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Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas.
This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.
This dataset compiles heat flow and temperature gradient data from over 44,000 wells across the United States, along with more than 6,000 related geothermal exploration resources. Originally assembled prior to 2014 for the now-retired National Geothermal Data System (NGDS), the co...
To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of...
This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. Th...
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model:
brady_som_output.gri, brady_som_output.grd, brady_som_output.*
desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rock...
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 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...
This data is a compilation of well observations from the Southern Methodist University (SMU) and Association of American State Geologists (AASG), location of identified low temperature geothermal systems from United States Geological Survey (USGS), and low temperature geothermal w...
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
This submission contains information used to compute the risk factors for the GPFA-AB project. The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking ...
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