S053
Extracting Information from Geophysical Signals with Machine Learning V Posters

Tuesday, 15 December 2020: 04:00-20:59
Poster
Primary Convener:  Ting Chen, Los Alamos National Laboratory, Los Alamos, NM, United States
Conveners:  Laura J Pyrak-Nolte, Purdue University, Department of Physics and Astronomy; Department of Earth, Atomospheric and Planetary Sciences; Lyles School of Civil Engineering, West Lafayette, IN, United States, Paul A Johnson, Los Alamos National Laboratory, Earth and Environmental Sciences: Geophysics (EES-17), Los Alamos, NM, United States and Gregory C Beroza, Stanford University, Department of Geophysics, Stanford, CA, United States
Primary Liaison:  Ting Chen, Los Alamos National Laboratory, Los Alamos, NM, United States
Chairs:  Ting Chen, Los Alamos National Laboratory, Los Alamos, NM, United States and Gregory C Beroza, Stanford University, Department of Geophysics, Stanford, CA, United States
OSPA Liaison:  Xiaofei Ma, Los Alamos National Laboratory, Los Alamos, NM, United States
 
Predict arrival time of acoustic emissions on a laboratory fault without the velocity model (673838)
Qi Zhao, The Hong Kong Polytechnic University, Hong Kong, China; University of California Berkeley, Berkeley, CA, United States, Qinya Liu, University of Toronto, Toronto, ON, Canada and Steven D Glaser, University of California, Berkeley, United States
 
Forecasting Induced Seismicity in Oklahoma using Machine Learning Methods (745877)
Yan Qin1,2, Ting Chen2 and Xiaofei Ma2, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)Los Alamos National Laboratory, Los Alamos, NM, United States
 
Accelerated target-oriented least-squares reverse time migration using optimal mini-batches of shots (743510)
Janaki Vamaraju, Shell Global Solutions International, Rijswijk Zh, Netherlands, Ram Tuvi, University of Texas at Austin, Austin, United States, Zeyu Zhao, Institute for Geophysics, University of Texas Austin, Austin, TX, United States and Mrinal K Sen, Univ Texas Inst Geophysics, Austin, TX, United States
 
Fully Non-linear Seismic Tomography using Normalizing Flows (706382)
Xuebin Zhao, University of Edinburgh, School of Geosciences, Edinburgh, EH9, United Kingdom, Andrew Curtis, University of Edinburgh, Edinburgh, United Kingdom and Xin Zhang, University of Edinburgh, Edinburgh, EH9, United Kingdom
 
Introducing machine learning methods to Geothermal Play Fairway Analysis in the Great Basin region of Nevada (673348)
Connor Smith, University of Nevada Reno, Geophysics, Reno, NV, United States, James E Faulds, University Nevada, Reno, Reno, NV, United States, Mark F Coolbaugh, Dajin Resources Corp., 450-789 West Pender Street, Vancouver, BC, Canada and Stephen Brown, Massachusetts Institute of Technology, Cambridge, United States
 
Joint facies and reservoir properties estimation by trans-dimensional seismic inversion using machine learning based priors (727264)
Arnab Dhara, Austin, Texas, United States and Mrinal K Sen, Univ Texas Inst Geophysics, Austin, TX, United States
 
Kinematics of Mw6.2 24/August/2016, Amatrice earthquake inferred from the novel fuzzy inversion method (725639)
Navid Kheirdast, International Institute of Earthquake Engineering and Seismology, Seismology, Tehran, Iran, Anooshiravan Ansari, International Institute of Earthquake Engineering and Seismology, Tehran, Iran and Susana Custodio, IDL - Instituto Dom Luiz, Lisboa, Portugal
 
Machine Learning-Based Tomography of the Ridgecrest Region (766843)
Zheng Zhou1, Peter Gerstoft2, Michael Joseph Bianco1 and Kim Bak Olsen3, (1)University of California San Diego, La Jolla, CA, United States, (2)Univ of California San Diego, San Diego, CA, United States, (3)San Diego State Univ, San Diego, CA, United States
 
