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    BHP’s AI copper push: leach reagent optimisation insights for process engineers

    June 3, 2026|

    Reviewed by Tom Sullivan

    BHP’s AI copper push: leach reagent optimisation insights for process engineers

    First reported on Australian Mining

    30 Second Briefing

    BHP is using artificial intelligence with Microsoft and Prescience Insilico to screen more than 500,000 candidate molecules that could accelerate and improve copper leaching from existing ore. The project applies advanced computing to predict which reagents may enhance recovery rates in heap and dump leach circuits, rather than relying solely on conventional lab trial-and-error. For geometallurgists and process engineers, this signals a push to optimise reagent chemistry on legacy ore bodies before committing capital to new copper projects.

    Technical Brief

    • Any shortlisted reagents still require conventional column and bottle-roll testing to validate AI predictions under site-specific conditions.

    Our Take

    BHP’s use of AI for copper in Australia sits alongside its push to keep Escondida and Spence in Chile on 100% renewable power, suggesting digital optimisation and decarbonised energy are being advanced in parallel on its core copper portfolio rather than as separate initiatives.

    In our database, copper appears frequently in BHP-related decarbonisation disputes in the Pilbara and at Olympic Dam, so AI-driven productivity gains may be used internally to justify or sequence large capital spends on renewables and critical-mineral expansions.

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    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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