Search GDR Data
Showing results 1 - 25 of 57.
Show
results per page.
Order by:
Available Now:
Topic
Technologies
Demonstration Sites
Data Type
This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while re...
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
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...
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 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...
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...
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...
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...
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
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 contains a final technical report and closeout presentation recording summarizing the results from Utah FORGE Project 5-2557 on the role of fluid pressure and temperature in fracture mechanics and coupled thermo-hydro-mechanical-chemical (THMC) processes relevant to enhanced ...
This submission contains the final technical report and closeout presentation for Utah FORGE Project 5-2419, which investigates the coupled evolution of permeability and induced seismicity in enhanced geothermal systems using laboratory experiments, field observations, and nonline...
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...
This submission houses the companion code for the manuscript by Zhengfa Bi (Lawrence Berkeley National Laboratory) and Nori Nakata (Lawrence Berkeley National Laboratory; MIT). Both the companion code and manuscript are included in the resources section of this submission.
Fluid ...
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 collection of documented state and local ordinances governing geothermal heat pumps (GHPs), ground-source heat pumps, and related geothermal exchange wells and loop systems throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance...
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 further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
This is a collection of documented state and local ordinances governing utility-scale geothermal electricity projects throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, wh...
This catalog contains microseismic event locations recorded during the April 2024 stimulation at the Utah FORGE site. Events were detected and located using a phase-picking workflow that integrates downhole geophones (wells 56 and 78B) and downhole DAS (well 16B). P and S-wave arr...
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...
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
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...
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 is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University, presented by Distinguished Professor of Physics & Astronomy, Laura J. Pyrak...
These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
Google Map