Personal data

Name: Xintao Chai

Present Position: Lecturer, China University of Geosciences (Wuhan), Faculty of Institute of Geophysics and Geomatics (IGG), Department of Applied Geophysics, the Director of the Consortium for Seismic Data Processing (CSDP), the OpenGEO Group, and the Team of Geophysics-steered Machine Learning for Wave Propagation and Imaging (GSML4WPI)

E-mail: xtchai@126.com

(Date of birth: December 7, 1987; Citizenship: Chinese)

Address: No. 388 Lumo Road,Wuhan, P.R. China

Homepage: http://dkxy.cug.edu.cn/info/1014/1476.htm

ORCID: http://orcid.org/0000-0002-1362-4491

Office: IGG-413

Research interests

Artificial intelligence, machine learning, deep learning, and their applications in Geophysics;

Wave theory, signal processing, scientific computing, inverse problems, seismic data processing, seismic modeling, imaging, and inversion.

Education

Professional experience

20150225-20160228, University of British Columbia, Visiting Ph.D. Student, Geophysics, adviser: Prof. Felix J. Herrmann.

Professional memberships

l  Society of Exploration Geophysics (SEG)

l  European Society of Exploration Geophysicists (EAGE)

Selected peer-reviewed journal papers

1.      X. Chai et al., "An Open-Source Package for Deep-Learning-Based Seismic Facies Classification: Benchmarking Experiments on the SEG 2020 Open Data," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022, Art no. 4507719, doi: 10.1109/TGRS.2022.3144666. Permalink: https://ieeexplore.ieee.org/document/9686703

2.      Xintao Chai, Genyang Tang, Kai Lin, Zhe Yan, Hanming Gu, Ronghua Peng, Xiaodong Sun, and Wenjun Cao, (2021), "Deep learning for multitrace sparse-spike deconvolution," GEOPHYSICS 86: V207-V218. Permalink: https://doi.org/10.1190/geo2020-0342.1

3.      X. Chai, G. Tang, S. Wang, K. Lin and R. Peng, "Deep Learning for Irregularly and Regularly Missing 3-D Data Reconstruction," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 7, pp. 6244-6265, July 2021, doi: 10.1109/TGRS.2020.3016343. Permalink: https://ieeexplore.ieee.org/document/9174797

4.      Xintao Chai, Hanming Gu, Feng Li, Hongyou Duan, Xiaobo Hu, and Kai Lin (2020). ”Deep learning for irregularly and regularly missing data reconstruction.” Scientific Reports, 10, 1-18, doi: 10.1038/s41598-020-59801-x. Permalink: https://doi.org/10.1038/s41598-020-59801-x

5.      X. Chai, G. Tang, S. Wang, R. Peng, W. Chen and J. Li, "Deep Learning for Regularly Missing Data Reconstruction," in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4406-4423, June 2020, doi: 10.1109/TGRS.2020.2963928. Permalink: https://doi.org/10.1109/TGRS.2020.2963928

6.      Xintao Chai, Ronghua Peng, Genyang Tang, Wei Chen, and Jingnan Li (2019). ” Some remarks on Q-compensated sparse deconvolution without knowing the quality factor Q.” Geophysical Prospecting, 67(8), 2003-2021, doi: 10.1111/1365-2478.12838. Permalink: https://doi.org/10.1111/1365-2478.12838

7.      Xintao Chai, Genyang Tang, Fangfang Wang, Hanming Gu, and Xinqiang Wang (2018). ”Q-compensated acoustic impedance inversion of attenuated seismic data: Numerical and field-data experiments.” Geophysics, 83(6), R553-R567, doi: 10.1190/geo2017-0499.1. Permalink: https://doi.org/10.1190/geo2017-0499.1

8.      Xintao Chai, Genyang Tang, Ronghua Peng, Shaoyong Liu, 2018, The linearized Bregman method for frugal full-waveform inversion with compressive sensing and sparsity-promoting, Pure and Applied Geophysics, 175(3), 1085-1101, doi: 10.1007/s00024-017-1734-4. Permalink: https://doi.org/10.1007/s00024-017-1734-4

9.      Xintao Chai, Shangxu Wang, Genyang Tang, Xiangcui Meng, 2017, Stable and efficient Q-compensated least-squares migration with compressive sensing, sparsity-promoting, and preconditioning, Journal of Applied Geophysics, 145, 84–99, doi: 10.1016/j.jappgeo.2017.07.015. Permalink: https://doi.org/10.1016/j.jappgeo.2017.07.015

