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At least 433 records · Page 24

The Geothermal Artificial Intelligence for geothermal exploration

Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial Intelligence (AI) have potential in managing the challenges of geothermal exploration. In this paper, we present a methodology that integrates RS, ML and AI to create an initial assessment of geothermal potential, by resorting to known indicators of geothermal areas namely mineral markers, surface temperature, faults and deformation. We demonstrated the implementation of the method in two sites (Brady and Desert Peak geothermal sites) that are close to each other but have different characteristics (Brady having clear surface manifestations and Desert Peak being a blind site). Here, we processed various satellite images and geospatial data for mineral markers, temperature, faults and deformation and then implemented ML methods to obtain pattern of surface manifestation of geothermal sites. We developed an AI that uses patterns from surface manifestations to predict geothermal potential of each pixel. We tested the Geothermal AI using independent data sets obtaining accuracy of 92-95%; also tested the Geothermal AI trained on one site by executing it for the other site to predict the geothermal / non-geothermal delineation, the Geothermal AI performed quite well in prediction with 72-76% accuracy.

15 GEOTHERMAL ENERGY↗

An Analysis of High Opportunity Geothermal Leasing Areas on BLM and USFS Lands

This analysis, conducted by the National Renewable Energy Laboratory (NREL) with support from the U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO), models potential geothermal deployment on BLM and USFS land for the years 2025, 2030, 2035, and 2050 under various scenarios using the Renewable Energy Potential (reV) model and the Regional Energy Deployment System (ReEDS) model. This report identifies potential future high opportunity geothermal leasing areas (i.e., Best, Middle, and Least identified opportunities) based on available data for geothermal resource potential, natural resource conflicts, and transmission access. In addition, this analysis considers the impacts of the Energy Policy Act of 2005's (EPAct 2005's) default competitive leasing provisions, specifically the impact this may have had on geothermal resource discovery outside of known geothermal resource areas.

15 GEOTHERMAL ENERGY↗

Model results and data for Nontechnical Barriers to Geothermal Development

Data included in this submission support the analysis conducted for the report "Nontechnical Barriers to Geothermal Development" which is linked bellow. These data include information about the power purchase agreements (PPAs) analyzed for the report, inputs and model results for the pro forma economic analysis, and outputs from the regression analysis conducted on PPAs comparing geothermal and other power generation technologies.

15 GEOTHERMAL ENERGY↗

Geothermal Flexibility Characteristics

This spreadsheet identifies various flexibility characteristics for flash and binary geothermal power plants which could potentially facilitate provision of grid services beyond bulk power generation. Characteristics are differentiated between resource characteristics such as metal concentration and plant characteristics such as flow rates of pumps used in flash vs. binary plants.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Phase 3 InSAR Study Results

Ground movement is evaluated through analysis of Interferometric Synthetic Aperture Radar (InSAR) interferograms. Results indicate there has been no detectable ground movement at millimeter scale. The zipped file in this submission contains a report, maps, and results from the InSAR Phase 3 study done to determine ground crustal deformation, if any, in the Utah FORGE area. The data used to facilitate this study included synthetic aperture radar data acquired by the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). It is accompanied by a README.txt file which further describes each included dataset.

15 GEOTHERMAL ENERGY↗

EGS Collab Experiment 1: Circulation Testing Processed data

This submission includes processed and reduced data for circulation testing that was conducted at the 164' fracture on the 4850 ft level of the Sanford Underground Research Facility. The circulation tests were done to test the flow through the 164' fracture in the EGS Collab Experiment 1 testbed on the 4850 ft level of the Sanford Underground Research Facility in order to validate computer models concerned with flow processes and heat exchange processes in EGS. This data was processed from raw data that is available in the GDR submission linked below: "EGS Collab Circulation Testing Raw Data and Documentation." Python scripts used to process and reduce the data are included. The scripts also serve as "documentation" as well as examples for data processing. More information about the test itself as well as the rationale and process of data processing is available at wiki page linked below.

15 GEOTHERMAL ENERGY↗

Utah FORGE Seismic Stations and Wells GPS Survey Data, 2021

This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 58-32, and 16A(78)-32 and BOR1, BOR2, BOR3, FOR2, FOR5, FORK, FORU, and FORW seismic stations. These are from a GPS survey conducted by the Utah Geological Survey in June, 2021.

15 GEOTHERMAL ENERGY↗

Utah FORGE Well 16A(78)-32 X-ray Diffraction Data

This submission contains x-ray diffraction data taken from 3,600 to 10,987 feet deep in well 16A(78)-32 in the Roosevelt Hot Springs Geothermal Area as part of the Utah FORGE project. 78 rock samples were taken. Samples are taken in a range of ten feet at 100 foot increments. Mineral abundances are given in weight percent of the sample, with results rounded to the nearest whole number. Fields marked with tr (trace) indicate that mineral is present, but that its abundance calculated from the Rietveld refinement was less than one weight percent; that it was observed in the clay-sized fraction, but not the bulk; and/or that it was observed in low abundance during petrographic analyses. The samples were taken between 10/29/2020 and 12/24/2020 during the drilling of well 16A(78)-32.

