Geothermal data streams come from many sources with varying degrees of fidelity. For example, direct borehole temperatures are often considered high fidelity measurements and provide hard constraints on hydrothermal reservoir models. Geophysical surveys, such as seismic and MT, are considered to be of lower fidelity but often have higher spatial coverage providing general large scale constraints. Regional geological and gravity surveys often provide locations of faults and pyroclastic rock formations. Geochemical data such as dissolved silica and Na-Ca-K provide estimates of maximum reservoir temperatures. Risk reduction in geothermal exploration and development requires a synthesis of these data streams. We are developing a framework that synthesizes these data streams by joint inversion of hydrothermal, geochemical, and geophysical models. Functionality is provided for handling non-collocated meshes to facilitate joint inversion. Prospectivity is defined as the amount that uncertain model parameters can deviate from nominal or best fit values and the models still produce simulations that meet geothermal production criteria. Larger parameter deviations indicate greater robustness in geothermal prospectivity. Results are presented as 3D prospectivity maps using the open-source visualization code ParaView allowing interactive interpretation of the results.

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