as a Postdoc at the Université du Québec.
Approach: Our approach included the re-interpretation and/or value-add of the provided and available datasets followed by a multi-pronged and integrated targeting approach applying data-driven machine learning (based on a balanced random forest algorithm) and weights of evidence to guide a set of knowledge-driven mineral systems informed fuzzy inference solutions. This resulted in three highly-ranked IOCG targets and seven secondary targets.
'Winning the Fusion Prize is validation of a great collaborative effort by the global SRK team that we believe was rooted in solid geoscience, combined with cutting-edge machine learning and more traditional data science techniques. We have already had enquiries from interested clients and will be presenting some of our work from the Explorer Challenge at the Australasian Exploration Geoscience Conference (AEGC 2019) in Perth this September’. - Mark Rieuwers, Structural Geologist - SRK Consulting.
The submissions to the Explorer Challenge displayed an amazing range of analytical and geological approaches. From cutting edge machine learning to advanced physical modelling, the submissions represented thousands of hours of work developing and applying robust techniques applicable to the problem of target generation. Bringing data scientists and geologists together for this challenge has resulted in novel ways to apply modern data science techniques, such as machine learning, to geological problems in a meaningful and explainable way.
