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Full Waveform Inversion Methods and Applications for Seismic Data in Complex Media

Submission deadline: 25 March 2026
Special Issue Editors
Pan Zhang
College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China
Interests: Full waveform inversion; Seismic velocity modeling; Passive seismic; Elastic wave
Liguo Han
College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Interests: Full waveform inversion; Active and passive seismic; Seismic signal processing; Seismic propagation and imaging in complex media
Zhaoqi Gao
School of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: Full waveform inversion; Reservoir parameters inversion; High-resolution processing
Jingrui Luo
School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710021, China
Interests: Full waveform inversion; Seismic velocity modeling; Seismic signal processing
Guoxin Chen
Department of Marine Sciences, Zhejiang University, Zhoushan, 316021, China
Interests: seismic wave full waveform inversion, reverse time migration imaging, geophysical data processing based on artificial intelligence
Hui Sun
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China
Interests: Seismic imaging; Seismic velocity modeling; TSP; Seismic attribute analysis
Jingjing Zong
School of Resource and Environment and the Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: VSP; DAS-VSP; Borehole Seismic;Rock physics
Special Issue Information

Dear Colleagues,


Full waveform inversion (FWI) is a high-resolution seismic imaging technique that uses both kinematic and dynamic information of seismic wavefields to reconstruct subsurface parameters with exceptional accuracy. By iteratively minimizing the misfit between observed and simulated seismic data, FWI provides detailed estimates of velocity, density, anisotropy, and attenuation properties, making it a powerful tool for subsurface characterization. In recent years, significant progress have been made in enhancing algorithm robustness, computational efficiency, and practical applicability of FWI. Given its potential, FWI is increasingly regarded as a key technology for high-precision velocity modeling in complex media and intricate geological structures, including salt bodies, thrust belts, and fractured reservoirs. However, challenges remain in handling strong anisotropy, viscoelastic attenuation, multi-parameter trade-offs, and cycle-skipping issues, necessitating further methodological innovations. This special issue aims to showcase the latest research progress in FWI for complex media, covering theoretical developments, computational optimizations, and field applications. Topics of interest include, but are not limited to:

  • Elastic FWI for multi-parameter inversion in isotropic/heterogeneous media;
  • Anisotropic FWI for VTI, HTI, and orthorhombic media;
  • Viscoacoustic/viscoelastic FWI incorporating attenuation estimation;
  • Physics-informed and AI-driven FWI;
  • Joint inversion strategies integrating FWI with other geophysical data;
  • Case studies from offshore and onshore exploration

Dr. Pan Zhang
Professor Liguo Han
Professor Zhaoqi Gao
Dr. Jingrui Luo
Dr. Guoxin Chen
Dr. Hui Sun
Dr. Jingjing Zong
Guest Editors

Keywords
elastic full waveform inversion
anisotropic full waveform inversion
viscoacoustic/viscoelastic full waveform inversion
deep learning based full waveform inversion
velocity modeling
case studies of full waveform inversion
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing