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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 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 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 Dr. No'am Zach Dvory. This video slide presentation, by the University of Utah, d...
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 ...
This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed ...
This recorded webinar provides background on the Value of Information (VOI) App and demonstrates how to use the application. The webinar walks through a public example dataset and includes slides and screen sharing to introduce decision analysis, the VOI metric, and the app workfl...
High-pressure and high-temperature (HPHT) lost circulation material (LCM) rheology test results, LCM particle size distributions (PSD) analysis, and HPHT LCM fluid loss test results. Three academic papers / reports derived from this research are also presented.
This report contains the results of research conducted to make measurements in the FORGE wells to map flowing fractures and estimate their flow magnitudes in real time. Implementation of the project had two substantial goals: (1) to locate flowing fractures at FORGE and estimate t...
We synthesized PEGDA polymer hydrogel beads for cell embedding and compared REE biosorption with these beads via a gravity-driven flow through setup. One way to set up a flow through system is by cell encapsulation into polymer beads with a column setup similar to that used in th...
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...
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the n...
At the beginning of this project, the Temple team spent significant effort to collect data relevant to foam fracturing. More than 40 articles/reports were found in the open literature that reported the properties of aqueous foams under various testing conditions. The foam properti...
During the 2013 fiscal year, the National Renewable Energy Laboratory (NREL) developed the Geothermal National Environmental Policy Act (NEPA) Database with funding provided by the U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO). The information in the databas...
This collection includes datasets used for the analyses and modeling of low-temperature geothermal resources at the U.S. Army's Detroit Arsenal located in Warren, Michigan. This project file includes tabular and geospatial data accessed from publicly available repositories held by...
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 ...
The included report outlines the creation of three 3D resistivity models that will be used to determine the sensitivity of EM measurements for the hypothetical stimulated reservoir at FORGE as well as for EM survey design. FORGE project 3-2535 is planning on using a casing source ...
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
This submission includes raster datasets for each layer of evidence used for weights of evidence analysis as well as the deterministic play fairway analysis (PFA). Data representative of heat, permeability and groundwater comprises some of the raster datasets. Additionally, the fi...
This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. Th...
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 FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
This is a final report summarizing a one-year (2014-15) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and...
This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylva...
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