5 datasets found
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Federal
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Department of Energy —
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells... -
Federal
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs
Department of Energy —
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to... -
Federal
EGS Collab Experiment 1: Accelerometer orientations
Department of Energy —
Document describing the methodology used to determine the accelerometers' three-component orientations at the first EGS Collab testbed using Continuous Active-Source... -
Federal
Python Codebase and Jupyter Notebooks - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Department of Energy —
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal... -
Federal
3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA
Department of Energy —
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of...
5 datasets found