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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

USU Camas-1 Test Well: Documentation

Oct 31, 2018
77.61 MB
Publicly accessible
This submission contains documents that describe the USU Camas-1 test well, drilled in Camas Prairie, Idaho, in Fall 2018 and Fall 2019. The purpose of this well is to validate exploration methodologies of the Snake River Plain (SRP) Play Fairway Analysis (PFA) project.
Authors
Shervais, J. Utah State University
geothermalenergyidahocamas prairieusuutah state universitycamas-1test welldrillingwell datasnake river plainsrpblindresourcecharacterizationplay fairway analysispfaidaho department of water resourcesprospectuspermitlithologicgeophysicalgeophysicsconductivityresistivitytemperaturerhyolitegraniteclay-richgougelithologywellboreenvironmentenvironmentalimpactassessmenteawildlifewildlife inventorycultural inventoryseismiccore