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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...
This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study.
The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for we...
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...
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
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...
This recorded webinar provides background on National Laboratory of the Rockies reV model (https://www.nlr.gov/gis/rev) and specifically the geothermal module. The reV model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate e...
This dataset contains distributed acoustic sensing (DAS) and downhole geophone data collected during the April 2024 stimulation experiments at the Utah FORGE site. DAS data were acquired from well 16B(78)-32 by Neubrex and processed by GeoEnergie Suisse (GES), covering the period ...
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 ...
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...
This dataset contains distributed acoustic sensing (DAS) data collected during the April 2024 mini-circulation test at the Utah FORGE site. Data were acquired from wells 16B(78)-32 and 58-32 during the mini-circulation period from April 23-28, 2024, following stimulation of the in...
Included are experimental data recorded from shear experiments that explore the effects of pore pressure heterogeneity on microseismic character and fault slip timing resulting from shear reactivation of laboratory faults. Raw mechanical and acoustic data from 15 experiments are i...
This dataset covers work that investigated the apparent toughness anisotropy at Utah FORGE by comparing microseismic data with stress profiles from field measurements. The study analyzes the hydraulic fracture growth of Stage 3 at Well 16A(78)-32 using MEQ data, calibrating a nume...
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...
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