Lihua Fu

Professor, School of Mathematics and Physics, China University of Geosciences (Wuhan)

New Century Excellent Talents Program, Ministry of Education, China

"Geosciences Scholar" Core Talent, China University of Geosciences (Wuhan)

Research Interests:

Deep learning, seismic data processing, image processing

Professional Experience:

•   2014/01–Present: Professor, School of Mathematics and Physics, China University of Geosciences (Wuhan)

•   2013/04–2014/04: Visiting Scholar, Department of Computer Science, The University of Vermont, USA

•   2010/01–2013/12: Associate Professor, School of Mathematics and Physics, China University of Geosciences (Wuhan)

•   2006/07–2009/12: Lecturer, School of Mathematics and Physics, China University of Geosciences (Wuhan)

•   2003/06–2006/06: Teaching Assistant, School of Mathematics and Physics, China University of Geosciences (Wuhan)

Selected Grants:

•   National Natural Science Foundation of China (NSFC) General Program on Deep Learning Methods for Five-Dimensional Seismic Data Reconstruction, 42274172, 2023/01–2026/12 (PI).

•   Chongqing Natural Science Foundation General Program on Seismic Data Reconstruction Based on "External Training + Self-learning" Dictionary Learning, 2023NSCQ-MSX0207, 2023/07–2026/07 (PI).

•   Guangdong Provincial Basic and Applied Basic Research Foundation on Seismic Data Reconstruction Methods Based on Self-similarity and Sparse Low-rank Priors, 2024/01–2026/12 (PI).

•   Collaborative Fund with China North Industries Group Corporation (CNGC) 59th Research Institute on Globalization Algorithm Research for Discrete Environmental Data, HDHDW5901030201, 2021/01–2021/12 (PI).

•   New Century Excellent Talents Support Program, Ministry of Education on Multi-core Fast Learning Methods in Seismic Signal Analysis, NCET-13-1011, 2014/01–2016/12, Completed, Principal Investigator (PI).

•   National Natural Science Foundation of China (NSFC) Tianyuan Mathematical Foundation, Sparse Adjustable Kernel Function Models and Their Application in Time-Frequency Analysis, 11026145, 2011/01–2011/12 (PI).

•   National Natural Science Foundation of China (NSFC) Young Scientists Fund on Adaptive Kernel Models with Joint Sparse Representation and Their Application in Seismic Signal Spectrum Decomposition, 61102103, 2012/01–2014/12 (PI).

•   Hubei Provincial Natural Science Foundation, NARX System Identification Based on Mixed Kernels and Its Application in Geomagnetic Storm Forecasting, 2010CDB04205, 2011/01–2012/12 (PI).

Selected Publications:

•   Y. Tian, L. Fu*, W.Fang, T. Li, FR-UNet: A feature restoration-based UNet for seismic data consecutively missing trace interpolation. IEEE Transactions on Geoscience and Remote Sensing, 2025. (DOI: 10.1109/TGRS.2025.3531934)

•   M. Wu, L. Fu*, W. Fang, J. Cao, Sparse prior-net: A sparse prior-based deep network for seismic data interpolation. Geophysics, 2024, 89(1): V34-V47.

•   W. Xu, W. Fang, L. Fu*, Seismic data interpolation using 5D-FCN: A preliminary study. IEEE Geoscience and Remote Sensing Letters, 2024. (DOI: 10.1109/LGRS.2024.3385433)

•   J. Cao, L. Fu*, W. Fang, M. Wu, Seismic data interpolation via UNet with non-local blocks. Exploration Geophysics, 2024, 55(3): 213-222. (DOI:10.1080/08123985.2023.2290134)

•   Z. Huang, J. Liu, W. Fang, L. Fu*, Surfaced-related multiple attenuation using the CNN method in the NMO domain, Coal Geology & Exploration, 2024, 52(11): 160-170. 

•   W. Gao, L. Fu*, W. Fang, Y. Wang, J Wu, Seismic data reconstruction via a hybrid CNN-low-rank method. Geophysics, 2024. (DOI: 10.1190/geo2024-0195.1)

•   X. Niu, L. Fu*, W. Fang, Q. Wang, and M Zhang, Seismic data interpolation using nonlocal self-similarity prior. Geophysics, 2023, 88(1): WA65-WA80.

•   S. Liu, W Ni., W. Fang, L. Fu*, Absolute acoustic impedance inversion using convolutional neural networks with transfer learning. Geophysics, 2023, 88(2): R163-R174.

•   W. Fang, L. Fu, M. Wu, J. Yue, H Li, Irregularly sampled seismic data interpolation with self-supervised learning. Geophysics, 2023, 88(3): V175-V185.

•   W. Fang, L. Fu*, W. Xu, A. Bian, H. Li, CCNet-5D: 5D convolutional neural network for seismic data interpolation. Geophysics, 2023, 88(4): V333-V344.

