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| 压缩感知在非重复时移地震处理中应用研究 |
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刘巍1, 雷霄1, 隋波1, 李轶彬1, 陈凤英2,3, 刘振东2, 王祥春2
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1.中海石油(中国)有限公司湛江分公司, 广东 湛江 524057;2.中国地质大学(北京) 地球物理与信息技术学院, 北京 100083;3.广东海洋大学 电子与信息工程学院, 广东 湛江 524088
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| 摘要: |
| 非重复采集的多分量和拖缆地震数据由于方位角、偏移距、覆盖次数、信噪比等差异,不利于时移地震对比,需在时移对比前进行一致性处理。压缩感知技术能够对地震数据进行重建和改善地震数据信噪比,将两期地震数据覆盖次数和信噪比归一化。本文将南海某区域早期三维拖缆地震数据和近期海底电缆(Ocean Bottom Cable,OBC)多分量地震数据进行非重复性时移地震处理研究:首先将OBC按与拖缆方位角、偏移距交集的部分取出,实现拖缆数据进行方位角和偏移距归一化;然后采用压缩感知数据重建的方法实现两期数据的覆盖次数和信噪比的一致性,同时与五维插值方法进行对比;最后将一致性处理后的两期数据进行时移对比分析。结果说明:压缩感知数据重建可以提高并归一化两期地震数据的覆盖次数和信噪比,达到时移对比的目的,且优于五维插值方法。研究结论表明压缩感知数据重建方法可实现OBC与三维拖缆数据进行非重复性时移地震一致性研究,降低时移地震成本,为后续多分量数据进行非重复性时移地震研究提供依据。 |
| 关键词: 时移地震 非重复 OBC 压缩感知 数据重建 时移对比 |
| DOI：10.11759/hykx20250418001 |
| 分类号:P631 |
| 基金项目:中国海洋石油有限公司重大科技资助项目(KJGG2021-0501) |
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| Application of compressed sensing in multicomponent and towed streamer data in time-shift seismic processing |
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LIU Wei1, LEI Xiao1, SUI Bo1, LI Yibin1, CHEN Fengying2,3, LIU Zhendong2, WANG Xiangchun2
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1.Zhanjiang Branch of CNOOC Ltd, Zhanjiang 524057, China;2.School of Geophysics and Information Technology, China University of Geosciences(Beijing), Beijing 100083, China;3.School of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China
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| Abstract: |
| Owing to differences in azimuth and offset, seismic data acquired without repetition geometry are not conducive to time-shift seismic comparison. Therefore, consistency processing should be carried out before time-shift comparison. Compressed sensing technology can reconstruct seismic data while improving its signal-to-noise ratio (SNR), enabling consistent SNR and effective fold normalization across different seismic surveys. In this paper, early three-dimensional (3D) towed streamer seismic data and recent ocean bottom cable (OBC) multicomponent seismic data from a region in the South China Sea are studied for nonrepetitive time-shift data processing. First, the portion of the OBC data with azimuth and offset values overlapping those of the towed streamer data is extracted, and the azimuth and offset of the towed streamer data are normalized accordingly. Then, the compressed sensing data reconstruction method is used to normalize the fold and SNR of the two datasets and compare them with those obtained using the five-dimensional interpolation method. Finally, the two normalized datasets are analyzed through time-shift comparisons. The results showed that compressed sensing data reconstruction can improve and normalize the coverage times and SNR of the two seismic datasets and achieve the purpose of time-shift comparison; thus, this approach is better than the five-dimensional interpolation method. Overall, the compressed sensing data reconstruction method can normalize the fold and SNR of OBC and 3D towed streamer data, realize the nonrepetitive time-shift seismic consistency study, reduce the time-shift seismic cost, and provide a basis for the subsequent nonrepetitive time-shift seismic exploration with multicomponent data. |
| Key words: time-shift seismic nonrepetition OBC compression sensing data reconstruction time-shift correlation |