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SIGNAL‐TO‐NOISE RATIO ENHANCEMENT IN MULTICHANNEL SEISMIC DATA VIA THE KARHUNEN‐LOÉVE TRANSFORM *
Author(s) -
JONES I.F.,
LEVY S.
Publication year - 1987
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.1365-2478.1987.tb00800.x
Subject(s) - karhunen–loève theorem , noise (video) , signal to noise ratio (imaging) , multiple , economic geology , algorithm , signal processing , synthetic data , regional geology , signal (programming language) , computer science , data processing , data compression , geology , seismology , mathematics , artificial intelligence , metamorphic petrology , digital signal processing , arithmetic , telecommunications , computer hardware , image (mathematics) , tectonics , programming language , operating system
The Karhunen‐Loéve transform, which optimally extracts coherent information from multichannel input data in a least‐squares sense, is used for two specific problems in seismic data processing. The first is the enhancement of stacked seismic sections by a reconstruction procedure which increases the signal‐to‐noise ratio by removing from the data that information which is incoherent trace‐to‐trace. The technique is demonstrated on synthetic data examples and works well on real data. The Karhunen‐Loéve transform is useful for data compression for the transmission and storage of stacked seismic data. The second problem is the suppression of multiples in CMP or CDP gathers. After moveout correction with the velocity associated with the multiples, the gather is reconstructed using the Karhunen‐Loéve procedure, and the information associated with the multiples omitted. Examples of this technique for synthetic and real data are presented.