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Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Utah FORGE 3-2418: Wellbore Fracture Imaging Using Inflow Detection 2024 Annual Workshop Presentation
This is a presentation on the Wellbore Fracture Imaging Using Inflow Detection by Stanford University and Sandia National Laboratory, presented by Roland Horde. This is a video presentation on wells, both before and after stimulation, using chloride or other ions to map fractures ...
Horne, R. and Schneider, M. Energy and Geoscience Institute at the University of Utah
Sep 13, 2024
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
MT Data: Newberry 4D Monitoring EGS Project
This submission contains a link to the EDX Collaborative Workspace where the MT data collected in support of the DOE GTO 4D EGS monitoring project is stored.
Daily production reports- Oregon State University (OSU) had 6 stations running continuously.
--Dynamic survey map, KML f...
Rose, K. National Energy Technology Laboratory
Apr 12, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
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
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
0 Stars
Curated
136 Resources
0 Stars
Curated
EGS Collab Experiment 1: Earth Model Input Files
The EGS Collab is conducting experiments in hydraulic fracturing at a depth of 1.5 km in the Sanford Underground Research Facility (SURF) on the 4850 Level. A total of eight ~60m-long subhorizontal boreholes were drilled at that depth on the western rib of the West Access Drift. S...
Neupane, G. and Sigma-V, T. Idaho National Laboratory
Dec 19, 2019
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 2: Continuous Broadband Seismic Waveform Data
Two broadband seismometers were installed on the 4100 level and recorded for the duration of EGS Collab Experiment #2. Inspired by published data from similar instruments installed in the Aspo Hard Rock Lab, these long-period instruments aimed to measure the tilting of the drift i...
Rodriguez Tribaldos, V. Lawrence Berkeley National Laboratory
Sep 12, 2022
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible