An optimized space-time Gaussian beam migration method with dynamic parameter control

被引:3
|
作者
Lv, Qingda [1 ]
Huang, Jianping [1 ]
Yang, Jidong [2 ]
Guan, Zhe [3 ]
机构
[1] China Univ Petr, Sch Geosci, Qingdao 266580, Peoples R China
[2] Univ Texas Dallas, Dept Geosci, Richardson, TX 75080 USA
[3] Rice Univ, Appl Phys Program, Houston, TX 77005 USA
基金
中国国家自然科学基金;
关键词
Space-time Gaussian beam; Dynamic beam parameter; Up-going ray tracing; Green function; DEPTH MIGRATION; WAVE-FIELDS; COMPUTATION;
D O I
10.1016/j.jappgeo.2018.11.006
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In the Gaussian beam (GB) method, initial beam parameters are principal factors influencing the accuracy and computational efficiency of seismic depth imaging. Various optimized beam parameter strategies for Gaussian beam migration (GBM) have been proposed to improve imaging quality as well as computational efficiency, while optimized space-time Gaussian beam schemes for seismic migration have still not been fully investigated. In this paper, an optimized space-time Gaussian beam approach with dynamic parameter control for seismic depth imaging is developed. We first provide an expression for dynamic beam parameter by taking in account the effect of velocity field variation on the beam forming. Based on dynamic beam parameters, the new space-time adaptive Gaussian beam generated by an arbitrary source wavelet is obtained, which can adaptively calculate the beam width to make the seismic beam energy better focused in the central ray neighborhood. Then, the forward wavefield is constructed in two-dimensional (2D) acoustic media by space-time adaptive Gaussian beam for the implementation of migration. Adhering to the framework of conventional space-time Gaussian beam method, we perform the up-going ray tracing from subsurface imaging points to the receiver surface to compute the asymptotic Green function for the construction of the backward wavefield. Numerical experiments demonstrate that the new presented approach has a superior accuracy for seismic depth imaging in both shallow and deep regions compared to the conventional space-time Gaussian beam migration scheme. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:47 / 56
页数:10
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