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Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
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...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
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4 Resources
0 Stars
Publicly accessible
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
3 Resources
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3 Resources
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Utah FORGE: Friction-Permeability-Seismicity Laboratory Experiments with Non-Linear Acoustics
Laboratory experimental data on saw-cut interface of Westerly Granite and Utah Forge granitoid rocks. Experiments include velocity-stepping and fluid pressure stepping experiments. Mechanical data from 3 ISCO pumps connected to a Temco pressure vessel measure axial, confining and ...
Eijsink, A. and Elsworth, D. Pennsylvania State University
Jul 08, 2022
2 Resources
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2 Resources
0 Stars
Publicly accessible