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Geothermal Energy

Science – Society – Technology

Fig. 2 | Geothermal Energy

Fig. 2

From: Machine learning to identify geologic factors associated with production in geothermal fields: a case-study using 3D geologic data, Brady geothermal field, Nevada

Fig. 2

The 14 variables used in this study along one of the Brady production wells. These are the input data for the NMFk algorithm. Cool colors correspond to low values and warm colors correspond to high values for each variable. For the binary variables (fault and goodlith), red corresponds to a value of one (a fault or the producing lithology), purple corresponds to a value of zero. For faultnear and contactnear warm colors indicate nearness to faults or contacts

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