Joint elastic reverse time migration of towed streamer and sparse ocean-bottom seismic node hybrid data

被引:0
作者
Yu, Pengfei [1 ]
Chu, Mingzhi [1 ]
Xu, Yunxia [2 ]
Zhang, Baojin [2 ]
Geng, Jianhua [3 ]
机构
[1] Hohai Univ, Coll Oceanog, Nanjing, Peoples R China
[2] Guangzhou Marine Geol Survey, Minist Nat Resources, China Geol Survey, Guangzhou, Peoples R China
[3] Tongji Univ, State Key Lab Marine Geol, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
DRIVEN ADAPTIVE DECOMPOSITION; SEA-FLOOR; OBS DATA; SCALAR; INVERSION; MEDIA;
D O I
10.1190/GEO2021-0333.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Compared to 1C towed-streamer (TS) seismic exploration, 4C ocean-bottom seismic (OBS) node exploration has great advantages in complex structure imaging, lithology, and fluid identification using elastic waves. However, sparse spatial sam-pling of OBS node surveys highlights the problems of the imaging acquisition footprint, poor phase continuity, and low signal-to-noise ratio (S/N) with conventional elastic reverse time migration (ERTM) methods. Therefore, a solution of joint ERTM (J-ERTM) is proposed by combining sparse OBS node data with dense TS data. In the J-ERTM of the hybrid data, a novel weighted boundary condition combined with acoustic -elastic coupling equations and a vector-based crosscorrelation imaging condition are presented to perform PP and PS imaging by receiver-side tensorial extrapolation of TS and OBS node hybrid data. A synthetic example demonstrates that our method can effectively process TS and OBS node hybrid data and improve elastic imaging problems caused by OBS node sparse acquisition. J-ERTM techniques also are applied to an active -source OBS data set from the South China Sea. To improve the imaging quality with limited data, some preprocessing procedures for field TS and OBS node hybrid data sets are nec-essary, such as denoising, OBS node relocation, OBS node orientation correction, OBS node calibration, and others. After preprocessing, the pressure component and velocity compo-nents have a more physical energy relationship, more consistent frequency range and wavelet, and a higher S/N. Finally, the pre-processed hybrid data can be used for J-ERTM. The imaging results demonstrate that our method works well with field data.
引用
收藏
页码:S47 / S57
页数:11
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