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Utah FORGE: Well 58-32 Stimulation Data

Pressure, temperature, and flow data from open-hole, upper perforation, and lower perforation well stimulations gathered from various tools collected at well 58-32 during phase 2C.

Best, S. Geothermal Resource Group

Apr 20, 2019
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Utah FORGE: Well 58-32 Stimulation Conference Paper and Data

The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...

Best, S. Energy and Geoscience Institute at the University of Utah

Apr 24, 2019
2 Resources
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Newberry EGS Demonstration: Well 55-29 Stimulation Data 2014

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ru...

Cladhouhos, T. et al AltaRock Energy Inc

Sep 03, 2015
54 Resources
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Wister, CA Downhole and Seismic Data

This submission contains Downhole geophysical logs associated with Wister, CA Wells 12-27 and 85-20. The logs include Spontaneous Potential (SP), HILT Caliper (HCAL), Gamma Ray (GR), Array Induction (AIT), and Neutron Porosity (NPOR) data. Also included are a well log, Injection T...

Akerley, J. Ormat Nevada Inc

Dec 18, 2010
16 Resources
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Dataset and SUTRA model used to evaluate Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon.

This is a link to the open access, published dataset and modeling that supports a feasibility study of Reservoir Thermal Energy Storage (RTES) in the Portland Basin, Oregon, USA. Citation: Burns, E.R., 2020, SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs f...

Bershaw, J. et al Portland State University

Jun 29, 2020
2 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
6 Resources
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Newberry EGS Demonstration: Well 55-29 Stimulation Data

The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ...

T., T. AltaRock Energy Inc

Dec 08, 2012
136 Resources
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Curated

Utah FORGE: Well 82-33 Logs and Data, Roosevelt Hot Spring Area

This is a compilation of logs and data from Well 82-33 in the Roosevelt Hot Springs area in Utah. This well is also in the Utah FORGE study area. The file is in a compressed .zip format and there is a data inventory table (Excel spreadsheet) in the root folder that is a guide to t...

Moore, J. Energy and Geoscience Institute at the University of Utah

Mar 03, 2016
1 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

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...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
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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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