Nuclear Blast Discrimination using a Convolutional Neural Network (750376)
Louisa Barama, Georgia Institute of Technology Main Campus, Atlanta, GA, United States, Jesse Williams, Global Technology Connection Inc., Atlanta, GA, United States, Zhigang Peng, Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, United States and Andrew Vern Newman, Georgia Tech, Atlanta, GA, United States
 
The Identification of the snowfall cloud at Syowa Station, Antarctica (715147)
Kazue Suzuki, Hosei University, Department of Applied Informatics, Faculty of Science and Engineering, Tokyo, Japan, Masaki Shimomura, Meiji University, Graduate School of Advanced Mathematical Sciences, Tokyo, Japan, Kazuyuki Nakamura, Meiji University, School of Interdisciplinary Mathematical Sciences, Tokyo, Japan, Naohiko Hirasawa, National Institute of Polar Research, Tokyo, Japan, Takashi Yamanouchi, Natl Inst Polar Research, Tokyo, Japan and Terumasa Tokunaga, Kyushu Institute of Technology, Department of Systems Design and Informatics, Faculty of Computer Science and Systems Engineering, Iizuka, Japan
 
One-Dimensional Seismic Inversion using Machine Learning techniques (661408)
Prajjwal Singh, Divakar Vashisth and Abhinav Pratap Singh, Indian School of Mines, Dhanbad, India
 
A recurrent neural network approach to characterize the postseismic deformation of the 2011 Tohoku‐Oki Earthquake (667877)
Norifumi Yamaga, Shizuoka University, Shizuoka, Japan and Yuta Mitsui, Shizuoka University, Geosciences, Shizuoka, Japan
 
Converting Smaller Seismic Arrays to Larger-N Synthetic-Aperture Arrays Using Deep Learning (699821)
Weichen Xu, Purdue University, Dept. of Electrical and Computer Engineering, West Lafayette, IN, United States and Robert L Nowack, Purdue University, Dept. of Earth Atmospheric and Planetary Sci., West Lafayette, IN, United States
 
Deep Learning for Ground Penetrating Radar Velocity Inversion (687248)
Zi Xian Leong, Pennsylvania State University Main Campus, Department of Geosciences, University Park, PA, United States and Tieyuan Zhu, Pennsylvania State University, Department of Geosciences, University Park, PA, United States
 
Estimating geodetic locking depth and long-term slip rate along the central San Andreas Fault using Neural Networks (687197)
Shaparak Salek, California State University Northridge, Northridge, CA, United States and Eileen L Evans, Harvard University, Earth and Planetary Sciences, Cambridge, MA, United States
 
Study on the Parameterization Response of Probabilistic Neural Networks for Seismic Facies Classification (683452)
Diana Katerine Salazar Florez, University of Oklahoma Norman Campus, Norman, OK, United States and Heather Bedle, University of Oklahoma, School of Geoscienes, Norman, OK, United States
 
Use Machine Learning to Remove Reverberations on Receiver Functions Caused by a Low-velocity Sedimentary Layer (675686)
Yanwei Zhang, Missouri University of Science and Technology, Rolla, MO, United States and Stephen S Gao, Missouri University of Science and Technology, Geology and Geophysics Program, Rolla, MO, United States
 
Using seismic gradiometry and machine learning to discriminate between explosion and earthquake seismic sources (681333)
Christian Poppeliers, Sandia National Laboratories, Albuquerque, NM, United States, Cristian Challu, Carnegie Mellon University, Auton Lab, Pittsburg, PA, United States, Predrag Punosevac, Carnegie Mellon University, Auton Lab, Pittsburg, United States, Charlie Vollmer, Sandia National Laboratories, Machine Intelligence, Albuquerque, United States and Artur Dubrawski, Carnegie Mellon University, Auton Lab, Pittsburgh, United States
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