Presentations

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Machine Learning/Artificial Intelligence for Seismic Processing

Special Session 6

Wednesday, 29 September 2021, 8:00 a.m.–12:00 p.m.  |  Denver, Colorado

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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

Rooms 405/406/407

Venue

Machine Learning/Artificial Intelligence for Seismic Processing
Colorado Convention Center
700 14th St
Denver, Colorado 80202
United States

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