The Dixie Valley Geothermal Wellfield (DVGW), a Basin and Range type system in central Nevada USA, is used as an exploration case history for Enhanced Geothermal Systems (EGS). It encompasses an area of approximately 170 km(2). The wellfield produces 67 MW of geothermal power and it contains a number of high temperature non-productive wells. This wellfield was chosen as the calibration site for the development of an EGS exploration methodology due to its extensive body of geoscience data and information on the geothermal system and most importantly, well results in the public domain. This existing body of data (ca. 2011) was in part re-interpreted to produce a baseline conceptual model in terms of a number of serial cross-sections for the available data sets: geology, seismic reflection, resistivity, temperature, gravity-magnetic, and p-wave velocity (Vp). The exploration methodology was calibrated against available geothermal well results. Basect on a comprehensive review of all available geoscience and well data, EGS favorability maps were generated, from +1 km above sea level (asl) to -4 km asl at 0.5 km intervals, for the three key EGS parameters of interest: rock type, temperature, and stress. Complimentary trust ("confidence-in-the-data-used") maps were also created at the same scale to, among other things, indicate where additional data may be required. Quantitative geostatistical analysis of the geoscience data was conducted, among other factors, to address the question of whether the baseline geoscience data could be used to predict EGS favorability without the advantage of existing well temperature data. Classification and Regression Tree (CART) was one of a number of geostatistical methods applied to the baseline geoscience data and it provided the most promising results. In CART, the response variable (RV) is predicted while using explanatory variables (EVs). The geoscience parameters (EVs) considered in the CART analysis included temperature, Vp, resistivity from magnetotellurics, Coulomb Stress Change (CSC), dilatational strain (from CSC modeling), vertical stress, lithology based on geologic analysis, lithology based on gravity magnetic modeling (G-M lithology) and the presence or absence of a fault. Temperature increases with depth in the DVGW. Vertical stress also increases with depth and it was deemed as a redundant EV. As such, a CART sensitivity analysis was applied to the baseline data set with and without vertical stress being considered as an EV to determine the effect of removing vertical stress and to evaluate with subsets of EVs that could be predictive of key EGS parameters. R-2-values ranging from 0.611 to 0.841 were obtained for the RVs: temperature, lithology, productive vs. non-productive hydrothermal cells and expected EGS favorable cells (the response variables) using both cross-section and well data and not considering vertical stress. However, these CART results were not used in the generation of the favorability maps because this is the first analysis of its kind that the authors are aware of and more testing at other sites needs to be done; the raw total baseline data set described above was considered the most appropriate for this study. (C) 2016 Elsevier Ltd. All rights reserved.