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Utah FORGE 5-2419: Final Report and Presentation on Seismicity Permeability Relationships Probed via Nonlinear Acoustic Imaging

Sep 30, 2025
254.88 MB
Publicly accessible
This submission contains the final technical report and closeout presentation for Utah FORGE Project 5-2419, which investigates the coupled evolution of permeability and induced seismicity in enhanced geothermal systems using laboratory experiments, field observations, and nonline...
Authors
Elsworth, D. Pennsylvania State University
geothermalenergyutah forgeegspermeabilityinduced seismicitylaboratory experimentsfield observationsnonlinear acoustic imagingfault reactivationreservoir rockmicroearthquakestimulationphysics informed modelingmachine learningseismic momentstress statepermeability creationseismic hazardtechnical reportgeomechanicsgeophysicsmicroseismicity

Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

May 05, 2021
Size unavailable
Publicly accessible
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...
Authors
Marone, C. Pennsylvania State University
geothermalenergyseismicactive sourcelaboratoryfriction experimentultrasonicgeophysicsmicroseismicitylab dataraw datawaveformsmechanical datapreprocessedmatlabacousticsacousticbiaxial testing apparatusultrasonic acoustic monitoring systemmachine learningdeep learningaiartificial intelligenceseismic forecastingearthquake forecastingfault

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

May 14, 2021
6.01 MB
Publicly accessible
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...
Authors
Marone, C. et al Pennsylvania State University
geothermalenergymatlabgeophysicsseismiccodeprocessed datamicroseismicityaiartificial intelligencedeep learningmachine learningacousticsacoustic emissionsseismic forcastingseismic predictionfaultfault propertiesshear stresstime to failureexperimentexperimental datalab databiaxial shear experimentbiaxial shear apparatusfriction