Interest in the application of Artificial Intelligence (AI) and how it can shape the future of mineral exploration was put in the spotlight recently by KoBold’s Mingomba project in Zambia, where the technology was utilised in re-interpreting the copper deposit. The success of an AI-based evaluation of a mineral prospect is dependent on the quality of the geological and geochemical data that is ingested into the platform.
At the deposit scale, the role of the geologist with field experience remains irreplaceable. This ranges from mapping, corelogging and sampling to first rough drafts of the lithologies. Their boots-on-the-ground knowledge aid in delineating exploration targets and evaluating the sample material being collected. This includes ensuring that all sampling is done according to the industry best practice QA/QC and meeting the requirements of the selected mineral reporting code (i.e., an important aspect towards quality data).
AI offers the potential to combine, and more time and cost effectively generate additional targets at the prospect scale, by considering the data from the various disciplines, such as geology, structural geology, remote sensing, geochemistry, geophysics, geotechnical and ultimately modelling outputs. The current subject matter experts need to emphasize the importance of evaluating data quality, in terms of validity, accuracy and relevance, that is used as input data and the critical interpretation of the results produced by the AI platform. The models being produced by the AI platform need to be considered if it is realistic, based on the geological setting and the recognised mineralisation processes.
The development of effective AI systems cannot be done in isolation and requires collaboration in the industry. However, when practitioners are sharing or presenting data, workflows, etc, they need to ensure that any sensitive and propriety company and/or project information used in developing better tools or model results remains confidential and therefore, would need to be removed before entering the public domain.
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This thought leadership piece is in partnership with the Mining Journal's Future of Exploration.
