Soma Gold advances mineralised material upgrade plan with TOMRA sensor-based sorter
Soma Gold Corp is advancing its mineralised material upgrading strategy at its El Bagre operation in Colombia through the implementation of TOMRA Mining’s sensor-based sorting technology, combining XRT technology with advanced artificial intelligence through OBTAIN and CONTAIN
, TOMRA says.
Following positive test work results carried out at the TOMRA Test Center in Germany, the company is moving forward with the installation of a COM Tertiary XRT 1200 sorter to improve process efficiency and maximise the value of its mineralised material.
A gold mining company focused on exploration, development and production in Colombia, Soma’s operations are centred in the Antioquia region, where the company is focused on optimising performance across its assets while maintaining strong operational efficiency and resource utilisation.
At its El Bagre operation, Soma processes gold-bearing material from both its own mines and third-party sources, requiring a flexible and efficient approach to handling varying mineralised material types and grades.
Like many gold operations, Soma faces the ongoing challenge of managing variable mineralised material characteristics while maintaining stable and efficient plant performance. A key priority is to reduce the amount of non-valuable material entering the processing circuit, particularly in energy-intensive stages such as crushing and grinding.
By removing waste material early in the process, the company aims to improve feed consistency, optimise downstream capacity, and reduce unnecessary wear and energy consumption.
Mark Bren, VP Operations at Soma (pictured below), said: “The test work confirmed that sensor-based sorting can play a key role in how we manage our mineralised material more efficiently. TOMRA demonstrated more consistent and reliable performance results under modelled plant conditions in our test work. By removing waste early in the process and concentrating the valuable material stream, we see clear potential to improve overall plant performance.”
At the core of the solution is TOMRA Mining’s X-ray Transmission (XRT) technology, which enables the differentiation of material based on its atomic density, allowing precise separation of mineralised material and non-valuable material. The system deployed at Soma combines dual-energy XRT sensing with advanced artificial intelligence algorithms to achieve highly accurate particle classification.
TOMRA’s latest innovations, OBTAIN and CONTAIN, play a key role in this capability, TOMRA says. OBTAIN introduces deep learning-based particle classification, enabling high-precision sorting at the individual particle level even at high throughput, ensuring consistent performance regardless of belt occupancy. CONTAIN, designed for complex inclusion-type material, uses advanced neural networks to detect valuable mineralisation that may be embedded within host rock and difficult to identify using conventional methods.
Bren added: “For us, the value lies not only in upgrading the material, but also in improving how the entire plant operates. If we can reject non-valuable material earlier, we can optimise downstream capacity and process the mineralised material more effectively.”
To evaluate the application of this technology, Soma conducted a benchmark test program at TOMRA’s Test Center, using representative material from its Colombian operations. The results demonstrated a clear upgrade of the mineralised material, providing strong validation of the technology, TOMRA says.
The test program evaluated material across different size ranges and mineralised material types, confirming the robustness of the system under varying feed conditions. Particular attention was given to performance in challenging scenarios, including small particle sizes and high belt occupancy, where the system demonstrated precise detection and reliable sorting results.
Bren explains: “What stood out was not only the level of upgrade achieved, but also the consistency of the results across different material types and size fractions. That gave us confidence to move forward with implementation.” Bren adds.
Fernando Romero, TOMRA Mining, said: “The test work further demonstrated how sensor-based sorting can efficiently separate lower-value material from mineralised material streams, enabling a more controlled and optimized processing approach.”
A key differentiating factor observed during testing was the ability of the sorter to maintain high precision even under demanding operating conditions. The system showed strong performance across both coarse and fine particle size ranges, as well as in dense material flows.
The integration of TOMRA’s high-speed TS100 ejection module also enables a significant reduction in compressed air consumption – up to 70% – while maintaining accurate and reliable separation. This contributes not only to operational efficiency but also to lower operating costs.
Following these results, Soma moved forward with the next phase of the project, placing an order for a COM Tertiary XRT 1200 sorter to be integrated directly into its main processing flowsheet, improving material handling conditions and overall plant efficiency.
The integration of the sorter into the continuous process enables more efficient material handling and improves overall plant performance. By operating as part of the main processing flowsheet, the system contributes to optimized material flow and enhanced process stability, according to TOMRA.
The project is being developed in close collaboration with DISMET, TOMRA’s local integrator, supporting the design and implementation of a solution tailored to the specific requirements of the El Bagre operation.
One of the key advantages of TOMRA’s sensor-based sorting solutions is the ability to simultaneously improve process control and material value. By removing non-valuable material early, operations can better manage the volume and consistency of feed entering the plant, while increasing the value of the processed stream.
“By rejecting waste early, you contain variability and unnecessary processing load, while obtaining a higher-value material stream. This has a direct impact on how efficiently the plant can operate,” Romero added.
Through the combination of TOMRA’s XRT sensing, deep learning and precise ejection technology, TOMRA enables mining operations to stabilise processing conditions, reduce unnecessary throughput and unlock value from material that may otherwise be considered marginal.
As Soma progresses toward full implementation at El Bagre, sensor-based sorting is expected to become an integral part of its operational strategy, TOMRA says. By combining validated test work with advanced XRT and AI-driven technologies, the company is positioning itself to further enhance performance and efficiency across its Colombian operations.
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