NDLI: Seismic dip estimation based on the two-dimensional Hilbert transform and its application in random noise attenuation

Content Provider	Springer Nature Link
Author	Liu, Cai Chen, Chang Le Wang, Dian Liu, Yang Wang, Shi Yu Zhang, Liang
Copyright Year	2015
Abstract	In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional (2D) derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variable-amplitude polynomial fitting along the direction of the dip to improve the adaptive structure-oriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.
Starting Page	55
Ending Page	63
Page Count	9
File Format	PDF
ISSN	16727975
Journal	Applied Geophysics
Volume Number	12
Issue Number	1
e-ISSN	19930658
Language	English
Publisher	Chinese Geophysical Society
Publisher Date	2015-04-16
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Two-dimensional Hilbert transform random noise attenuation structure protection nonstationary polynomial fitting local seismic dip Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Geophysics

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