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Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
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...
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
This is a presentation on Machine Learning and Seismology for Real-Time Decision-Making in Stimulation by the University of Utah, presented by Dr. No'am Dvory. The project is developing real-time seismic monitoring, machine-learning, and geomechanical risk assessment tools to supp...
This dataset provides Python scripts supporting both subsurface and surface geothermal exploration AI models developed for the project "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning." It includes two main components: (1) scripts fo...
This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, disc...
This is a presentation on Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics (Global Technology Connection), presented by Dr. Jesse Williams. The project is developing machine-learning and physics-informed models to impro...
This is a presentation on Real-Time Robust Adaptive Traffic Light System and Reservoir Engineering with Machine-Learning-Based Seismicity Forecasting and Data-Driven Ground Motion Prediction (RT Forecast) by Lawrence Berkeley National Laboratory, presented by Dr. Nori Nakata. The ...
Comprehensive catalogue of drill-hole data in spreadsheet, shapefile, and Geosoft database formats. Includes XYZ locations of well heads, year drilled, type of well, operator, total depths, well path data (deviations), lithology logs, and temperature data. Plus, 13 cross-sections...
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
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 submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project.
A submission linking the full GitHub repository for our machine learning Jupyter Notebooks...
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...
This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid...
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...
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant...
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