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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...
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...
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,...
This archive contains data from the tracer test performed during the Utah FORGE well 16A(78)-32 stimulation. This includes: the raw data file from Pason in the csv format, a one-page Word document from Pason that explains the headers and units used in their data file, an Excel spr...
This dataset includes results and supporting documentation from tracer tests conducted in 2024 at Utah FORGE. The tests involved injecting nanoparticle tracers into injection well 16A(78)-32 and monitoring their recovery in production well 16B(78)-32 to assess hydraulic connectivi...
This dataset contains tracer test results from stimulation and circulation experiments conducted on the Utah FORGE wells 16A(78)-32 and 16B(78)-32 during 2024. The data was collected by RESMAN Energy Technology and includes detailed tracer analysis from flowback, short and extende...
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...
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...
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
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 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 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 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...
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
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...
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Archive containing input/output data for distinct element reservoir modeling for Fallon FORGE. Models created using 3DEC, InSite, and in-house Python algorithms (ITASCA). List of archived files follows; please see 'Modeling Metadata.pdf' (included as a resource below) for addition...
Plugging of fracture porosity from mineral precipitation due to injecting cold water into a a geothermal reservoir can impact the overall permeability of the fracture network in the reservoir. This can have serious ramifications on the efficiency of the geothermal resource. Geoche...
This submission contains pressure and flow time series data from the reservoir testing of Well 58-32. These activities were part of the Utah FORGE Phase 2B site suitability confirmatory testing.
Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...
This is a presentation on the Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Professor. The project's objective was to develop a methodology ...
This is a final report summarizing a two-year (2014-16) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and ...
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