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Nonlinear structure‐enhancing filtering using plane‐wave prediction *
Author(s) -
Liu Yang,
Fomel Sergey,
Liu Guochang
Publication year - 2010
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/j.1365-2478.2009.00840.x
Subject(s) - similarity (geometry) , filter (signal processing) , noise (video) , attenuation , nonlinear system , computer science , algorithm , geology , artificial intelligence , optics , physics , quantum mechanics , image (mathematics) , computer vision
Attenuation of random noise and enhancement of structural continuity can significantly improve the quality of seismic interpretation. We present a new technique, which aims at reducing random noise while protecting structural information. The technique is based on combining structure prediction with either similarity‐mean filtering or lower‐upper‐middle filtering. We use structure prediction to form a structural prediction of seismic traces from neighbouring traces. We apply a non‐linear similarity‐mean filter or an lower‐upper‐middle filter to select best samples from different predictions. In comparison with other common filters, such as mean or median, the additional parameters of the non‐linear filters allow us to better control the balance between eliminating random noise and protecting structural information. Numerical tests using synthetic and field data show the effectiveness of the proposed structure‐enhancing filters.