Sergey Fomel

Areas of Expertise

Computational and exploration geophysics; seismic imaging; wave propagation; seismic data analysis; inverse problems; geophysical estimation

Research Locations

Current Research Programs & Projects

Texas Consortium for Computational Seismology ( view )

Best Paper, Interpretation - Society of Exploration Geophysicists (2023)

Honorary Member - Society of Exploration Geophysicists (2022)

Honorary Member - Geophysical Society of Houston (2020)

Distinguished Lecturer - Society of Exploration Geophysicists (2020)

Best Paper, Interpretation - Society of Exploration Geophysicists (2017)

Honorable Mention, Best Poster - Society of Exploration Geophysicists (2015)

Tinker Family BEG Publication Award - Bureau of Economic Geology, The University of Texas at Austin (2014)

Outstanding Educator Award - Jackson School of Geosciences, The University of Texas at Austin (2012)

Conrad Schlumberger Award - European Association of Geoscientists and Engineers (2011)

Best Poster presented at the SEG Annual Meeting - Society of Exploration Geophysicists (2010)

Honorable Mention, Best Poster - Society of Exploration Geophysicists (2007)

Lorand Eotvos Award - European Association of Geoscientists and Engineers (2007)

Best Poster presented at the SEG Annual Meeting - Society of Exploration Geophysicists (2006)

Honorable Mention, Best Paper - Geophysics (2003)

J. Clarence Karcher Award - Society of Exploration Geophysicists (2001)

Guest Associate Editor, Special section on Advances in Mathematical Geophysics, Geophysics (2021 - 2022)

Guest Associate Editor, Special section on Automated Approaches to Interpretation, Interpretation (2021 - 2022)

Member, North American Regional Advisory Committee, Society of Exploration Geophysicists (2021 - Present)

Associate Editor, IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers (2020 - Present)

Member, Education Committee, European Association of Geoscientists and Engineers (2020 - Present)

Chair, Publications Committee, Society of Exploration Geophysicists (2019 - 2021)

Vice President for Publications, Board of Directors, Society of Exploration Geophysicists (2017 - 2019)

Guest Editor, Special issue on Subsurface Exploration in the Information Age, IEEE Signal Processing Magazine (2017 - 2018)

Co-Chair, Technical Program Committee, Society of Exploration Geophysicists (2017)

Guest Associate Editor, Special section on Reproducible Research: Geophysics Papers of the Future, Geophysics (2016 - 2017)

Guest Associate Editor, Special section on Computer-Assisted Seismic Interpretation Methods, Interpretation (2016 - 2017)

Chair, Distinguished Lecturer Committee, Society of Exploration Geophysicists (2015 - 2017)

Guest Associate Editor, Special section on Thin Beds, Interpretation (2014 - 2015)

Guest Associate Editor, Special issue on Signal and Noise Separation, Geophysics (2014 - 2015)

Chair, Publications Committee, Society of Exploration Geophysicists (2013 - 2015)

Guest Associate Editor, Special section on Diffraction Imaging, Interpretation (2013 - 2015)

Member, Distinguished Lecturer Committee, Society of Exploration Geophysicists (2012 - Present)

Chair, Technical Program Committee, Society of Exploration Geophysicists (2011)

District Representative, Council, Society of Exploration Geophysicists (2011 - 2013)

Guest Editor, Special issue on Seismic Imaging, International Journal of Geophysics (2010 - 2011)

Guest Associate Editor, Special issue on Seismic Data Sampling, Geophysics (2009 - 2010)

Guest Editor, Special issue on Reproducible Research, Computing in Science and Engineering (2008 - 2009)

District Representative, Council, Society of Exploration Geophysicists (2008 - 2011)

Member, Publications Committee, Society of Exploration Geophysicists (2008 - 2021)

Member, Technical Program Committee, Society of Exploration Geophysicists (2007)

Chair, Translations Committee, Society of Exploration Geophysicists (2007 - 2010)

Associate Editor, Seismic Migration and Signal Processing, Geophysics (2004 - 2009)

Creator and Project Manager, Madagascar, an open-source software package for geophysical data analysis (2003 - Present)

Creator and Project Manager, SEGTeX, an open-source LaTeX package for geophysical publications (2001 - Present)

Postdocs

Xinming Wu, 2016 - 2019, Colorado School of Mines
Professor at the University of Science and Technology of China

Tieyuan Zhu, 2014 - 2016, Stanford University
Assistant Professor at the Pennsylvania State University

Mark Lai, 2014 - 2017, University of Maryland, College Park
Data Scientist at IntegraFEC

Hejun Zhu, 2013 - 2015, Princeton University
Associate Professor at the University of Texas at Dallas

Mehdi Far, 2013 - 2014, University of Houston
Principal Scientist at Halliburton

Alexander Klokov, 2011 - 2013, Gubkin University of Oil and Gas
Lead Scientific Developer at Factor Technology

Jingwei Hu, 2011 - 2014, University of Wisconsin-Madison
Associate Professor at Purdue University

Hesam Kazemeini, 2010 - 2011, Uppsala University
Geophysicist at ION

Roman Kazinnik, 2009 - 2010, Tel-Aviv University
Lead Data Scientist at Brighthouse Financial

Yang Liu, 2007 - 2010, Jilin University
Professor at Jilin University

Jules Browaeys, 2006 - 2009, Institut de Physique du Globe
Geophysicist at Total E&P

Graduate Students

Akshika Rohatgi , Ph.D., expected 2028 (Supervisor)

Shuhua Hu , Ph.D., expected 2025 (Committee Member)
I am a PhD Candidate in computational geophysics, interested in using numerical methods, scientific computing and machine learning to solve large-scale geophysical inverse problems. My previous experience includes land seismic data processing, seismic imaging R&D for anisotropic media.

Ben Gremillion (Supervisor)

Héctor Antonio Corzo Pola (Supervisor)

Shirley T Mensah (Supervisor)
Shirley Mensah completed her BS in Geology and Professional Science Master's in Geographic Information Science and Cartography from Eastern Illinois University. After her graduation, she worked with various companies like Apple and Nicor Gas as a GIS Technician and Geospatial Analyst. Currently, she is a Ph.D. student working with Professor Sergey Fomel, and her interest includes machine learning and its...

Sabrina A Reichert (Supervisor)

Zhicheng Geng, Ph.D., 2022 (Supervisor)
(Currently at Amazon) Deep learning for pattern recognition in seismic reflection data

Hapreet Kaur, Ph.D., 2022 (Supervisor)
(Currently at Amazon) Improving accuracy and efficiency of seismic data analysis using deep learning

Nam Pham, Ph.D., 2022 (Supervisor)
Jackson School of Geosciences
(Currently at Schlumberger): Deep learning for automatic geophysical interpretation with uncertainty quantification

Luke Decker, Ph.D., 2021 (Supervisor)
Computational Science, Engineering, and Mathematics
(Currently at Chevron) Parameter selection in seismic data analysis problems

Yunzhi Shi, Ph.D., 2020 (Supervisor)
(Currently at Amazon) Deep learning empowers the next generation of seismic interpretation

Zhiguang Xue, Ph.D., 2018 (Supervisor)
(Currently a CGG): Regularization strategies for increasing efficiency and robustness of least-squares RTM and FWI

Dmitrii Merzlikin, Ph.D., 2018 (Supervisor)
(Currently at Schlumberger): Diffraction imaging by path-summation migration

Yanadet Sripanich, Ph.D., 2017 (Supervisor)
(Currently at PTTEP): Seismic anisotropy analysis using Muir-Dellinger parameters

Mason Phillips, M.S., 2017 (Supervisor)
(Currently at DownUnder GeoSolutions): Geophysical data registration using modified plane-wave destruction filters

Junzhe Sun, Ph.D., 2016 (Supervisor)
(Currently at Meta): Seismic modeling and imaging in complex media with low-rank approximation

Kelly Regimbal, M.S., 2016 (Supervisor)
(Currently at ExxonMobil): Improving resolution of NMO stack using shaping regularization

Parvaneh Karimi, Ph.D., 2015 (Supervisor)
(Currently at Oxy): Seismic interpretation using predictive painting

Yangkang Chen, Ph.D., 2015 (Supervisor)
(Currently at UT Austin): Noise attenuation in seismic data from the simultaneous-source acquisition

Ryan Swindeman, M.S., 2015 (Supervisor)
(Currently at Enthought): Iterative seismic data interpolation using plane-wave shaping

Vladimir Bashkardin, Ph.D., 2014 (Supervisor)
(Currently at BP): Phase-space imaging of reflection seismic data

Siwei Li, Ph.D., 2014 (Supervisor)
(Currently at Chevron): Imaging and velocity model building with linearized eikonal equation and upwind finite-differences

Shaunak Ghosh, M.S., 2013 (Supervisor)
(Currently at CGG): Multiple suppression in the t-x-p domain

Xiaolei Song, Ph.D., 2012 (Supervisor)
(Currently at BP): Application of Fourier finite differences and lowrank approximation method for seismic modeling and subsalt imaging

Salah Al-Hadab, M.S., 2012 (Supervisor)
(currently at Saudi Aramco): Diffraction imaging of sediment drifts in Canterbury Basin

Yihua Cai, M.S., 2012 (Supervisor)
(currently at Shell): Spectral recomposition and multicomponent seismic image registration

William Burnett, Ph.D., 2011 (Supervisor)
(currently at ExxonMobil): Multiazimuth velocity analysis using velocity-independent seismic imaging

Undergraduate Students

Reem Alomar, B.S., 2022
(Currently at Saudi Aramco): Seismic data analysis by least-squares non-stationary triangle smoothing

Tharit Tangkijwanichaku, B.S., 2021
(Currently at PTTEP): Chain of operators for inverse Hessian estimation in least-squares migration

