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Hybrid machine learning model to predict 3D in-situ permeability evolution

Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...

Elsworth, D. and Marone, C. Pennsylvania State University

Nov 22, 2022
4 Resources
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EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper

Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...

Guglielmi, Y. Lawrence Berkeley National Laboratory

Sep 24, 2020
9 Resources
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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
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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
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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
1 Resources
0 Stars
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GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

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 ...

Buster, G. et al Upflow

Jun 30, 2021
11 Resources
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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
1 Resources
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Control-based optimization for tethered tidal kite

This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission. Cobb...

Vermillion, C. et al North Carolina State University

Mar 02, 2020
3 Resources
0 Stars
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Utah FORGE LBNL 3-2535 Preliminary Report on Development of a Reservoir Seismic Velocity Model

This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation. A preliminary 3D velocity model for the larg...

Gritto, R. Array Information Technology

Jan 30, 2023
1 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
0 Stars
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Sustainable Self-Propping Shear Zones in EGS: Chlorite, Illite, and Biotite Rates and Report

Spreadsheet containing chlorite, illite, and biotite rate data and rate equations that can be used in reactive transport simulations. Submission includes a report on the development of the rate laws.

Carroll, S. and Smith, M. Lawrence Livermore National Laboratory

Nov 06, 2015
2 Resources
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Chlorite Dissolution Kinetics at Variable pH and Temperatures up to 275C

FY13 annual report describing the calculations and results associated with the data and dissolution rate contained in "Chlorite Kinetic Dissolution Data and Rate" (linked below).

Carroll, S. and Smith, M. Lawrence Livermore National Laboratory

Oct 01, 2013
2 Resources
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Chlorite, Biotite, Illite, Muscovite and Feldspar Dissolution Kinetics at Variable pH and Temperatures up to 280 deg C

Chemical reactions pose an important but poorly understood threat to EGS long-term success because of their impact on fracture permeability. This report summarizes the dissolution rate equations for layered silicates where data were lacking for geothermal systems. Here we report ...

Carroll, S. et al Lawrence Livermore National Laboratory

Feb 24, 2017
2 Resources
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DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period

This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file correspondin...

Reinisch, E. et al University of Wisconsin

Jun 27, 2018
20 Resources
0 Stars
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ORNL Air Handling Fault Test Data FRP#1

ORNL test data for air handling faults. Data contains electrical measurements and power consumption measurements.

Fugate, D. and Laboratory, O. Oak Ridge National Laboratory

Mar 22, 2017
5 Resources
0 Stars
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Utah FORGE Project 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
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Washington Play Fairway Analysis Geothermal Heat and Permeability Potential Geodatabases

This file contains file geodatabases of the Mount St. Helens seismic zone (MSHSZ), Wind River valley (WRV) and Mount Baker (MB) geothermal play-fairway sites in the Washington Cascades. The geodatabases include input data (feature classes) and output rasters (generated from modeli...

Norman, D. et al Washington Division of Geology and Earth Resources

Dec 15, 2015
5 Resources
0 Stars
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Modeling the Integration of Marine Energy into Microgrids Wave Resource Assessment

This submission has wave resource assessments which were conducted for six locations based on IEC requirements using the DOE WPTO Hindcast data and MHKiT. The locations are chosen to provide varying wave climates and include PacWave South, OR; Wave Energy Testing Site (WETS), HI; ...

Mankle, H. and Robertson, B. University of Alaska Fairbanks

Jan 19, 2023
9 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
11 Resources
0 Stars
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Utah FORGE Well 16A(78)-32 Stage 1 Pressure Falloff Analysis

This is an analysis of the pressure falloff in stage 1 fracture stimulation of FORGE well 16A(78)-32. The objective of this research is to understand the information content of the well stimulation data of FORGE Well 16A(78)-32. The Stage 1 step-rate test, a variant of the classic...

Kazemi, H. et al Colorado School of Mines

Aug 04, 2022
1 Resources
0 Stars
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Laboratory Experiments Examining the Effect of Thermal and Mechanical Processes on Hydraulic Transmissivity Evolution

Using laboratory slide-hold-slide experiments, at temperatures from 22 to 200 degrees C, to examine effects of fracture reactivation and quasi-static loading on the evolution of fluid transport properties of simulated fractures in Westerly granite. At all temperatures, the in-plan...

Lockner, D. et al U.S. Geological Survey

Apr 03, 2023
2 Resources
0 Stars
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Technology Development and Field Trials of EGS Drilling Systems at Chocolate Mountain

Polycrystalline diamond compact (PDC) bits are routinely used in the oil and gas industry for drilling medium to hard rock but have not been adopted for geothermal drilling, largely due to past reliability issues and higher purchase costs. The Sandia Geothermal Research Departmen...

Knudsen, S. et al Sandia National Laboratories

Jan 01, 2012
3 Resources
0 Stars
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Utah FORGE: Well 16A(78)-32 Logs

This dataset contains all well logs from Utah FORGE well 16A(78)-32. This includes the mud log, Sanvean Technologies logs, and Schlumberger logs. Please see the file descriptions below for information about each log.

Gilmour, B. et al Energy and Geoscience Institute at the University of Utah

Mar 08, 2021
7 Resources
0 Stars
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LCOE Baseline for RME Surge WEC Device

This submission includes all the data to support an LCOE baseline assessment for the Resolute Marine Energy (RME) Surge WEC device.

Previsic, M. et al Re Vision Consulting

Jul 19, 2017
4 Resources
0 Stars
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OU (A. Ghassemi) Reservoir Geomechanics & Seismicity Research Group

Data on Injection-Induced Shear Slip and Permeability Increase in Granite Fractures. In the plots, we present the results of novel injection-induced shear tests on cylindrical granite samples each containing a single tensile or saw-cut fracture. Flow rate and permeability are sho...

Ghassemi, A. University of Oklahoma

Aug 14, 2018
4 Resources
0 Stars
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