Study and application of high-order statistics constrained sparse blind deconvolution technique

Zhang Hua; Pang Yanqing; He Zhenhua; Yang Bo; He Guangming; Wu Furong; Chen Aiping; Xie Xiaocui

doi:10.11743/ogg20160417

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Study and application of high-order statistics constrained sparse blind deconvolution technique
Vol. 37, Issue 4, Pages: 591-597(2016)
Online First：08 August 2016，

Published：2016
DOI： 10.11743/ogg20160417
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DOI：

Zhang Hua, Pang Yanqing, He Zhenhua, et al. Study and application of high-order statistics constrained sparse blind deconvolution technique[J]. 2016, 37(4): 591-597. DOI： 10.11743/ogg20160417.

摘要

以贝叶斯基本理论为基础，利用高阶双谱域估算的高精度地震子波为约束，在修正柯西判别准则下，实现地震数据的稀疏盲反褶积拓频处理，获取比常规反褶积提频方法分辨率更高的可靠数据。模拟数值实验和多波实际数据处理结果表明：双谱域估算的子波精度较高，以该子波为先验约束的稀疏盲反褶积能极大提高纵波和转换波数据的分辨率，满足精细解释能分辨更小薄层的要求，可作为多波高分辨率处理的有效手段。

Abstract

Based on the basic theory of Bayesian and using the high precision wavelet estimated in high-order double spectrum domain as constraints

this paper realized sparse blind deconvolution frequency-expanding processing under the modified Cauchy criteria and obtained data that are more reliable and have higher frequency than the conventional deconvolution frequency-enhancing method.The results of numerical experiments and real data processing show that the wavelet estimated in the dual spectrum domain has higher accuracy

under the priori constraint of which the sparse blind deconvolution can greatly enhance the resolution of both P-wave and PS-wave.It can meet the requirement of resolute very thin layers

thus can be used as an effective method for high resolution processing.