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Matlab Scripts and Sample Data Associated with Water Resources Research Article
Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research:
Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock
M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1)
1 California St...
Becker, M. and Coleman, T. California State University
Jul 18, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Imperial Valley Dark Fiber Project Continuous DAS Data
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory
Nov 10, 2020
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests: Hydraulic Data
Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this gr...
Cole, M. California State University
Jul 31, 2015
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
20 Resources
1 Stars
Curated
20 Resources
1 Stars
Curated
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
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: Microseismic Monitoring
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Schoenball, M. et al Lawrence Berkeley National Laboratory
Jul 29, 2019
46 Resources
0 Stars
Curated
46 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
2 Resources
0 Stars
Curated
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
4 Resources
0 Stars
Publicly accessible
Community Geothermal: Seward Alaska Heat Loop District Energy System Modelica Model
This dataset contains a Modelica-based dynamic thermal simulation model of the Seward Heat Loop project. The model contains building loads generated from DesignBuilder simulations of the four city-owned buildings that are connected to the system. These buildings are heated by a hy...
Mitchell, M. et al National Renewable Energy Laboratory
Sep 29, 2024
1 Resources
0 Stars
In progress
1 Resources
0 Stars
In progress
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
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
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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments
Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite.
All expe...
Yu, J. et al Pennsylvania State University
Jul 01, 2023
27 Resources
0 Stars
Curated
27 Resources
0 Stars
Curated
Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems
Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduct...
Hu, J. et al Lawrence Berkeley National Laboratory
Jan 31, 2022
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible