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Vector elastic deconvolution migration with dual wavefield decomposition
Geophysics ( IF 3.3 ) Pub Date : 2021-07-02 , DOI: 10.1190/geo2020-0826.1
Benxin Chi 1 , Kai Gao 1 , Lianjie Huang 1
Affiliation  

Elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

中文翻译:

具有双波场分解的矢量弹性反卷积偏移

使用多分量数据的弹性波成像可以提供比声波成像更有用的地下信息,但它通常在算法上具有挑战性。我们开发了一种矢量弹性反卷积偏移方法,用于对各向同性和各向异性弹性介质中的地下结构进行高分辨率成像。我们的新方法使用基于双波场分解的矢量去卷积成像条件,包括使用希尔伯特变换的显式定向波场分离和使用低秩分解方法的 P/S 矢量波场分解。使用三个弹性模型,我们从数值上确定,与基于互相关的矢量弹性逆时偏移方法相比,我们的新方法可产生显着更高的分辨率和更振幅平衡的弹性图像。
更新日期:2021-07-04
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