Search GDR Data
Showing results 1 - 25 of 38.
Show
results per page.
Order by:
Available Now:
Topic
Technologies
Demonstration Sites
Data Type
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 ...
This GDR submission is an interim technical report and raw data files from the first year of testing on functionalized nanoparticles for rare earth element extraction from geothermal fluids. The report contains Rare Earth Element uptake results (percent removal, mg Rare Earth Ele...
This report presents the geologic framework critical in understanding spring discharge and the hydrogeology in Black Canyon directly south of Lake Mead below Hoover Dam, Nevada and Arizona. Most of the springs are thermal 2 Geologic Framework of Thermal Springs, Black Canyon, Neva...
Final Report describing regional signature detection for blind and traditional play fairways as part of Phase I of New Mexico Play Fairway Analysis. This project seeks to reduce exploration risk and identify new prospective targets using available geologic, geochemical, and geophy...
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 California and Nevada, geothermal projects are subject to non-technical barriers, which may create development delays leading to higher project costs and risks and decreased competitiveness with other electricity generation technologies. These non-technical barriers may include...
This report examines life cycle water consumption for various geothermal technologies to better understand factors that affect water consumption across the life cycle (e.g., power plant cooling, belowground fluid losses) and to assess the potential water challenges that future geo...
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 comprehensive technical report documents a multi-component approach to in-situ stress characterization at the Utah FORGE EGS site that integrates Machine Learning (ML) methods for predicting near-well principal stresses around geothermal wells with the physics-based finite el...
This collection includes datasets used for the analyses and modeling of low-temperature geothermal resources in east-central Georgia. This project file includes tabular and geospatial data accessed from publicly available repositories and scholarly and government publications.
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...
Research references to literature about the Newberry geothermal area, Oregon.
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...
This submission includes data accompanying the paper titled, "Isotropic components of microseismic moment tensors at Utah FORGE reveal a diversity of fluid pathway creation processes in EGS development." Included are the pre-calculated Green's functions used to calculate the momen...
This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of designing a recurrent neural network (RNN) to predict induced seismicity. Background material is included t...
Well completions are an integral part of providing safe, reliable and continuous access to underground resources such as oil, gas and geothermal resources. Completions are typically considered to be the final step of drilling engineering which includes processes such as setting c...
Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...
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...
This dataset includes a consistent framework of annual, quarterly, and hourly energy demand and operational profiles for 63 U.S. manufacturing subsectors defined by NAICS classification, building on the county-level demand dataset "Updated U.S. Low-Temperature Heating and Cooling ...
This is a report that describes the modelling of fracture nucleation and propagation in the near-wellbore region to understand the relationship between in situ stress and fracture patterns. A novel phase field formulation is described here, which represents fractures as a diffuse ...
This collection includes datasets used for the analyses and modeling of low-temperature geothermal resources in the central Hudson River Valley region in New York State. This project file includes tabular and geospatial data accessed from publicly available repositories managed by...
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...
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
This dataset presents the results of techno-economic simulations performed using the Distributed Geothermal Market Demand Model (dGeo) to evaluate the feasibility of Enhanced Geothermal Systems (EGS)-based district heating in the Northeastern United States. Developed by the Nation...
Included here are access links to a report on procurement options for low temperature geothermal technologies at federal facilities from Pacific Northwest National Laboratory. Federal agencies are moving towards more efficient and resilient facilities by increasingly implementing...
Google Map