Fitzroy Minerals Inc. has announced the results of an integrated seismic and machine-learning targeting study at its Buen Retiro Copper Project near Copiapo, Chile, completed with Australian technology firm Fleet Space Technologies. The study generated a ranked portfolio of nine previously untested exploration targets within 400 metres of surface, marking a significant shift in how the company plans to pursue the project's sulphide potential.
The targets were defined by combining 3D Ambient Noise Tomography data with prior geophysical surveys, geological models, and approximately 24,400 copper assays from 140 drill holes. Fleet's regional and infill ANT surveys mapped the project's deeper geology well beyond the depths of current drilling, using natural seismic noise to build a 3D picture of the rock beneath the surface. Extensive alluvial gravel cover in the area had made surface geological mapping and target generation much more difficult, and the new technique provides a 3D framework to trace known mineralized trends and identify new opportunities, including toward the 100%-owned Sierra Fritis properties to the east.
The targeting method involved four steps: prediction of zones where copper mineralization above a 0.5% Cu threshold might be located, refinement to exclude mined-out areas and ground within 200 metres of existing drill holes, grouping of remaining blocks into nine geographic domains, and drill planning. Fitzroy has started a 5,000-metre drilling program using diamond and reverse circulation rigs. As drill logs and assay results come in, the company and Fleet will update the ML model, so each new hole serves to test a specific target, improve or validate the model, and inform the next drilling decision. The full summary of the four datasets and copper assay results used in the new ML targeting is available in Table 1.
Merlin Marr-Johnson, President and CEO of Fitzroy, said the company believes Buen Retiro shares many geological characteristics of the major iron oxide copper-gold deposits at Candelaria and Mantoverde, yet the sulphide potential of the wider property has barely been tested. To date, the oxide copper mineralisation and its potential to support a low-capital-intensity, near-term production operation have been the focus. "Now, however, we have a tool with which to test the exploration optionality of this large IOCG system in one of Chile's most prolific copper-producing regions," he said. "By combining advanced 3D subsurface imaging with machine learning and our extensive drilling database, we can now identify and prioritise blind exploration targets beneath the gravel cover."
The news matters because it demonstrates how machine learning and seismic imaging are being deployed to reduce the cost and risk of mineral exploration at a time when global demand for copper is rising. If the ML targeting proves successful, it could serve as a cost-effective discovery tool for Fitzroy, creating value for shareholders and offering a template for other explorers facing similar challenges of concealed geology. The targets are conceptual and have not yet been tested by drilling, and the company cautions that they do not confirm the presence, grade, size or continuity of mineralization.
Fitzroy Minerals is focused on exploring and developing copper assets with substantial upside potential in Chile, with its two lead properties being the Buen Retiro Copper Project and the Caballos Copper Project in Valparaiso. The announcement was distributed via NEWMEDIAWIRE.
