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Fallon FORGE: Distinct Element Reservoir Modeling
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...
Blankenship, D. et al Sandia National Laboratories
Mar 12, 2018
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2 Resources
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
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...
Marone, C. et al Pennsylvania State University
May 14, 2021
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3 Resources
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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
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2 Resources
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