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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

Utah FORGE: 2024 Discrete Fracture Network Model Data

The Utah FORGE 2024 Discrete Fracture Network (DFN) Model dataset provides a set of files representing discrete fracture network modeling for the FORGE site near Milford, Utah. The dataset includes four distinct DFN model file sets, each corresponding to different time frames and ...

Finnila, A. and Jones, C. Energy and Geoscience Institute at the University of Utah

Sep 08, 2024
5 Resources
0 Stars
Curated

Utah FORGE: Well 16A(78)-32 Simplified Discrete Fracture Network Data

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...

Finnila, A. Golder Associates Inc.

Jun 01, 2021
3 Resources
0 Stars
Curated

Modeling Responses of Naturally Fractured Geothermal Reservoir to Low-Pressure Stimulation

Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...

Fu, P. and Carrigan, C. Lawrence Livermore National Laboratory

Jan 01, 2012
2 Resources
0 Stars
Publicly accessible

Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models

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...

Finnila, A. Energy and Geoscience Institute at the University of Utah

Oct 02, 2023
17 Resources
0 Stars
Publicly accessible

Utah FORGE: Well 16A(78)-32 Stimulation DFN Fracture Plane Evaluation and Data

This dataset includes files used to fit planar fractures through the preliminary earthquake catalogs of the three stages of the April 2022 well 16A(78)-32 stimulation which is linked bellow. These planar features have been used to update the FORGE reference Discrete Fracture Netwo...

Finnila, A. WSP Golder

Oct 27, 2022
3 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

SMP and Fracture Modeling

The problem of loss circulation in geothermal wells is inherently challenging due to high temperatures, brittle rocks, and presence of abundant fractures. Because of the inherent challenges in geothermal environments, there are limitations in selecting proper lost circulation mate...

Salehi, S. et al University of Oklahoma

Oct 01, 2021
4 Resources
0 Stars
Publicly accessible

Utah FORGE 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity

This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the t...

Ward-Baranyay, M. et al Rice University

Jan 01, 2023
4 Resources
0 Stars
Curated

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
0 Stars
Publicly accessible

SMP Preparation, Programming, and Characterization

Salehi, S. et al University of Oklahoma

Oct 01, 2021
4 Resources
0 Stars
Curated

Utah FORGE: Discrete Fracture Network (DFN) Data

Finnila, A. and Podgorney, R. Golder Associates Inc.

Jun 24, 2020
66 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

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

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

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

Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags

Lanthanide binding tags (LBTs) have been engineered onto native Escherichia coli (E. coli) bacterial surfaces to enhance extraction and recovery of rare earth elements (REEs). Three strains of E. coli were studied: (1) the native E. coli surface, (2) a mutant E. coli surface with ...

Jiao, Y. Lawrence Livermore National Laboratory

Apr 01, 2018
1 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

Community Geothermal: Borefield Design, Thermal Conductivity, and Subsurface Modeling Data Chicago, IL

This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes therm...

Baser, T. et al Saint Louis University

Dec 04, 2023
6 Resources
0 Stars
Curated

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

Utah FORGE: Evaluation of Potential Geochemical Responses to Injection in the FORGE Geothermal Reservoir

Plugging of fracture porosity from mineral precipitation due to injecting cold water into a a geothermal reservoir can impact the overall permeability of the fracture network in the reservoir. This can have serious ramifications on the efficiency of the geothermal resource. Geoche...

Patil, V. and Simmons, S. Energy and Geoscience Institute at the University of Utah

Apr 03, 2019
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

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

DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific e...

Pauling, H. et al National Renewable Energy Laboratory

Jun 30, 2023
22 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...