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EGS Collab Experiment 1: DNA tracer data on transport through porous media
This submission contains DNA tracer data that supports the analysis and conclusions of the publication, "DNA tracer transport through porous media The effect of DNA length and adsorption." https://doi.org/10.1029/2020WR028382. This experiment used DNA as an artificial reservoir t...
Zhang, Y. et al Stanford University
Nov 21, 2020
3 Resources
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3 Resources
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EGS Collab Experiment 1: Tracer data tests
This file contains the first set of tracer data for the EGS Collab testbed. The first set of tracer tests were conducted during October-November, 2018. We have included tracer data for C-dots, chloride, fluorescein, and rhodamine-B. The details about the tracer test can be found i...
Neupane, G. et al Idaho National Laboratory
Apr 16, 2019
3 Resources
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3 Resources
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EGS Collab Experiment 1: Second Set Tracer Test Results
The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead,...
Neupane, G. et al Idaho National Laboratory
Dec 19, 2019
4 Resources
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4 Resources
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First Tracer Test After Circulation in Desert Peak 27-15
Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored ove...
Rose, P. University of Utah
Nov 16, 2013
1 Resources
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1 Resources
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Utah FORGE: Well 16A(78)-32 Stimulation Tracer Test Results
This archive contains data from the tracer test performed during the Utah FORGE well 16A(78)-32 stimulation. This includes:
1. the raw data file from Pason in the csv format;
2. a one-page Word document from Pason that explains the headers and units used in their data file;
3. an...
Rose, P. and Barker, B. Energy and Geoscience Institute at the University of Utah
Sep 16, 2022
1 Resources
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1 Resources
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Development of a Downhole Tracer and pH Measurement Instrument for Application in Geothermal Wells
Due the high temperature and pressure conditions found in geothermal wells, tracer studies designed to elucidate properties of geothermal reservoirs are traditionally conducted by pulling liquid samples from the wellhead. These samples are then sent off for analysis in a fixed lab...
Hess, R. et al Sandia National Laboratories
Sep 11, 2013
1 Resources
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1 Resources
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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
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4 Resources
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EGS Collab Experiment 2: Results of Tracer Tests
Multiple sets of tracer tests were conducted at the EGS Collab Testbed 2 on the 4100 L at the Sanford Underground Research Facility (SURF), Lead, SD. The enclosed data package includes: tracer recovery results, water balance calculations and rationales, water flow measurement for ...
Neupane, G. et al Idaho National Laboratory
Jul 26, 2022
5 Resources
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5 Resources
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Development of a Downhole Tool Measuring Real-Time Concentration of Ionic Tracers and pH in Geothermal Reservoirs
For enhanced or Engineered Geothermal Systems (EGS) geothermal brine is pumped to the surface via the production wells, the heat extracted to turn a turbine to generate electricity, and the spent brine re-injected via injection wells back underground. If designed properly, the sub...
Hess, R. et al Sandia National Laboratories
Mar 31, 2014
1 Resources
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1 Resources
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Altona Field Lab Inverse Model WRR 2020
Includes data for measured inert tracer breakthrough curves first reported in Hawkins (2020) (Water Resources Research). In addition, this submission includes the production well temperature measurements first reported in Hawkins et al. (2017a) (Water Resources Research, volume 53...
Tester, J. Cornell University
Jan 01, 2015
3 Resources
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3 Resources
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Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
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3 Resources
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Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
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3 Resources
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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
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3 Resources
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Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
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12 Resources
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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
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11 Resources
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Utah FORGE Well 16A(78)-32 Stage 1 Pressure Falloff Analysis
This is an analysis of the pressure falloff in stage 1 fracture stimulation of FORGE well 16A(78)-32. The objective of this research is to understand the information content of the well stimulation data of FORGE Well 16A(78)-32. The Stage 1 step-rate test, a variant of the classic...
Kazemi, H. et al Colorado School of Mines
Aug 04, 2022
1 Resources
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1 Resources
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Hydrogeologic Windows: Regional Signature Detection for Blind and Traditional Geothermal Play Fairways applied to Southwestern New Mexico
Final Report describing regional signature detection for blind and traditional play fairways as part of Phase I of New Mexico Play Fairway Analysis. This project seeks to reduce exploration risk and identify new prospective targets using available geologic, geochemical, and geophy...
Bielicki, J. et al Los Alamos National Laboratory
Oct 16, 2015
1 Resources
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Utah FORGE Well 16A(78)-32 Stimulation Data (April, 2022)
This is a set of data related to the stimulation program at Utah FORGE well 16A(78)-32 during April, 2022. This includes daily reports, 1 second Pason data, tracer data, and shear stimulation data and information including a report of an evolving prognosis for the stimulation oper...
McLennan, J. Energy and Geoscience Institute at the University of Utah
May 18, 2022
11 Resources
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11 Resources
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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
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100 Resources
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Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
Kelley, M. et al Battelle Memorial Institute
Jun 19, 2023
1 Resources
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Altona, NY EGS Field Site Radon Study
Data include 222Rn activities and complimentary geochemical data for multiple field experiments as part of an EGS project
Brown, S. and Christensen, J. Lawrence Berkeley National Laboratory
Sep 02, 2016
3 Resources
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3 Resources
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Caldwell Ranch Exploration and Confirmation Project, Northwest Geysers, CA: 2011 Geothermal Technologies Peer Review Project Summary
Caldwell Ranch Exploration and Confirmation Project, Northwest Geysers, CA: 2011 Geothermal Technologies Peer Review Project Summary
The Caldwell Ranch Exploration and Confirmation Project was to drill, test, and confirm the present economic viability of the undeveloped geothermal...
Walters, M. Geysers Power Company, LLC
Jan 01, 2011
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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
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3 Resources
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Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...
Marone, C. Pennsylvania State University
May 05, 2021
1 Resources
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Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
Faulds, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
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