Machine Learning/Artificial Intelligence for Seismic Processing
Special Session 6
Wednesday, 29 September 2021, 8:00 a.m.–12:00 p.m. | Denver, ColoradoRooms 405/406/407 - Colorado Convention Center
This session showcases the diagnostic capabilities of near surface geophysics at current and former industrial sites for site characterization and remediation monitoring.
Co-Chairs
- Marianne Rauch
- Muhlis Unaldi
Speakers
- VIDEO Detecting Microseismic Events on DAS Fiber With Super-Human Accuracy:
Fantine Huot, Ariel Lellouch, Paige Given, Robert G. Clapp, and Biondo L. Biondi, Stanford University; Tamas Nemeth and Kurt Nihei, Chevron Technical Center
- Automatic Salt Geometry Update Using Deep Learning in Iterative FWI-RTM Workflows:
Tao Zhao, Chunpeng Zhao, Anisha Kaul, and Aria Abubakar, Schlumberger
- Improved 3D Neural Network Architecture for Fault Interpretation on Field Data:
Enning Wang, Maisha Amaru, Stan Jayr, and Barton Payne, Chevron Technical Center
- Seismic Deblending by Self-Supervised Deep Learning With a Blind-Trace Network:
Shirui Wang, University of Houston; Wenyi Hu, Advanced Geophysical Technology Inc.; Pengyu Yuan and Xuqing Wu, University of Houston; Qunshan Zhang, Prashanth Nadukandi, and German Ocampo Botero, Repsol; Jiefu Chen, University of Houston
- An Innovative Strategy for Seismic Swell Noise Removal Using Deep Neural Networks:
Olga Brusova, Sean Poche, Sribharath Kainkaryam, Alejandro Valenciano, and Arvind Sharma, TGS
- VIDEO Framework and Standalone Applications of Machine Learning in Seismic Processing:
Tony Martin, Bagher Farmani, Morten Pedersen, and Elena Klochikhina, PGS
- VIDEO Machine Learning for Seismic Processing: The Path to Fulfilling Promises:
Song Hou and Jérémie Messud, CGG
Venue
Colorado Convention Center
700 14th St
Denver,
Colorado
80202
United States