- Ph.D., 2016-2021
- 毕业去向: 南昌组织部
- GitHub: ssyan33
- Email: ssyan33@mail.ustc.tsg211.com
- Undergraduate: Geophysics, Jilin University, 2012-2016.
- Experience: Cloud Computing Engineer, Summer Intern, Huawei, 2020.
- Research: automatic seismic horizon interpretation, deep learning for seismic impedance inversion, and optimized seismic interpretation workflows.
Publication
7. Yan, S., X. Sun, X. Wu*, S. Zhang, and H. Si, 2021, Building subsurface models with horizon-guided interpolation and deep learning: applied to the Volve field data. Geophysics, Vol. 87(4), B233–B245.6. Wu, X.*, S. Yan, Z. Bi, S. Zhang, and H. Si, 2021, Deep learning for multi-dimensional seismic impedance inversion. Geophysics, Vol. 86(5), R735–R745.
5. Zhang, S., H. Si, X. Wu*, and S. Yan, 2020, A comparison of deep learning methods for seismic impedance inversion. Petroleum Science, Vol. 19(3), 1019-1030.
4. Yan, S. and X. Wu*, 2021, Seismic horizon extraction with dynamic programming. Geophysics, Vol. 86(2), A15-W19.
3. Wu, X., S. Yan, J. Qi, and H. Zeng, 2020, Deep learning for characterizing paleokarst collapse features in 3D seismic images. JGR Solid Earth, Vol. 125 (9), doi: 10.1029/2020JB019685.
2. Yan, S., and X. Wu*, 2020, Seismic horizon refinement with dynamic programming. 90th Annual Meeting of the Society of Exploration Geophysics , Expanded Abstracts.
1. Yan. S and J. Zhang, 2017, Comparison of stacking methods with a depth model or with a RMS velocity for automated microseismic event location from surface monitoring. SEG Workshop, Microseismic Technologies and Applications.
Miniposter
