We evaluated a method for cooperatively inverting multiple electromagnetic (EM) data sets with bound constraints to produce a consistent 3D resistivity model with improved resolution. Field data from the Antonio gold deposit in Peru and synthetic data were used to demonstrate this technique. We first separately inverted field airborne time-domain EM (AEM), controlled-source audio-frequency magnetotellurics (CSAMT), and direct current resistivity measurements. Each individual inversion recovered a resistor related to gold-hosted silica alteration within a relatively conductive background. The outline of the resistor in each inversion was in reasonable agreement with the mapped extent of known near-surface silica alteration. Variations between resistor recoveries in each 3D inversion model motivated a subsequent cooperative method, in which AEM data were inverted sequentially with a combined CSAMT and DC data set. This cooperative approach was first applied to a synthetic inversion over an Antonio-like simulated resistivity model, and the inversion result was both qualitatively and quantitatively closer to the true synthetic model compared to individual inversions. Using the same cooperative method, field data were inverted to produce a model that defined the target resistor while agreeing with all data sets. To test the benefit of borehole constraints, synthetic boreholes were added to the inversion as upper and lower bounds at locations of existing boreholes. The ensuing cooperative constrained synthetic inversion model had the closest match to the true simulated resistivity distribution. Bound constraints from field boreholes were then calculated by a regression relationship among the total sulfur content, alteration type, and resistivity measurements from rock samples and incorporated into the inversion. The resulting cooperative constrained field inversion model clearly imaged the resistive silica zone, extended the area of interpreted alteration, and also highlighted conductive zones within the resistive region potentially linked to sulfide and gold mineralization.

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