The Basil Cu/Co deposit comprises a 26.5 Mt Inferred Resource of copper and cobalt, grading 0.57per cent Cu and 0.05 per cent Co. It lies in the Harts Range, Central Australia, within the Riddock Amphibolite of the Irindina Province. Analysis of drilling within the mineralised zone of the deposit determined a spatial association between pyrrhotite with high magnetic susceptibility and chalcopyrite, following a strong magnetic trend as determined from airborne geophysics. A study was commissioned to examine if geophysical inversion could predict the distribution of sulfide mineralisation based on pyrrhotite from drill hole intersections, as well as predicting further mineralisation at depth or in the vicinity of the deposit. Petrophysical and geostatistical analysis of drilling susceptibility and mineralisation provided a basis of property distribution inside the model. This was followed by 3D geological modelling of mineralisation based on domain kriging of drill hole susceptibility sensitivity testing of signal to source depth, and distribution was performed using 3D forward modelling. Stochastic inversion generated alternative 3D geological models, which were tested for behaviour and adherence to observed drilling data and geostatistical limitations using GeoModeller software. Predicted mineralisation distribution was compared with conventional geostatistical modelling and found to be in agreement in planar behaviour but exhibiting possibly isoclinally folded trends, with reliability increasing closer to the surface. Predictions of mineralisation at greater depth and beneath weaker anomalies were more diffuse due to small model cell size having limited influence on the signal at depth.The Blackbush uranium deposit comprises a 64.5 Mt Inferred Resource, grading 230 ppm U in the Pirie Basin south of Whyalla, South Australia. It directly overlies the radiogenic Samphire Granite and is considered a tertiary unconformity deposit. Sensitivity modelling was performed using high-resolution ground gravity to see if a deposit signature could be detected using gravity. This required 3D implicit modelling of the geology and mineralisation from drill hole data and characterisation of an associated physical property model using domain kriging in GeoModeller. Density models relied on exploiting an observed relationship between logged density and measured uranium oxide percentage. The residual gravity response of the background geology model identified the location of the uranium deposit. Stochastic inversion of the litho/property 3D model has refined the known distribution of uranium from drilling and provided structural insights into the deposit.These projects have become excellent case studies for exploiting the relationship between mineralisation and potential fields and for testing the applicability of using domain kriging of properties determined from drilling to build robust 3D geological models for stochastic geophysical inversion, leading to robust methods for exploration targeting and mineral deposit prediction.CITATION:Zengerer, M, 2014. Use of geostatistically-constrained potential field inversion and downhole drilling to predict distribution of sulfide and uranium mineralisation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 281-290 (The Australasian Institute of Mining and Metallurgy: Melbourne).