App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 11

High fidelity full waveform inversion for enhanced boundary sharpness and structural continuity

Zeng Zifei1
Lu Han2
Liu Liyan1
Min Fan1
1. School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu Sichuan 610500, China
2. Chengdu Yihe Information Technology Co, Ltd, Chengdu Sichuan 610095, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0064

Abstract

Deep learning-based full waveform inversion struggles to balance large-scale structures and local details. It also suffers from semantic gaps in skip connections and redundant global attention computation. To address these issues, this study proposed the DFR-FWI algorithm. This algorithm is based on feature decoupling, cross-level fusion, and context refinement. First, the encoder utilized a dynamic gated dual-path feature fusion module. This module applied standard and deformable convolutions in parallel. It decoupled and dynamically fused local textures and large-scale structural features. Second, the network embedded a channel-spatial synergistic attention module into the skip connections. This module dynamically calibrated the semantic consistency of multi-scale features. Third, the decoder integrated a bi-level routing attention module. This module modeled long-range dependencies in a region-aware manner. It balanced computational efficiency and structural fidelity. Furthermore, the training process adopted a joint pixel-level and gradient loss. This loss improved overall accuracy and enhanced boundaries simultaneously. Experiments on the OpenFWI and Marmousi II datasets validate the proposed method. The results show that the DFR-FWI algorithm significantly outperforms mainstream methods in imaging accuracy and edge clarity. The source code is available at: https: //github. com/FanSmale/DFR-FWI.

Foundation Support

四川省科技计划资助项目(2024NSFSC2050)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0064
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 11

Publish History

[2026-07-02] Accepted Paper

Cite This Article

曾子斐, 陆晗, 刘丽艳, 等. 提升边界锐度与结构连续性的高保真全波形反演 [J]. 计算机应用研究, 2026, 43 (11). (2026-07-31). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0064. (Zeng Zifei, Lu Han, Liu Liyan, et al. High fidelity full waveform inversion for enhanced boundary sharpness and structural continuity [J]. Application Research of Computers, 2026, 43 (11). (2026-07-31). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0064. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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