小波束叠前深度偏移和照明:基于Marmousi模型的测试

摘要

Beamlet sources have strong local and directional character and can easily accomplish local illumination and migration. Besides, they provide better migration results than conventional migration methods. We introduce the basic principles of beamlet prestack depth migration that includes a windowed Fourier transform and frame theory. We explain the Gabor-Daubechies (G-D) frame based on a Gaussian function. Beamlet decomposition provides information on the local space and direction of wavefield. We synthesize the beamlet source and beamlet records in the wavelet domain using both rectangle and Gaussian windows and then extrapolate the synthesized data with a Fourier finite-difference operator.We test the method using the standard Marmousi model. By comparing and analyzing the migration results of single directional beamtet and beamlets with different windows and directions, we demonstrate the validity of the prestack depth migration with Gaussian beamlets method.%小波束源有很强的局部性和方向性,它可以很容易的实现局部照明和偏移,除此之外,它的偏移效果也要好于常规的偏移方法.本文介绍了基于框架理论的小波束叠前深度偏移的基本原理.我们解释了基于Gaussian函数的G-D框架.小波束分解提供了局部空间和方向上的信息.我们在小波域中,分别应用矩形窗和Gaussian窗合成了小波束源和小波束记录,并基于傅立叶有限差分算子,对marmousi模型进行了叠前深度偏移试算.通过对单个,以及多个小波束源偏移结果对比分析,验证了Gaussian小波束叠前深度偏移方法的有效性.