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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Apr 04, 2022
1.04 GB
Publicly accessible
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Authors
Ahmmed, B. Stanford University
geothermalenergymachine learningartificial intelligenceaiexplorationmodelmodelingprocessed datatraining datatraining datasetremote sensinghidden geothermal resourcesresource detectiondiscoverydevelopmentresourceneural networkprediction

Utah FORGE: Triggered DAS Data from the April 2024 Mini-Circulation Test

May 01, 2026
Size unavailable
In progress
This dataset contains distributed acoustic sensing (DAS) data collected during the April 2024 mini-circulation test at the Utah FORGE site. Data were acquired from wells 16B(78)-32 and 58-32 during the mini-circulation period from April 23-28, 2024, following stimulation of the in...
Authors
Dyer, B. et al Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgeegsdistributed acoustic sensingdasmini-circulation testcirculation testsegyseg-y16b78-3258-32seismic datawell trajectoriesgeophysics