A Novel Marine Seismic Streamer Positioning Data Quality Control Method Based on Morphological Constraints
High-precision hydrophone positioning is crucial for ensuring the quality and reliability of marine seismic exploration imaging. However, existing data quality control methods for hydrophone positioning often neglect the streamer’s geometry and morphology, which hampers effective outlier detection in complex scenarios and reduces the accuracy and stability of hydrophone positioning. To address this issue, this article proposes a novel quality control method that integrates the structural morphology of multiple towed streamers. First, the method incorporates prior information about compass bearings, acoustic distance structures, and geometric conditions. It then introduces a robust surface-fitting method and a stochastic model refinement based on the rate of change (ROC). The algorithms’ detailed workflow is presented. Finally, the method’s performance is evaluated through simulations and field experiments. Simulation results demonstrate that, compared to the traditional single-streamer threshold method relying solely on mathematical statistics, the new approach effectively addresses cases with consecutive outliers, improving hydrophone positioning accuracy by approximately 43.7%. Field experiments show an accuracy improvement of 38.7%. Overall, the method significantly enhances the stability of hydrophone positioning, ensuring higher quality seismic exploration operations.
Authors
- Chufeng Duan (ORCID: https://orcid.org/0009-0009-7747-0178)
- Cuilin Kuang (ORCID: https://orcid.org/0000-0002-8599-706X)
- Kaiwei Sang (ORCID: https://orcid.org/0009-0002-2891-8828)
- Haonan Zhang (ORCID: https://orcid.org/0009-0009-8142-852X)
- Yijun Yang (ORCID: https://orcid.org/0000-0002-9855-9616)
- Ling Lv (ORCID: https://orcid.org/0000-0002-8893-3889)
- Heng Liu (ORCID: https://orcid.org/0009-0005-2882-6474)
Institutions
- Central South University (CN)
- Peng Cheng Laboratory (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/jsen.2024.3510947
- Primary Topic
- Advanced Computational Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Key Research and Development Program of Hunan Province of China