Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
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 friction experiments reported here were performed in a double-direct shear (DDS) configuration in a biaxial testing apparatus in the Penn State Rock Mechanics laboratory. In addition to mechanical data acquisition, all experiments were instrumented with an ultrasonic acoustic monitoring system. Both mechanical data and ultrasonic data from experiments p5270 and p5721 are available in this submission.
Citation Formats
Pennsylvania State University. (2021). Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments [data set]. Retrieved from https://gdr.openei.org/submissions/1309.
Marone, Chris. Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments. United States: N.p., 05 May, 2021. Web. https://gdr.openei.org/submissions/1309.
Marone, Chris. Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments. United States. https://gdr.openei.org/submissions/1309
Marone, Chris. 2021. "Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments". United States. https://gdr.openei.org/submissions/1309.
@div{oedi_1309, title = {Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments}, author = {Marone, Chris.}, abstractNote = {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 friction experiments reported here were performed in a double-direct shear (DDS) configuration in a biaxial testing apparatus in the Penn State Rock Mechanics laboratory. In addition to mechanical data acquisition, all experiments were instrumented with an ultrasonic acoustic monitoring system. Both mechanical data and ultrasonic data from experiments p5270 and p5721 are available in this submission.}, doi = {}, url = {https://gdr.openei.org/submissions/1309}, journal = {}, number = , volume = , place = {United States}, year = {2021}, month = {05}}
Details
Data from May 5, 2021
Last updated Jun 8, 2021
Submitted May 5, 2021
Organization
Pennsylvania State University
Contact
Chris Marone
Authors
Keywords
geothermal, energy, Seismic, Active source, Laboratory, Friction experiment, ultrasonic, geophysics, microseismicity, lab data, raw data, waveforms, mechanical data, preprocessed, MATLAB, acoustics, acoustic, biaxial testing apparatus, ultrasonic acoustic monitoring system, machine learning, deep learning, AI, artificial intelligence, seismic forecasting, earthquake forecasting, faultDOE Project Details
Project Name Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties
Project Lead Mike Weathers
Project Number EE0008763