基于W变换压缩感知框架的崎岖海底信号补偿方法

黄玉; 李芳; 任婷

doi:10.19509/j.cnki.dzkq.tb20250358

基于W变换压缩感知框架的崎岖海底信号补偿方法

doi: 10.19509/j.cnki.dzkq.tb20250358

中海石油（中国）有限公司海南分公司，海口 570100

基金项目: 中国海洋石油有限公司综合科研项目“琼东南盆地他源超压模拟及预测方法研究”（KJZH-2025-2101）

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E-mail：8249078@qq.com

中图分类号: P631.46
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- 文章访问数: 78
- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2025-07-31
- 录用日期: 2025-12-04
- 修回日期: 2025-12-03
- 网络出版日期: 2025-12-15

A rugged seabed signal compensation method based on W transform compressive sensing framework

CNOOC China Limited, Hainan Branch, Haikou 570100, China

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Corresponding author: E-mail：8249078@qq.com

摘要

摘要:
南海北部琼东南盆地海底地形复杂，横跨浅海、陆架坡折、深海海域。在崎岖海底附近发育了多个潜力目标，是发现储量的重点区带。然而深水崎岖海底下方地震资料振幅、频率失真，与陆地采集的地震资料差距较大，传统的信号补偿方法很难有效处理这类数据。为了得到高品质的地震资料，准确评价崎岖海底下方目标，亟需开发一种合理有效的补偿方法。本研究设计了基于W变换的压缩感知补偿框架，通过构建参考道与目标道之间的补偿矩阵，快速实现地震资料的振幅补偿；引入稀疏变换正则化方法，保证补偿资料的高信噪比，提高地震资料的质量。利用本方法对南海北部复合崎岖海底地震数据进行了信号补偿处理，补偿后的地震数据剖面能量分布一致性得到了较好的改善。本次信号补偿处理的成功应用证明了方法的可行性，可为类似地震资料的信号补偿处理提供借鉴。
- 崎岖海底 /
- 地震资料 /
- 信号补偿 /
- W变换 /
- 压缩感知 /
- 南海北部
Abstract: <p>The Qiongdongnan Basin, situated in the northern part of the South China Sea, is a geologically significant and resource-rich marine area, characterized by extremely complex seabed topography that transitions seamlessly across shallow coastal waters, gently sloping continental shelves, steep shelf break zones, and abyssal deep-sea basins. Within this basin, the vicinities of the rugged and uneven seabed-marked by abrupt topographic variations such as submerged ridges, fault scarps, and scattered seamounts-have emerged as key exploration zones, as geological surveys and preliminary prospecting have identified a multitude of potential hydrocarbon and mineral reserve targets in these sub-seabed formations. However, the amplitude and frequency of seismic data under the rugged seabed in deep water are distorted, and there is a large gap between the seismic data collected on land and that under the rugged seabed. Traditional signal compensation methods fail to effectively process such data. </p></sec><sec><title>Objective
In order to obtain high-quality seismic data and accurately evaluate targets under the rugged seabed, it is urgent to develop a reasonable and effective compensation method.
Methods
Inspired by time-frequency analysis and compressive sensing methods, this paper designed a compressive sensing compensation framework based on W transform. By constructing the compensation matrix between the reference trace and the target trace, the amplitude compensation of seismic data was rapidly achieved in a single step. The sparse transform regularization method was introduced to ensure the high signal-to-noise ratio of the compensation data and improve the quality of the seismic data.
Results
This method was used to compensate the seismic data under complex rugged seabed conditions in the northern part of the South China Sea, and the consistency of the energy distribution of the seismic data profile after compensation was effectively improved.
Conclusion
The successful application of the signal compensation processing demonstrates the feasibility of the method and provides a reference for the signal compensation processing of similar seismic data.
- rugged seabed /
- seismic data /
- signal compensation /
- W transform /
- compressive sensing /
- northern part of the South China Sea

HTML全文

图 1 基于W变换压缩感知框架的信号补偿方法流程图

Figure 1. Flowchart of signal compensation method based on W-transform compressive sensing framework

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图 2 W变换和S变换的时频分析结果

Figure 2. Time-frequency analysis results of W transform and S transform

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图 3 振幅补偿前后地震剖面对比图（采样间隔2 ms；下同）

Figure 3. Seismic profiles before and after compensation

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图 4 信号补偿前(a)、后(b)时域对比图

Figure 4. Time-domain comparison before and after signal compensation

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图 5 信号补偿前后频谱对比图

Figure 5. Comparison of spectra before and after signal compensation

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图 6 信号补偿前(a)、后(b)时频谱对比图

Figure 6. Comparison of time-frequency spectra before and after signal compensation

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图 7 信号补偿前后时间切片对比图

Figure 7. Comparison of time slices before and after signal compensation

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图 8 三维信号振幅补偿前后结果

Figure 8. Results before and after amplitude compensation of three-dimensional signals

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