Stratum AI at Simberi JORC resource: key modelling takeaways for geologists
Reviewed by Joe Ashwell
First reported on International Mining – News
30 Second Briefing
Artificial intelligence models from Toronto-based Stratum AI are now underpinning the publicly reported JORC mineral resource estimate for St Barbara’s operating Simberi gold mine in Papua New Guinea, in what is claimed as one of the first such applications globally. Developed jointly with Perth-based St Barbara, the models were used directly in resource estimation rather than as a parallel or shadow study. For geologists and resource modellers, this signals growing regulator and owner confidence in AI-derived domaining and grade interpolation workflows within formal reporting frameworks.
Technical Brief
- For other mining projects, this case provides a precedent for AI outputs entering formal public reporting workflows.
Our Take
Simberi’s use of Stratum AI aligns with the rapid deployment of artificial intelligence flagged for IMARC in Sydney, where International Mining is also involved, signalling that AI-guided resource modelling is moving from pilot status into mainstream conference and project agendas.
With Stratum AI operating out of Toronto and Perth, the Simberi milestone reinforces the pattern seen across our AI-tagged coverage of solutions being developed in established mining tech hubs but validated on remote Asia–Pacific assets, which can accelerate acceptance by larger operators watching these test beds.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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