Iron oxide copper–gold potential of Australia using a hybrid data- and knowledge-driven approach and its implications for the formation of IOCG mineral systems

• First hybrid national mineral potential model of Australia for IOCG mineral systems. • New areas of high prospectivity in under-explored regions of Australia are highlighted. • The model successfully reduces the exploration search space by 91.7% • Criteria related to energy sources show the strongest spatial associations. • Criteria related to sources of metals, fluids and ligands show the weakest spatial associations. Iron oxide copper–gold (IOCG) deposits are a globally significant source of copper and gold, and can also contain critical minerals required for the transition to a low-carbon economy. Given their economic and strategic importance, a national-scale assessment of the mineral potential for IOCG mineral systems in Australia has been undertaken using a hybrid data- and knowledge-driven approach. For the model, 149 mappable criteria were tested using the Kolmogorov-Smirnov test, and 14 criteria were identified to show a strong relationship with known IOCG mineralization and were retained for the model. The mineral potential model successfully predicts the location of 91.7% of known IOCG deposits and occurrences in 8.3% of the area, reducing the exploration search space by 91.7%. Based on the statistical analysis, criteria related to energy sources are the most important, followed by ore depositional gradients, fluid pathways and architecture, and sources of metals, fluids and ligands. The new national-scale model highlights several new areas of elevated prospectivity for IOCG mineral systems in under-explored regions of Australia. Based on their geological evolution, IOCG mineralization is probable in the Delamerian Orogeny, the Lamboo Province and the Tanami Orogen, possible in the Western Gawler Craton, the Hooper Province and the Musgrave Province, and unlikely in the Edmund Basin, Pilbara region and the Yilgarn Craton. This study highlights how precompetitive geoscience data can be evaluated and utilized within a geologically and statistically robust framework to produce mineral potential models with strong predictive performance.