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An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Geothermal Behavior with Example Simulations on The Treasure Island and UC Berkeley Campus
This submission contains the source code of the Hydrothermal Finite Element Simulator used for the Treasure Island and UC Berkeley campus geothermal simulation. It contains a report that summarizes the development and validation of this Hydrothermal Finite Element Simulator, with ...
Chen, K. et al Lawrence Berkeley National Laboratory
Aug 01, 2021
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
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
11 Resources
0 Stars
Publicly accessible
11 Resources
0 Stars
Publicly accessible
Alternative CAES Technology Using Depleted Unconventional Gas Wells and Subsurface Thermal Energy Storage (GeoCAES)
This project assessed the technical viability of a process called GeoCAES. The process stores electrical energy by injecting natural gas into shale gas formations using a compressor, storing it, and producing it through an expander to generate electricity. This data submission inc...
Johnston, H. and Young, D. National Renewable Energy Laboratory
May 23, 2019
8 Resources
0 Stars
Publicly accessible
8 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
3 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: Temperature profile
This submission includes an input file, plot file, Fortran conversion file, and 3D data file from the simulation of the temperature profile within the Test Bed #1 of the EGS Collab project. The simulation was executed with PNNL's STOMP-GT simulator, which reads the input file, and...
White, M. Pacific Northwest National Laboratory
Apr 01, 2019
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal energy production. Phase 1 includes reservoir analyses to determine injector/producer well schemes that balance the generation of economically useful flow rates at the ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Resource Analysis for Deep Direct-Use Feasibility Study in East Texas
The National Renewable Energy Laboratory, Southern Methodist University Geothermal Laboratory, Eastman Chemical, Turbine Air Systems, and the Electric Power Research Institute are evaluating the feasibility of using geothermal heat to improve the efficiency of natural gas power pl...
Richards, M. et al Southern Methodist University
Jun 28, 2018
13 Resources
0 Stars
Publicly accessible
13 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
11 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
6 Resources
0 Stars
Publicly accessible
Snake River Plain Geothermal Play Fairway Analysis Project MT Data
MT is measured in the field by using induction coils to measure the time-varying magnetic source for frequencies between 1000-0.001~Hz, and electric dipoles to measure the Earth's electrical response. Because the magnetic source field is polarized, orthogonal directions of the f...
Peacock, J. et al United States Geological Survey
May 06, 2018
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
PoroTomo Distributed Temperature Sensing (DTS) Measurements made in Brady Observation Well 56-1
This submission is a follow-up to Distributed Temperature Sensing (DTS) measurements made in Brady observation well 56-1 during the PoroTomo field experiment conducted in March, 2016. The measurements in this data set were made on August 24, 2018 over an approximately 20 hour per...
Kratt, C. et al Oregon State University
Jan 09, 2019
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Utah FORGE: InSAR Data Best Pairs
This submission provides Interferometric Synthetic Aperture Radar (InSAR) data covering the Utah FORGE site via the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). Data was collected between 2019/01/01 and 2023/06/30. Interferometric pairs (...
Batzli, S. and Feigl, K. University of Wisconsin Madison
May 31, 2023
11 Resources
0 Stars
Curated
11 Resources
0 Stars
Curated
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2000
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
G-Function Library for Modeling Vertical Bore Ground Heat Exchanger
This library contains g-functions (thermal response functions) for standard, regularly spaced vertical borehole ground heat exchangers. In total, it contains 34, 321 configurations. To permit interpolation, each configuration has g-functions for heights of 24, 48, 96, 192, and 384...
Spitler, J. et al Oak Ridge National Laboratory
Jun 30, 2021
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)
This submission contains information used to compute the risk factors for the GPFA-AB project. The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking ...
E., T. Cornell University
Sep 30, 2015
191 Resources
0 Stars
Publicly accessible
191 Resources
0 Stars
Publicly accessible