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Adaptive acquisition footprint suppression based on a 3D stationary wavelet transform: A case study from China

Authors :
Chen, Xuehua
Yang, Wei
He, Zhenhua
Zhong, Wenli
Source :
Journal of Applied Geophysics. Feb2012, Vol. 77, p1-6. 6p.
Publication Year :
2012

Abstract

Abstract: To reduce the acquisition footprint in the geometric attribute analysis of marine seismic data, a 3D stationary wavelet transform (SWT) is presented in this paper. We use the 3D SWT to decompose the seismic volume into multiple levels of cubes in three directions, and we determine the different filter parameters, which vary with depth. Then, we implement the suppression of the acquisition footprint by adaptively reconstructing the weighted filtered wavelet components. The field data examples indicate that the method effectively removes the acquisition footprint and suppresses other types of noise while at the same time, preserving and highlighting geological features. The method can improve the accuracy and reliability of geometric attribute analysis (such as eigenstructure-based coherence and 3D volumetric curvature) in characterizing the internal structure of reservoirs and in structural interpretation. The method can be expected to be applicable to the removal of other kinds of noise on marine seismic datasets. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09269851
Volume :
77
Database :
Academic Search Index
Journal :
Journal of Applied Geophysics
Publication Type :
Academic Journal
Accession number :
70873214
Full Text :
https://doi.org/10.1016/j.jappgeo.2011.11.004