Fitzroy Minerals Inc. has completed an integrated seismic and machine-learning targeting study at its Buen Retiro Copper Project in Copiapo, Chile, producing a ranked portfolio of nine completely new and untested exploration targets. The study, conducted with Australian technology firm Fleet Space Technologies, combines 3D Ambient Noise Tomography (ANT) data with prior geophysical surveys, geological models, and approximately 24,400 copper assays from 140 drill holes. The significance of this announcement lies in the project's geological setting: Buen Retiro is believed to share characteristics with major iron oxide copper-gold (IOCG) deposits such as Candelaria and Mantoverde, yet its sulphide potential has barely been tested due to extensive alluvial gravel cover that complicates surface mapping.
The new machine-learning model identifies nine priority domains where subsurface characteristics closely resemble the signature of known copper mineralization at Buen Retiro. These targets are all within 400 metres of surface and focus on gravel-covered geology, excluding previously mined ground or areas within 200 metres of existing drill holes. The methodology involved predicting zones where copper grades above a 0.5% threshold might occur within 25-metre blocks, then refining the list by removing mined-out areas, mapped gravel cover, and proximity to existing drilling. The remaining blocks were grouped into nine geographic domains, each representing a cluster of blocks with a similar predicted response and interpreted to be geologically significant.
Fitzroy has already started a 5,000-metre drilling program using diamond and reverse circulation rigs to test the new targets. As drill logs and assay results come in, the company and Fleet will update the machine-learning model, so each new hole serves three purposes: testing a specific target, improving or validating the model, and informing the next drilling decision. This iterative approach could make the targeting system a cost-effective discovery tool, creating value for shareholders if successful.
Merlin Marr-Johnson, President and CEO of Fitzroy, commented: “We believe Buen Retiro shares many of the geological characteristics of the major iron oxide copper-gold (IOCG) 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.”
The targeting study follows an earlier regional ANT survey commissioned by Fitzroy in early 2026, which mapped the project's deeper geology beyond the depths of current drilling. A higher-resolution infill survey then improved understanding of the faults and fractures interpreted to control permeability corridors and associated mineralization. The machine-learning phase converted this geological and geophysical picture into ranked exploration opportunities. The company noted that the targets are conceptual and have not yet been tested by drilling; they do not confirm the presence, grade, size or continuity of mineralization. The reliability of the model depends on the quality and coverage of the underlying data and tends to decrease with distance from existing drill holes and with depth. For this reason, the targets are intended to be used alongside conventional geological interpretation, not in place of it.
For a detailed summary of the four datasets and copper assay results used in the new machine-learning targeting, Click Here to see Table 1 - Summary of the 4 datasets and copper assay results used in the new ML targeting. The announcement was first distributed via NEWMEDIAWIRE.
