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This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification.
In this study, a machine-learning-assiste...
To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group a consortium of several national labs and academic institutions has tabulated time-depe...
Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the n...
This dataset accompanies the paper "Geothermal district energy systems coupled with seasonal underground thermal energy storage: a U.S. techno-economic screening by climate and geology." It contains the data and scripts required to reproduce the study's results across ten U.S. cit...
These resources describe the 3D geophysical inversion modeling of gravity data at the FORGE site near Milford, Utah. FORGE is the Frontier Observatory for Research in Geothermal Energy and the site in Utah has been selected by the U.S. Dept. of Energy for a 5-year R&D program to t...
An integrated open mineral spectral library designed to enhance the utility and precision of mineral spectral data for geothermal exploration, developed from a reliable and comprehensive digital dataset for seamless sharing by integrating field data, the USGS spectral library, and...
This dataset contains example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) framework, specifically for the fictional Kahunanui (KHN) geothermal power plant. The dataset includes synthetic time series data, confi...
Geothermal growth is limited by a lack of geographically dispersed high-temperature thermal resources and high initial upfront investment in characterization and well construction. This project intended to address the challenges of energy supply intermittency and enhance grid resi...
Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a deep-circulation (amagmatic) meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich...
The computed tomography (CT) facilities at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize core of the Tuscarora Sandstone from a vertical well in Preston County WV, the Preston-119 from a depth of 7,165 to 7,438 ft. The pr...
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the...
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