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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

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...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
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Stanford Thermal Earth Model for the Conterminous United States

Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....

Aljubran, M. and Horne, R. Stanford University

Mar 14, 2024
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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

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-...

Lu, G. et al University of Pittsburgh

Aug 30, 2024
2 Resources
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Community Geothermal: Final Thermal Conductivity Test Report and Data Logs Carbondale, CO

Provided here are a final thermal conductivity test report, a drilling log, and a heat rejection log from Carbondale, CO. Also attached is a report made before drilling, which contains predictions on the hydrogeologic conditions of the drill site. The forty-eight (48.9) hour in-si...

Ewbank, G. et al Clean Energy Economy for the Region (CLEER)

Oct 20, 2023
4 Resources
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System Advisor Model (SAM)

The System Advisor Model (SAM) is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry. SAM makes performance predictions and cost of energy estimates for grid-connected power projects based on installation a...

Blair, N. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
1 Resources
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In curation

Analysis of Pre-Retrofit Building and Utility Data Southeast United States

TO4 9.1.2: Comm. Scale Military Housing Upgrades This project delves into the workflow and results of regression models on monthly and daily utility data (meter readings of electricity consumption), outlining a process for screening and gathering useful results from inverse model...

Beach, R. and Prahl, D. Ibacos Innovation

Apr 27, 2016
12 Resources
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Utah FORGE: Stress Logging Data

This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in...

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

Mar 14, 2018
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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
6 Resources
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Transient Cold-Climate Building Foundation Hygrothermal Experimental Data

The data consist of two years of continuous transient experimental measurements on the hygrothermal performance of concrete masonry block walls in a full basement in a cold climate (US DOE climate zone 7). The walls were insulated in compliance with the thermal requirements of the...

Merket, N. and Laboratory, N. National Renewable Energy Laboratory

Jun 30, 2015
4 Resources
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In curation

Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 May 2025

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...

Lu, G. et al University of Pittsburgh

Jun 05, 2025
2 Resources
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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
7 Resources
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Laboratory Upgrade Point Absorber WEC-Sim Model with MoorDyn Moorings

This dataset includes a WEC-Sim and MoorDyn model of the Laboratory Upgrade Point Absorber (LUPA). LUPA is an open-source wave energy converter designed and tested by Oregon State University. The files provided here constitute a stable LUPA configuration with three mooring lines. ...

Mcconnell, A. Oregon State University

Oct 08, 2024
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EGS Collab Experiment 1: DNA tracer data on transport through porous media

This submission contains DNA tracer data that supports the analysis and conclusions of the publication, "DNA tracer transport through porous media The effect of DNA length and adsorption." https://doi.org/10.1029/2020WR028382. This experiment used DNA as an artificial reservoir t...

Zhang, Y. et al Stanford University

Nov 21, 2020
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Utah FORGE 5-2428: Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior Workshop Presentation

This is a presentation on the Fracture Permeability Impact on Seismic Slip Behavior project by Lawrence Livermore National Laboratory, presented by Dr. Kayla A. Kroll. The project's objective is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemic...

Kroll, K. et al Lawrence Livermore National Laboratory

Sep 08, 2023
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Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report

This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...

Mustafa, A. et al Battelle Memorial Institute

Sep 28, 2023
3 Resources
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Error-Level-Controlled Synthetic Forecasts for Renewable Generation

Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...

Zhang, X. et al National Renewable Energy Laboratory (NREL)

Jun 01, 2021
3 Resources
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TEAMER: Tidal Energy Resource Characterization and Model Validation via the Assessment of Distributed Current Measurements from microFloat Swarms, Data and Post-Access Report

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for pro...

University of Washington (NNMREC)

Aug 20, 2020
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EGS Collab Experiment 1: TOUGH2-CSM Simulation of Embedded Natural Fractures and Chemical Tracer Transport and Sorption

The EGS Collab SIGMA-V project is a multi-lab and university collaborative research project that is being undertaken at the Sanford Underground Research Facility (SURF) in South Dakota. The project consists of studying stimulation, fluid-flow, and heat transfer processes at a scal...

Johnston, B. et al National Renewable Energy Laboratory

Jun 07, 2019
4 Resources
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Deep Green Unannotated Protein Structures

The Deep Green list is based on the identification and curation of conserved unannotated proteins in three green lineage (Viridiplantae) model organisms; Arabidopsis thaliana, Chlamydomonas reinhardtii, and Setaria viridis. Preliminary characterization of Deep Green proteins and g...

Knoshaug. . et al National Renewable Energy Laboratory

Apr 20, 2023
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Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa (for corresponding manuscript: DOI: 10.1002/bbb....

Happs. . et al National Renewable Energy Laboratory

Mar 16, 2022
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3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

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...

Siler, D. and Pepin, J. United States Geological Survey

Oct 01, 2021
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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

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...

Siler, D. et al United States Geological Survey

Oct 01, 2021
6 Resources
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Deep Direct-Use Feasibility Study Numerical Modeling and Uncertainty Analysis using iTOUGH2 for West Virginia University

To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of...

Garapati, N. et al West Virginia University

Dec 20, 2019
13 Resources
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Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the...

Smith, J. Cornell University

Oct 29, 2019
6 Resources
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INGENIOUS Great Basin Regional Dataset Compilation

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...

Ayling, B. et al GBCGE, NBMG, UNR

Jun 30, 2022
16 Resources
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