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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 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 report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
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...
This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to esti...
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...
This dataset contains project data generated by the project "Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers." It includes drilling, downhole drilling dynamics, bit records, daily drilling reports, directional surveys, lithology and mineralogy data, ...
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
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 dataset includes data from injection/fall-off experiments conducted in controlled laboratory settings. The aim is to investigate the physics governing fracture closure and the associated stress measurements during hydraulic fracturing. These time series data include flow rat...
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...
1301 Vertical Component seismic instruments were deployed at San Emidio Geothermal field in Nevada in December 2016. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in o...
This dataset contains the final technical report for the project Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development, carried out from 2021 to 2025 by Lawrence Berkeley Natio...
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 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, Dr. Laura J. P...
This submission contains curated injection parameter datasets from the 2022 and 2024 stimulation experiments conducted at the Utah FORGE site, along with the report documenting the data processing workflow. The datasets were developed as part of Project 6-3712: Probabilistic Estim...
Widespread adoption of geothermal energy will require access to deeply buried resources in granitic basement rocks at high temperatures and pressures. Exploiting these resources necessitates novel methods for drilling, stimulation, and maintenance, under operating conditions that ...
The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater,...
Data from high temperature dynamic sealing tests for various fracture widths, at various temperatures (degrees F), with 5 wt.% bentonite-based mud containing various material fiber contents, at 100 to 400 psi differential pressure.
Data from pressure test and evaluation of the dy...
Description of a conceptual commercial process to remove rare earth elements (REEs) from geothermal brine, based on a small-scale laboratory experiment to load, strip, and regenerate a ligand-based media used to adsorb REEs from a simulated brine doped with known mineral concentra...
This dataset contains results from five laboratory shear experiments on gneiss and granitoid samples from the Utah FORGE site, conducted at Penn State University. The experiments investigate links between fault surface roughness, frictional behavior, permeability, and P-wave acous...
This dataset contains thermohydraulic measurements of fluid flow through single and dual fracture systems under controlled laboratory conditions. Experiments were conducted at Oklahoma State University using various ionic and nonionic fluids, including deep eutectic solvents (DES)...
This dataset includes raw and processed seismic data from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 N, 119.409019 W. The first...
This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes therm...
This dataset contains high-pressure, high-temperature (HPHT) rheological measurements of ionic liquids and alternative geothermal fluids. Experiments were conducted at Oklahoma State University using a Chandler Model 5550 viscometer and Rheo 5000 software to evaluate the flow beha...
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