Soma Gold TOMRA sorter upgrade: pre-concentration impacts for mine planners
Reviewed by Tom Sullivan

First reported on International Mining – News
30 Second Briefing
Soma Gold Corp is advancing a mineralised material upgrading strategy at its El Bagre underground operation in Colombia using TOMRA Mining’s sensor-based sorter that combines XRT technology with OBTAIN™ and CONTAIN™ AI-based image processing. Positive test work at TOMRA’s Test Center in Germany showed sufficient ore–waste discrimination to justify implementation, targeting higher feed grades and reduced haulage and processing of low-value material. For mine planners and process engineers, the move signals a shift towards pre-concentration at the mine gate, with potential impacts on cut-off grade, stope design and plant throughput.
Technical Brief
- TOMRA’s sorter uses X-ray transmission to distinguish density contrasts between gold-bearing quartz veins and waste.
- OBTAIN™ processes full-pixel XRT data to refine particle-by-particle ore–waste classification in real time.
- CONTAIN™ applies AI-based image analysis on conveyor-belt images to adapt sorting rules as ore characteristics vary.
Our Take
TOMRA Mining’s recent work on turning waste rock and tailings into saleable aggregate, highlighted in the 10 February 2026 piece, suggests that Soma Gold’s El Bagre deployment could later be extended beyond run-of-mine upgrading into reprocessing historic dumps in Colombia.
For a narrow-vein underground district like El Bagre in Colombia, sensor-based sorting typically has the biggest impact where haulage and processing costs are high, implying Soma Gold is likely targeting both unit cost reductions and a potential increase in cut-off flexibility rather than just marginal grade uplift.
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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