•   Y. Xu, L. Fu*, X. Niu, X. Chen, M Zhang, Three-dimensional seismic data reconstruction based on fully connected tensor network decomposition. IEEE Transactions on Geoscience and Remote Sensing, 2023. (DOI: 10.1109/TGRS.2023.3272583)

•   J. Yue, L. Fu*, X. Niu, W. Fang, Orthogonal dictionary learning based on l4-Norm maximisation for seismic data interpolation. Exploration Geophysics, 2023. (DOI: 10.1080/08123985. 2023.2205582)

•   J. Cao, L. Fu*, W. Fang, M. Wu, Seismic data interpolation via UNet with non-local blocks. Exploration Geophysics, 2023. (DOI:10.1080/08123985.2023.2290134)

•   Y. Guo, L. Fu, H. Li, Seismic data interpolation based on multi-scale transformer. IEEE Geoscience and Remote Sensing Letters, 2023. (DOI 10.1109/LGRS.2023.3298101)

•   Y. Yang, L. Fu, K. Qian, H. Li, Seismic random noise attenuation via a two-stage U-net with supervised attention. Exploration Geophysics, 2023. (DOI:10.1080/08123985.2023.2218870)

•   Y. Li, L. Fu*, W. Cheng, et al, Efficient seismic data reconstruction based on Geman function minimization. Applied Geophysics, 2022. (DOI: 10.1080/08123985.2021.1886853)

•   W. Fang, L. Fu*, H. Li, S. Liu, and Q. Wang, BSnet: An unsupervised blind spot network for seismic data random noise Attenuation. IEEE Transactions on Geoscience and Remote Sensing, 2022. (DOI: 10.1109/TGRS.2022.3179718)

•   M. Cui, L. Fu*, and W. Fang, Seismic noise attenuation via convolution neural network with learning noise prior. Exploration Geophysics, 2022, 53(1): 38-51.

•   G. Li, S. Liu, X. Jian, D. Zhu, L. Fu, T. Chen and X. Hu, Identifying the lineament structure cooperatively using the airborne gravimetric, magnetic and remote sensing data: a case study from the Pobei Area, NW China. IEEE Transactions on Geoscience and Remote Sensing, 2022. (DOI: 10.1109/TGRS.2022.321380)

•   L. Wang and L. Fu*, Airborne LiDAR point cloud classification based on attention mechanism point convolutional network, Laser & Optoelectronics Progress, 2022. (DOI: 10.3788/LOP202259.1028007)

•   X. Niu, L. Fu*, W. Zhang and Y. Li, Seismic data interpolation based on simultaneously sparse and low-rank matrix recovery. IEEE Transactions on Geoscience and Remote Sensing, 2021. (DOI: 10.1109/TGRS.2021.3110600)

•   W. Fang, L. Fu*, S. Liu and H. Li, Dealiased seismic data interpolation using a deep-learning-based prediction-error filter, Geophysics, 2021, 86(4): V317-V328. 

•   Q. Liu, L. Fu*, and M. Zhang, Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks. Geophysics, 2021, 86(2): V131-V142.

•   W. Fang, L. Fu and Z. Li, Seismic data interpolation based on U-net with texture loss, Geophysics, 2021, 86(1): V41-V54. 

•   W. Fang, L. Fu, and H. Li, Unsupervised CNN based on self-similarity for seismic data denoising. IEEE Geoscience and Remote Sensing Letters, 2021. (Accepted. DOI 10.1109/LGRS.2021.3131046)

•   Q. Wang, L. Fu, S. Ruan, et al., Reconstructing seismic data by incorporating deep external and internal learning. Exploration Geophysics, 2021. (Accepted. DOI: 10.1080/08123985.2021.2024072)

•   Z. Hu, S. Liu, X. Hu, L. Fu, et al. Inversion of magnetic data using deep neural networks. Physics of the Earth and Planetary Interiors, 2021. (Accepted. DOI: 10.1016/J.PEPI. 2021/106653)

•   W. Zhang, L. Fu*, M. Zhang, and W. Cheng, 2-D seismic data reconstruction via truncated nuclear norm regularization. IEEE Transaction on Geoscience and Remote Sensing, 2020, 58(9): 6336-6343.

•   Q. Liu, L. Fu*, M. Zhang, and W. Zhang, Two-dimensional seismic data reconstruction using patch tensor completion. Inverse Problems and Imaging, 2020,14(6): 985-1000.

•   Q. Wang, Y. Shen, L. Fu, and H. Li, Seismic data interpolation using deep internal learning, Exploration Geophysics, 2020, 51(6): ‏683-697. 

•   D. Zhu, H. Li, T. Liu, L. Fu and S. Zhang, Low-rank matrix decomposition method for potential field data separation. Geophysics, 2020, 85(1): G1-G16.

