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New Frontiers - Mining the data for our next copper discovery

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Unearthed Industry Lead - Crowdsourcing, Holly Bridgwater's presentation from the Copper to the World conference on 18 June 2019 about outcomes of the OZ Minerals Explorer Challenge.

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New Frontiers - Mining the data for our next copper discovery

  1. 1. New frontiers Mining the data for our next copper discovery Copper the the World, June 18th 2019 Holly Bridgwater, Industry Lead
  2. 2. We know we need to increase our discovery rate. How do we increase our confidence in the targets we generate? How do we make the right bet?
  3. 3. Geologists love bias! Targets Interpretation Data Deposit Models ‘Geology’ +Uncertainty + Bias Data Science!!!
  4. 4. But we could do this…. Just not by ourselves
  5. 5. • The Mount Woods Project is an area ~ 5000km2 near the Prominent Hill Mine in South Australia • Participants in the competition had access to the OZ Minerals private exploration database of >5TB • The challenge was to use the data to predict the location of economic mineralisation of any kind, not just another Prominent Hill Crowdsourcing Exploration at Mount Woods
  6. 6. What was in the data? • 621 datasets • 678 drillholes with 115,000 assay results • 2.7TB of geophysics data in 62 datasets • 60 prospect datasets • Magnetics, gravity, seismic, radiometrics, IP, EM and MT • Petrology • Geological maps and reports Crowdsourcing Exploration at Mount Woods
  7. 7. The Explorer Challenge • >5TB of data instantly accessible online around the world • >1000 participants • >10,000 data downloads • >60 countries • Geologists, data scientists, startups, students, consultants, universities, research organisations
  8. 8. The Crowd and Exploration Open and accessible data creates conditions for: • Multiple results to be developed in parallel • Independent approaches – no group think, no bias! • Consensus = Confidence – statistically relevant consensus due to independence and diversity • Speed, new knowledge, new workflows and << cost are an additional bonus.
  9. 9. We did this!
  10. 10. Explorer Challenge Outcomes • Multiple approaches never before imagined internally • Applications of robust leading edge machine learning, data science and geological techniques • New ways of extracting data, fusing and analysing multiple data layers • >400 targets – robust new targets generated, confidence increased in known targets
  11. 11. Data Science and Exploration: What did we learn? • Multidisciplinary teams rule! • DS enables state, national and global datasets to be trained on and pulled into local problems, a great way to reduce bias • Explainable/interpretable machine learning is key for it to be added to the geologists toolkit • Geoscience data is not friendly for data scientists
  12. 12. The Startup Ecosystem in Exploration Data Science improve-holly-bridgwater/
  13. 13. Key takeaways • CONSENSUS = CONFIDENCE, geology is complex: search for consensus not the best • Open, accessible data creates an environment where you can achieve consensus. • Data scientists + geologists = success! • Internal – 1yr, 2-3 models max • Crowd – 3 months, 40 models
  14. 14. Thank you Holly Bridgwater