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"Machine Learning for in-situ stress"×
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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
0 Stars
Curated

Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the U...
Kelley, M. and Bunger, A. Battelle Memorial Institute
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

GIS Resource Compilation Map Package Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...
Brown, S. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
1 Resources
0 Stars
Publicly accessible

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

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...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible

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
1 Resources
0 Stars
Publicly accessible

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

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...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
0 Stars
Publicly accessible

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
0 Stars
Publicly accessible

Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress

Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizi...
Bunger, A. et al Battelle Memorial Institute
Dec 13, 2022
4 Resources
0 Stars
Curated

Utah FORGE 2-2446: Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity Workshop Presentation

This is a presentation on the Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity project by Lawrence Livermore National Laboratory, presented by Dr. Matteo Cusini. The project's objective was to employ a combination of high-fidelity simulations and true...
Cusini, M. and Bunger, A. Lawrence Livermore National Laboratory
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

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
0 Stars
Publicly accessible

GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples

This submission includes example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Kahunanui (KHN) fictional geothermal power plant, which uses synthetic data to model a fictional plant. Includes data curation, histo...
Taverna, N. et al Upflow
Jan 30, 2023
10 Resources
0 Stars
In progress

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
Curated

Utah FORGE: Phase Native State FALCON Model Files

The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...
Podgorney, R. Idaho National Laboratory
Jun 06, 2019
2 Resources
0 Stars
Curated

Investigation of Stimulation-Response Relationships for Complex Fracture Systems in Enhanced Geothermal Reservoirs

Hydraulic fracturing is currently the primary method for stimulating low-permeability geothermal reservoirs and creating Enhanced (or Engineered) Geothermal Systems (EGS) with improved permeability and heat production efficiency. Complex natural fracture systems usually exist in ...
Fu, P. et al Lawrence Livermore National Laboratory
Jan 01, 2011
2 Resources
0 Stars
Publicly accessible

Using Fully Coupled Hydro-Geomechanical Numerical Test Bed to Study Reservoir Stimulation with Low Hydraulic Pressure

This paper documents our effort to use a fully coupled hydro-geomechanical numerical test bed to study using low hydraulic pressure to stimulate geothermal reservoirs with existing fracture network. In this low pressure stimulation strategy, fluid pressure is lower than the minimu...
Fu, P. et al Lawrence Livermore National Laboratory
Jan 31, 2012
2 Resources
0 Stars
Publicly accessible

Simulating Complex Fracture Systems in Geothermal Reservoirs Using an Explicitly Coupled Hydro-Geomechanical Model

Low permeability geothermal reservoirs can be stimulated by hydraulic fracturing to create Enhanced (or Engineered) Geothermal Systems (EGS) with higher permeability and improved heat transfer to increase heat production. In this paper, we document our effort to develop a numerica...
Carrigan, C. et al Lawrence Livermore National Laboratory
Jan 01, 2011
2 Resources
0 Stars
Publicly accessible

Stimulation at Desert Peak Modeling with the Coupled THM Code FEHM

Numerical modeling of the 2011 shear stimulation at the Desert Peak Well 27-15 using a coupled thermal-hydrological-mechanical simulator. This submission contains the finite element heat and mass transfer (FEHM) executable code for a 64-bit PC Windows-7 machine, and the input and ...
Kelkar, S. et al Los Alamos National Laboratory
Apr 30, 2013
1 Resources
0 Stars
Publicly accessible

EGS Collab: Modeling and Simulation Working Group Teleconference Series (1-98)

This submission contains the presentation slides and recordings from the first 98 EGS Collab Modeling and Simulation Working Group teleconferences. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and resul...
White, M. et al Pacific Northwest National Laboratory
Feb 04, 2020
100 Resources
0 Stars
Publicly accessible

Snake River Plain FORGE: Site Characterization Data

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,...
Moos, D. and Barton, C. Idaho National Laboratory
Apr 18, 2016
49 Resources
0 Stars
Curated

WHOLESCALE: Coordinates of wells at San Emidio, Nevada

This dataset includes position coordinates and elevation information for wells at the WHOLESCALE San Emidio project location. Well positions in the attached file are characterized by UTM coordinates (Easting, Northing) in meters, and WHOLESCALE coordinates (Easting, Northing) rel...
Cardiff, M. et al University of Wisconsin Madison
Sep 25, 2023
1 Resources
0 Stars
Publicly accessible

Utah FORGE: Data for 3-D Model Development Lithology, Temperature, Pressure, and Stress

This submission comprises two downloadable .zip archives. Each archive contains spreadsheets with 3-D data and a .txt document describing the data. The Mesh Files .zip download contains data regarding the lithologic contacts of the granitoid and overlying sedimentary basin fill. T...
Podgorney, R. Idaho National Laboratory
Mar 17, 2020
2 Resources
0 Stars
Publicly accessible

WHOLESCALE: Mass Flux Rates for Wells at San Emidio in December 2016

This dataset provides mass flux rates in kg/s from six (production and injection) wells at San Emidio at minute intervals from December 1, 2016 December 15, 2016. Files for injection wells are named with "IW", for instance "WellIW42-21SI.csv", and include negative flux rates. Fil...
Cardiff, M. et al University of Wisconsin Madison
Dec 01, 2016
2 Resources
0 Stars
Curated
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