10.   Xintao Chai, Shangxu Wang, Genyang Tang, 2017, Sparse reflectivity inversion for non-stationary seismic data with surface-related multiples: Numerical and field-data experiments, Geophysics, 82(3), R199-R217, doi: 10.1190/geo2016-0520.1. Permalink: https://doi.org/10.1190/geo2016-0520.1

11.   Xintao Chai, Shangxu Wang, Jianxin Wei, Jingnan Li, Hanjun Yin, 2016, Reflectivity inversion for attenuated seismic data: Physical modeling and field data experiments, Geophysics, 81(1), T11-T24, doi: 10.1190/geo2015-0250.1. Permalink: https://doi.org/10.1190/geo2015-0250.1

12.   Xintao Chai, Shangxu Wang, Sanyi Yuan, Jianguo Zhao, Langqiu Sun, Xian Wei, 2014, Sparse reflectivity inversion for nonstationary seismic data, Geophysics, 79(3), V93-V105, doi: 10.1190/geo2013-0313.1. Permalink: https://doi.org/10.1190/geo2013-0313.1

Expanded abstracts or conference papers

1.      Xintao Chai, Mengmeng Yang, Philipp Witte, Rongrong Wang, Zhilong Fang, Felix Herrmann, 2016, A linearized Bregman method for compressive waveform inversion, SEG International Exposition and Annual Meeting, New Orleans, USA, doi: 10.1190/segam2016-13848105.1. Permalink: https://doi.org/10.1190/segam2016-13848105.1

2.      Xintao Chai, Shangxu Wang, Xian Wei, Xiangcui Meng, Jingnan Li, Hanjun Yin, Yang Qiao, Ming Ma, 2014, High resolution prestack nonstationary AVA inversion: Part 1 - Theory，SEG Annual Meeting, Denver, USA, 2014.10.26-2014.11.01.

3.      Xintao Chai, Shangxu Wang, Sanyi Yuan, Xiangcui Meng, Xiaoyu Chuai, A new high resolution AVA inversion using partial spectrum of prestack seismic data, SEG Annual Meeting, Houston, USA, 2013.09.21-2013.09.2.

Funding grant

l  National Natural Science Foundation of China, grant no. 41704129, 20180101-20201231

l  Foundation of the State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing (Grant no. PRP/open-2108)

l  Opening Fund of the Key Laboratory of Deep Oil & Gas (Grant no. 20CX02117A)

l  Hubei Subsurface Multi-scale Imaging Key Laboratory (China University of Geosciences) Program, grant no. SMIL-2017-01, 2018-2019

l  Fundamental Research Funds for the Central Universities, 2018-2020

l  China University of Geosciences (Wuhan) Funds for the course “Python with artificial intelligence, deep learning”, 2019-2020

Advising

l  Adviser to Junyong Yu (2019), M.S. student.

l  Adviser to Wenhui Nie (2020), M.S. student.

l  Adviser to Taihui Yang (2020), M.S. student.

Teaching experience

l  “Machine learning”, undergraduate level, 3.0 credits, 2021-present.

l  “Python programming language”, undergraduate level, 1.0 credits, 2021-present.

l  “Python with artificial intelligence, deep learning”, undergraduate level, 1.5 credits, 2019-2020.

l  “Computational geophysics”, undergraduate level, 2017-2020.

l  “MATLAB programming language”, undergraduate level, 2018-2020.

Editorial service

l  2021-present, Reviewer, IEEE Transactions on Geoscience and Remote Sensing

l  2017-present, Reviewer, Geophysics

l  2019-present, Reviewer, IEEE Geoscience and Remote Sensing Letters

l  2020-present, Reviewer, Geophysical Prospecting

l  2020-present, Reviewer, Journal of Applied Geophysics

l  2017-present, Reviewer, Journal of Geophysics and Engineering

l  2020-present, Reviewer, Exploration Geophysics

l  2022-present, Reviewer, Chinese Journal of Geophysics

l  2017-present, Reviewer, Petroleum Science Bulletin

Authorized patents as the first inventor

1.      Patent no. ZL 2017 1 0994606.5, Authorization no. CN 107894612 B, 20190531, in Chinese.

2.      Patent no. ZL 2017 1 0525466.7, Authorization no. CN 107367760 B, 20190402, in Chinese.

3.      Patent no. ZL 2017 1 0524014.7, Authorization no. CN 107390261 B, 20190212, in Chinese.