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Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...

Norbeck, J. et al Fervo Energy

Feb 08, 2023
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Simbol Materials Lithium Extraction Operating Data From Elmore and Featherstone Geothermal Plants

The data provided in this upload is summary data from its Demonstration Plant operation at the geothermal power production plants in the Imperial Valley. The data provided is averaged data for the Elmore Plant and the Featherstone Plant. See average brine composition tab for submi...

Harrison, S. Simbol, Inc

Jul 01, 2015
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Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...

Moraga, J. Colorado School of Mines

Apr 27, 2021
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University of Illinois Campus Deep Direct-Use Feasibility Study Designs for Deep Injection and Monitoring Wells

The following information is provided about the design of deeps wells constructed in the Illinois Basin to store, sequester, or dispose of CO2, natural gas, and industrial wastes.

Lin, Y. et al University of Illinois

Mar 30, 2018
3 Resources
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Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions

This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...

Kelley, M. et al Battelle Memorial Institute

Jun 19, 2023
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Water Use in Enhanced Geothermal Systems (EGS): Geology of U.S. Stimulation Projects, Water Costs, and Alternative Water Use Policies

According to the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE), geothermal energy generation in the United States is projected to more than triple by 2040 (EIA 2013). This addition, which translates to more than 5 GW of generation capacity, is anti...

Harto, C. et al Argonne National Laboratory

Dec 16, 2014
13 Resources
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Geothermal Sector Cybersecurity Vulnerability Assessment Presentation

As geothermal resource contributions to the energy sector grow, cybersecurity will be increasingly important to ensure resilient, reliable, and secure clean energy for years to come. An overview of the cybersecurity vulnerability assessment project was developed and presented at t...

Markel, T. et al National Renewable Energy Laboratory

Oct 20, 2020
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...

Marone, C. et al Pennsylvania State University

May 14, 2021
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Compatibility Study of Nanofiltration and Reverse Osmosis Membranes with 1 Cyclohexylpiperidenium Bicarbonate Solutions

The switchable polarity solvent forward osmosis (SPS FO) desalination process requires use of a polishing filtration step to remove trace quantities of draw solution from the product water stream. Selected nanofiltration (NF) and reverse osmosis (RO) membranes were tested for thei...

Adhikari, B. et al Idaho National Laboratory

Oct 01, 2015
2 Resources
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Paisley Oregon Geothermal Plant Operated by Surprise Valley Electrification 2016 Operational Information

This submission includes an Electricity Generation Summary, Maintenance Logs, Detailed Operations Data, Operating Cost Summary, and an Operations overview at the Paisley Oregon Geothermal Plant. Data uploaded for SVEC by Tom Williams, NREL

Culp, E. Surprise Valley Electrification Corp. (SVEC)

Jan 01, 2017
5 Resources
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Appendices for Geothermal Exploration Artificial Intelligence Report

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...

Duzgun, H. et al Colorado School of Mines

Jan 08, 2021
12 Resources
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Utah FORGE Well 16A(78)-32 Stimulation Data (April, 2022)

This is a set of data related to the stimulation program at Utah FORGE well 16A(78)-32 during April, 2022. This includes daily reports, 1 second Pason data, tracer data, and shear stimulation data and information including a report of an evolving prognosis for the stimulation oper...

McLennan, J. Energy and Geoscience Institute at the University of Utah

May 18, 2022
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

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...

Mordensky, S. et al United States Geological Survey

Feb 07, 2023
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

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...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
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