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Engineering and Technology

D-Index
74
Citations
19785
World Ranking
815
National Ranking
284

Overview

Sergey Fomel is affiliated with The University of Texas at Austin in the United States. Their research spans several intersecting fields with a primary focus on Earth and Planetary Sciences, Engineering, and Computer Science. Within these domains, they have contributed extensively to subfields including Geophysics, Ocean Engineering, Artificial Intelligence, Mechanical Engineering, and Computer Vision and Pattern Recognition.

The main topics of Fomel's work cover a broad spectrum involving seismic processes and computational methods. Notable topics include:

  • Seismic Imaging and Inversion Techniques
  • Seismic Waves and Analysis
  • Seismology and Earthquake Studies
  • Geophysical Methods and Applications
  • Drilling and Well Engineering
  • Hydraulic Fracturing and Reservoir Analysis
  • Image and Signal Denoising Methods

The recent papers associated with Sergey Fomel demonstrate active research in seismic and geophysical applications enhanced by deep learning techniques. Selected publications include:

  • "Seismic data interpolation using deep learning with generative adversarial networks," 2020, Geophysical Prospecting
  • "Deep learning for relative geologic time and seismic horizons," 2020, Geophysics
  • "Seismic ground-roll noise attenuation using deep learning," 2020, Geophysical Prospecting
  • "Improving the resolution of migrated images by approximating the inverse Hessian using deep learning," 2020, Geophysics
  • "SCALODEEP: A Highly Generalized Deep Learning Framework for Real-Time Earthquake Detection," 2021, Journal of Geophysical Research Solid Earth

Frequent coauthors in Fomel's work indicate collaboration with several researchers, including:

  • Yangkang Chen
  • Omar M. Saad
  • Alexandros Savvaidis
  • Nam Pham
  • Liuqing Yang

The venues where Sergey Fomel most frequently publishes reflect the interdisciplinary nature of their research. These venues are:

  • Geophysics
  • IEEE Transactions on Geoscience and Remote Sensing
  • Second International Meeting for Applied Geoscience & Energy
  • Geophysical Prospecting
  • Seismological Research Letters

Through a combination of geophysical methods and artificial intelligence, Sergey Fomel's research addresses complex challenges related to seismic imaging, noise attenuation, and earthquake detection. Their publication record and coauthor network indicate ongoing contributions to both fundamental geoscience and applied engineering problems.

Best Publications

  • Applications of plane-wave destruction filters

    Sergey Fomel

  • FaultSeg3D: Using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation

    Xinming Wu;Luming Liang;Yunzhi Shi;Sergey Fomel

  • Angle-domain common-image gathers by wavefield continuation methods

    Paul C. Sava;Sergey B Fomel

  • Shaping regularization in geophysical-estimation problems

    Sergey Fomel

  • Seislet transform and seislet frame

    Sergey Fomel;Yang Liu

  • Local seismic attributes

    Sergey B Fomel

  • Time-shift imaging condition in seismic migration

    Paul Sava;Sergey B Fomel

  • Seismic wave extrapolation using lowrank symbol approximation

    Sergey B Fomel;Lexing Ying;Xiaolei Song

  • Poststack velocity analysis by separation and imaging of seismic diffractions

    Sergey B Fomel;Evgeny Landa;M. Turhan Taner

  • Random noise attenuation using local signal-and-noise orthogonalization

    Yangkang Chen;Sergey B Fomel

  • Madagascar: open-source software project for multidimensional data analysis and reproducible computational experiments

    Sergey Fomel;Paul Sava;Ioan Vlad;Yang Liu

  • Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization

    Yangkang Chen;Sergey B Fomel;Jingwei Hu

  • Double Sparsity Dictionary for Seismic Noise Attenuation

    Yangkang Chen;Jianwei Ma;Sergey B Fomel

  • Seismic reflection data interpolation with differential offset and shot continuation

    Sergey B Fomel

  • Separation and imaging of seismic diffractions using migrated dip-angle gathers

    Alexander Klokov;Sergey B Fomel

  • Building realistic structure models to train convolutional neural networks for seismic structural interpretation

    Xinming Wu;Zhicheng Geng;Yunzhi Shi;Nam Pham

  • Fast sweeping method for the factored eikonal equation

    Sergey Fomel;Songting Luo;Hongkai Zhao

  • Separation, Imaging, And Velocity Analysis of Seismic Diffractions Using Migrated Dip-angle Gathers

    Evgeny Landa;Sergey B Fomel;Moshe Reshef

  • SaltSeg: Automatic 3D salt segmentation using a deep convolutional neural network

    Yunzhi Shi;Xinming Wu;Sergey Fomel

  • Stacking seismic data using local correlation

    Guochang Liu;Sergey Fomel;Long Jin;Xiaohong Chen

  • Guest Editors' Introduction: Reproducible Research

    S. Fomel;J.F. Claerbout

  • On anelliptic approximations for qP velocities in VTI media

    Sergey Fomel

  • Seismic imaging of incomplete data and simultaneous-source data using least-squares reverse time migration with shaping regularization

    Zhiguang Xue;Yangkang Chen;Sergey B Fomel;Junzhe Sun

Frequent Co-Authors

Paul Sava
Paul Sava Colorado School of Mines
Yangkang Chen
Yangkang Chen The University of Texas at Austin
Lexing Ying
Lexing Ying Stanford University
Biondo Biondi
Biondo Biondi Stanford University
Mrinal K. Sen
Mrinal K. Sen The University of Texas at Austin
James A. Sethian
James A. Sethian University of California, Berkeley
Mirko van der Baan
Mirko van der Baan University of Alberta
Christopher Juhlin
Christopher Juhlin Uppsala University
Hongliu Zeng
Hongliu Zeng The University of Texas at Austin
Omar Ghattas
Omar Ghattas The University of Texas at Austin

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