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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...
This is a presentation on Integrating Tracer Huff-Puff Tests and Geomechanical Analysis to Measure Evolution of the Fracture Network in EGS Reservoirs by California State University Long Beach, presented by Prof. Matthew Becker. The project is evaluating huff-puff tracer testing, ...
This is a presentation on Integrating Tracer Huff-Puff Tests and Geomechanical Analysis to Measure Evolution of the Fracture Network in EGS Reservoirs by California State University Long Beach, presented by Prof. Matthew Becker. This video slide presentation describes the use of h...
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,...
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...
This is a presentation on Integrated Diagnostics to Interpret Doublet Heat Sweep Efficiency by the Texas Tech University, presented by Smith Leggett. The project is developing integrated fiber-optic sensing, chemical tracer, and numerical modeling approaches to characterize fractu...
This report presents thermal stability testing of fifteen Tracerco water tracers exposed to 250C for 48 hours. Tracer concentrations were compared using HPLC, with samples grouped based on retention time. Three tracers, HTP-001, HTP-002, and HTP-005, retained over 90% of their ori...
This is a presentation on Designing, Characterizing & Optimizing Proppant & Flow Monitoring Materials for a Utah FORGE Engineered Geothermal System by Oklahoma State University, presented by Dr. Mileva Radonjic. This video slide presentation discusses enhanced proppant coatings, z...
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 ...
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...
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...
Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy.
Objective and Purpose:
Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...
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...
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...
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...
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...
This dataset contains the final technical report and closeout presentation for Utah FORGE Project 4-2492, which investigated advanced stimulation design and diagnostic approaches to improve fracture uniformity, inter-well connectivity, and energy recovery efficiency in enhanced ge...
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
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...
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
This submission is a curated geoscience, well and plant-operations data package for the Lightning Dock geothermal field in the Animas Valley, Hidalgo County, south-western New Mexico, a liquid-dominated system produced for binary (ORC) power generation. It covers well-by-well data...
This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of designing a recurrent neural network (RNN) to predict induced seismicity. Background material is included t...
This report discusses the objectives, goals, accomplishments and results of Phase 3B Year 1 of the Utah FORGE project. The report includes infrastructure, seismic monitoring, modelling, external R&D, communications and outreach, data produced, lessons learned, conclusions, and pla...
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 package includes data and models that support hydraulic fracture stimulation and fluid circulation experiments in the Sanford Underground Research Facility (SURF). A paper by Schwering et al. (2020) describes the deterministic basis for developing a "common" discrete fracture...
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