•   L. Fu, C. Zeng, W. Yang and Y. Li, Fourth-order spectral moment analysis for extracting the information of crustal arc structure, Oil Geophysical Prospecting, 2020, 55(4): 923-930.

•   W. Cheng, W. Fang and L. Fu*, Seismic noise suppression via self-similarity and low-rank prior. Geophysical Prospecting for Petroleum, 2020, 59(6): 880-889.

•   L. Fu, M. Zhang, Z. Liu, H. Li, Robust frequency estimation of multi-sinusoidal signals using orthogonal matching pursuit with weak derivatives criterion. Circuits, Systems, and Signal Processing, 2019, 38(3): 1194-1205.

•   W. Zhang, L. Fu* and Q. Liu, Non-convex Log-sum function-based majorization-minimization framework for seismic data reconstruction. IEEE Geoscience and Remote Sensing Letters, 2019, 16(11): 1776-1780. 

•   X. Zhang, L. Fu*, H. Zhang, J. Peng, Reconstruction of natural earthquake data based on Orthogonal Rank-one Matrix Pursuit and its application to dense seismic array around the San Jacinto Fault Zone in California. Chinese Journal of Geophysics, 2019, 62(4):1427-1439.

•   J. Peng, L. Fu*, X. Zhang, Seismic data reconstruction based on fast fixed point continuation algorithm. Oil Geophysical Prospecting,2019, 54(6): 1195-1205.

•   Q. Liu, L. Fu*, W. Zhang, Three-dimensional seismic data reconstruction via nonconvex Lp norm. Oil Geophysical Prospecting, 2019, 54(5): 979-987. 

•   L. Fu, W. Yang, Depth evaluation of magnetic sources by spectral moment analysis. Chinese Journal of Geophysics, 2018, 61(7): 3044-3054. 

Books：

•   X. Hu, L. Fu., G. Hao, H. Zhang. Modern Information Processing Technologies in Geophysics. Science Press, 2022.

Patents:

•   J. Yue, L. Fu., W. Fang, X. Niu, Seismic Data Reconstruction Method and System Based on L4 Norm Maximized Orthogonal Dictionary, Patent No. ZL202210191246.6, Granted on: October 29, 2024.

•   W. Fang, H. Li, L. Fu, Seismic Data Interpolation Method and Device Based on Unsupervised Deep Learning for Randomly Missing Data, Patent No. ZL202210071726.9, Granted on: October 15, 2024.

•   W. Fang, H. Li, L. Fu, 5D-CNN-Based Seismic Data Five-Dimensional Interpolation Method, Patent No. ZL202210684712.4, Granted on: August 2, 2024.

•   M. Wu, L. Fu, W. Fang, Unsupervised Seismic Data Reconstruction Method and Device Based on Sparse Constraints, Patent No. ZL202210071732.4, Granted on: July 2, 2024.

•   Y. Li, L. Fu, C Zeng, Seismic Field Boundary Identification Method Based on Fourth-Order Spectral Moments, Patent No. ZL201910579203.3, Granted on: January 3, 2023.

•   X. Niu, L. Fu, H. Li, Seismic Data Reconstruction Method, Device, Equipment, and Storage Medium, Patent No. ZL202110308415.5, Granted on: March 29, 2022.

•   L. Fu, W. Fang, Z. Li, H. Li, Seismic Data Reconstruction Method Using U-net Network Based on Texture Constraints, Patent No. ZL201910591075.4, Granted on: March 11, 2022.

•   W. Fang, L. Fu, H. Li, Z. Li, Seismic Data De-aliased Interpolation Method Combining Deep Learning and Predictive Filtering, Patent No. ZL202010325961.5, Granted on: June 6, 2021.

•   X. Niu, L. Fu, H. Li, W. Zhang, K. Zou, Seismic Data Reconstruction Method Based on Low-rank and Sparse Constraints, Patent No. ZL201911177677.1, Granted on: November, 27, 2020.

Academic Services:

Ø  Technical Committee:

Elected Member, Intelligent Geophysics Professional Committee, Chinese Geophysical Society, 2022-present.

Ø  Journal Editorship:

Guest Editor, AIMS Geosciences (American Institute of Mathematical Sciences), 2022.

Ø  Conference and Workshop Organization：

Conference Convenor, "Geophysics under Big Data and Big Models" Symposium, China Geoscience Union (CGU) Annual Meeting, October 20–23, 2024.

Session Chair, SEG 4th International Workshop on Mathematical Geophysics: Traditional & Learning，December 17-19, 2021.

Ø  Journal Reviewer:

Geophysics

IEEE Transactions on Geoscience and Remote Sensing (TGRS)

IEEE Geoscience and Remote Sensing Letters (GRSL)

Geophysical Prospecting (GP)

Petroleum Science

Geoenergy Science and Engineering

IEEE Transactions on Artificial Intelligence

IEEE Signal Processing Letters

Petroleum Science Bulletin (Outstanding Reviewer, 2023)