AUTHORED BY VERACIO’S GLEN BRABHAM: MULTIMODAL INTEGRATION OF XRF GEOCHEMISTRY AND CORE IMAGERY FOR SCALABLE, AUTOMATED LITHOLOGICAL LOGGING WAS PRESENTED AT THE SEG 2026 CONFERENCE IN SALT LAKE CITY.

Geological logging underpins exploration and resource modelling, but it remains subjective and time-intensive. VERACIO’s Glen Brabham explored how combining XRF geochemistry with high-resolution core imagery can improve the consistency, resolution and scalability of lithological interpretation.

The study compared four machine learning approaches to automated lithology classification, using XRF geochemistry, high-resolution core imagery, and models that integrate both datasets.

The results showed that combining geochemistry and imagery consistently improved classification performance compared with using either dataset independently, demonstrating the value of bringing multiple geological datasets together.

The outcome is a scalable approach to more consistent geological interpretation, with applications across exploration workflows, domain definition and resource modelling.

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