3‐D reverse time migration for tunnel seismic data with an optimized observation system

Abstract Tunnel seismic advance detection is a technology that uses geophysical or drilling methods to predict geological information. As an important step in tunnel seismic advance detection, the tunnel observation system promotes accurate prediction of the location for adverse geological bodies ahead of the tunnel face. However, current tunnel observation systems suffer from limited spatial coverage and insufficient reception of reflection information, resulting in inaccurate migration imaging and susceptibility to noise interference during reflection layer extraction. This paper employs the three‐dimensional (3‐D) reverse time migration (RTM) method, mainly focusing on designing tunnel observation systems. To optimize the existing tunnel observation system, the radiation theory is used to conduct an in‐depth exploration of the advantages and disadvantages of various excitation and reception modes. We summarize their respective applicability based on subjective and visual analysis and provide several design principles that have the potential to achieve good imaging results. In numerical experiments, several observation systems are designed according to the current project case to evaluate the imaging performance under the 3‐D RTM method. By comparing the migration results, it is demonstrated that the designed observation system can obtain state‐of‐the‐art performance due to its superiority in terms of imaging amplitude and energy distribution. Finally, we evaluated the impact of excavation damage zones on imaging performance and summarized the computational efficiency and storage requirements of 3‐D RTM.

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Publication Details

Journal
Near Surface Geophysics
Published
2025-05-09
DOI
https://doi.org/10.1002/nsg.70014
Citations
1
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
1.87

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article

3‐D reverse time migration for tunnel seismic data with an optimized observation system

Renjie He, Zubin Chen, Jianqian Li, Zhiyuan Li et al.
1 citations
Near Surface Geophysics
Seismic Imaging and Inversion Techniques
1.87
article

3‐D reverse time migration for tunnel seismic data with an optimized observation system

Renjie He, Zubin Chen, Jianqian Li, Zhiyuan Li, Yanqing Fan, Chunyang Pei
article en
1 citations

Abstract

Abstract Tunnel seismic advance detection is a technology that uses geophysical or drilling methods to predict geological information. As an important step in tunnel seismic advance detection, the tunnel observation system promotes accurate prediction of the location for adverse geological bodies ahead of the tunnel face. However, current tunnel observation systems suffer from limited spatial coverage and insufficient reception of reflection information, resulting in inaccurate migration imaging and susceptibility to noise interference during reflection layer extraction. This paper employs the three‐dimensional (3‐D) reverse time migration (RTM) method, mainly focusing on designing tunnel observation systems. To optimize the existing tunnel observation system, the radiation theory is used to conduct an in‐depth exploration of the advantages and disadvantages of various excitation and reception modes. We summarize their respective applicability based on subjective and visual analysis and provide several design principles that have the potential to achieve good imaging results. In numerical experiments, several observation systems are designed according to the current project case to evaluate the imaging performance under the 3‐D RTM method. By comparing the migration results, it is demonstrated that the designed observation system can obtain state‐of‐the‐art performance due to its superiority in terms of imaging amplitude and energy distribution. Finally, we evaluated the impact of excavation damage zones on imaging performance and summarized the computational efficiency and storage requirements of 3‐D RTM.

Near Surface GeophysicsVol. 23(3)
Jilin University (CN)
National Natural Science Foundation of China, People's Government of Jilin Province
Openalex Percentile: Top 19%
Seismic Imaging and Inversion Techniques
1.87
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