Sarah Greer, B.S., 2018
(Currently at MIT): A data matching algorithm and its applications in seismic data analysis

Lubna Barghouty, B.S., 2013
(Currently at MIT): Surface-related multiple elimination and velocity-independent imaging of a 2D seismic line from the Viking Graben dataset

Yanadet Sripanich, B.S., 2013
(Currently at PTTEP): An efficient algorithm for two-point seismic ray tracing

Year	Semester	Course
2024	Spring	GEO 365N	Seismic Data Processing
2024	Spring	GEO 384S	Seismic Data Processing
2024	Spring	GEO 398D	2-App Data Anly/Vis/Mchn Lrng
2023	Fall	GEO 383D	Num Meth I: Comp Meth Geol Sci
2023	Fall	GEO 325K	Computational Methods
2023	Spring	GEO 391	Machine Learning Applicatns
2022	Fall	GEO 384H	Multidimnsnl Data Anlys In Geo
2022	Spring	GEO 365N	Seismic Data Processing
2022	Spring	GEO 384S	Seismic Data Processing
2022	Spring	GEO 391	Machine Learning Applicatns
2021	Spring	GEO 365N	Seismic Data Processing-Wb
2021	Spring	GEO 384S	Seismic Data Processing-Wb
2021	Spring	GEO 391	Machine Learning Applicatns-Wb
2020	Fall	GEO 384H	Multidimnsnl Data Anlys-Wb
2019	Fall	GEO 366M	Mathematical Meths In Geophys
2019	Fall	GEO 380J	Math Mthds In Geophys
2019	Fall	GEO 384W	Seismic Imaging
2018	Fall	GEO 384H	Multidimnsnl Data Anlys In Geo
2018	Spring	GEO 384S	Seismic Data Processing
2018	Spring	GEO 394	Rsch In Geological Sciences
2018	Spring	GEO 365N	Seismic Data Processing
2017	Fall	GEO 394	Rsch In Geological Sciences
2017	Spring	GEO 365N	Seismic Data Processing
2017	Spring	GEO 384S	Seismic Data Processing
2017	Spring	GEO 394	Rsch In Geological Sciences
2016	Fall	GEO 394	Rsch In Geological Sciences
2016	Fall	GEO 384H	Multidimnsnl Data Anlys In Geo
2016	Spring	GEO 365N	Seismic Data Processing
2016	Spring	GEO 384S	Seismic Reflection Processing
2016	Spring	GEO 394	Rsch In Geophysics
2015	Fall	GEO 394	Rsch In Geological Sciences
2015	Spring	GEO 394	Rsch In Geophysics
2014	Fall	GEO 394	Rsch In Geophysics
2014	Fall	GEO 366M	Mathematical Meths In Geophys
2014	Fall	GEO 391	Multidimensional Data Analysis
2014	Spring	GEO 394	Rsch In Geophysics

Graduate Positions

Graduate research opportunities in computational seismology
Texas Consortium for Computational Seismology is looking for Ph.D. students interested in computational research. Our group works on a broad range of topics in exploration geophysics, from wave-equation seismic imaging and inversion to computational algorithms for seismic data processing and seismic interpretation. The work is supported by industrial sponsors. We use open-source software tools and high-performace computing resources.

Undergraduate Positions

Analyzing seismic data using machine learning techniques
Seismic recordings are used to detect earthquakes and to create images of the Earth’s interior. Seismic data contain rich patterns that can be discovered for extracting detailed information. Newly developed machine learning techniques aid in the discovery process. Deep learning has been used to detect arrivals of seismic signals from earthquakes and volcano eruptions and to extract from subsurface images such features, as faults, channels, salt bodies, etc. In detecting geological features, computational algorithms prove to be as powerful or even more powerful than the human eye, especially in higher dimensions.

In this project, we are adopting the latest ideas from the field of machine learning and artificial intelligence to improve the resolution ability of seismic images. Our objective is to advance the state of the art in discovering seismic data patterns. The approaches include unsupervised learning for analyzing seismic waveforms and compressing data in the transformed domain and supervised learning for teaching the computer how to imitate the work of human interpreters.

We are seeking an enthusiastic student to participate in this project. The student will develop data-analysis skills and contribute to an open-source software project. Some prior familiarity with seismology and machine learning, as well as some prior experience with computer programming using Python are helpful but not required

Madagascar
Madagascar is an open-source software package for multidimensional data analysis and reproducible computational experiments. Its mission is to provide a convenient and powerful environment and a convenient technology transfer tool for researchers working with digital image and data processing in geophysics and related fields.

Texas Consortium for Computational Seismology
The Texas Consortium for Computational Seismology is a joint initiative of the Bureau of Economic Geology (BEG) and the Center for Numerical Analysis at the Institute for Computational Engineering and Science (ICES) at The University of Texas at Austin. Its mission is to address the most important and challenging research problems in computational geophysics as experienced by the energy industry while educating the next generation of research geophysicists and computational scientists.