15 GEOTHERMAL ENERGY↗

Hydrothermal mineral alterations in the Brady and Desert Peak geothermal fields

Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. The analysis was performed using ENVI's Target Detection process against USGS library spectra for Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite. Each compressed file includes three raster images created after fusing the target detection results for all minerals: _fusion_all - Contains the 8 layers resulting from target detection and fusion of the 5 minerals _fusion_all_normal - Contains each layer as above, after Winsorization (99% percentile on the positive side only due to skewness of results), and normalization of each layer to achieve a range between [0-1] _fusion_final - Contains a fused raster by sub-setting the normalized layers, with the results of MTMF, MTTCIMF, OSP and SAM. Both CEM and MF were discarded as being less accurate than MTMF, and TCIMF is less accurate than MTTCIMF, ACE results were discarded because they were notably different from the rest of the analyses. The base_names are: brady - Brady geothermal area only desert - Desert Peak geothermal area only hymap - Full image analysis comprising both the Brady and Desert Peak geothermal areas

15 GEOTHERMAL ENERGY↗

Geothermal Mineral Alterations in Brady and Desert Peak

Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.

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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021

This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in the laboratory at UW-Madison, and an excel catalog of rock samples with information on sample name, rock type, coordinates of sample location, structural measurements, field notes, observations for plug preparation (e.g., weathering, ability to be cut and cored), and rock descriptions. It should be noted that not every sample was photographed in the field. Names and descriptions of rock formation units are taken from Rhodes et al. (2011). The README.txt file is a description of this submission.

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EGS Collab: Modeling and Simulation Working Group Teleconference Series (99-128)

This submission contains the presentation slides and recordings from EGS Collab Modeling and Simulation Working Group (MSWG) teleconferences number 99 through 128. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and results to the simulation teams, and 3) hold open scientific discussions on EGS topics.

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Experimental Images and Videos of Foam Stability (Half-life)

The experimental data obtained in this project is the thermal stability data of various foams measured using the setup established at Temple University during this study. The setup is installed with a portable digital camera which can take images and videos of foam evolution at a given pressure and temperature condition. Consequently, the half-life data was recorded from the images/videos, which are used as a measure of the thermal stability for foams. Over the 3 years of this project, four different surfactants and five different stabilizing agents were studied. The surfactants are, Alfa Olefin Sulfonate (AOS), Sodium Dodecyl Sulphate (SDS), Tergitol (NP-40), and Cetyltrimethylammonium chloride (CTAC). The stabilizing agents are, guar gum, bentonite clay, crosslinking agents, silicon dioxide nanoparticles (60 to 70nm), and graphene oxide dispersions. Foam stability was evaluated at different temperatures between 100C and 200cC, while the foam generation pressure varied between atmospheric pressure (14.7 psi) and 1000 psi. The images are saved as .jpg file and videos are saved as .avi files.

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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021 Version 2.0

This submission includes an update to the WHOLESCALESamples2021January.xls file where the strikes and dips initially reported have been corrected to comply with the right hand rule. The updated excel file and a link to the original submission are included in this report. The original submission "WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021" contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in the laboratory at UW-Madison, and an excel catalog of rock samples with information on sample name, rock type, coordinates of sample location, structural measurements, field notes, observations for plug preparation (e.g., weathering, ability to be cut and cored), and rock descriptions. It should be noted that not every sample was photographed in the field. Names and descriptions of rock formation units are taken from Rhodes et al. (2011). The README.txt file is a description of this submission.

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Directional Cooling-Induced Fracturing: Directional Cooling Data Under True-Triaxial Stress State

Data includes Directional Cooling-Induced Fracturing (DCIF) testing data using westerly granite blocks. This submission includes data from two samples of westerly granite, lab sample 7 and 8. Files contain stress, temperature and acoustic emission data acquired during polyaxial, laboratory testing of westerly granite blocks for each sample. FILES: .tradb -- files containing acoustic emission waveforms; sqlite3 database .pridb -- files containing basic acoustic emission information (no waveforms); sqlite3 database .geom -- geometry of the AE sensor network (ASCII)

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Utah FORGE Well 56-32 Sludge XRF

This is an Excel spreadsheet containing the results of X-ray fluorescence from well 56-32 sludge samples. The instrumentation used was a Olympus Vanta M series handheld XRF analyzer. A glass (SiO2) "blank" was analyzed at the beginning and end of each sample batch to detect contamination within the instrument. The standard 2711A was analyzed at the beginning and end of each sample batch to detect drift in instrument precision over time. Material was analyzed in a plastic cup with a prolene thin film cover for minimal interference.

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