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Wavelet based self-similarity analysis in seismic data processingNormal access

Authors: Z. Yu and D. Whitcombe
Event name: 69th EAGE Conference and Exhibition - Workshop Package
Session: WO8 Curvelets, contourlets, seislets, … in seismic data processing - where are we and where are we going?
Publication date: 11 June 2007
DOI: 10.3997/2214-4609.201405089
Organisations: SPE, EAGE
Language: English
Info: Extended abstract, PDF ( 1.15Mb )
Price: € 20

Wavelet based self-similarity analysis in seismic data processing Zhou Yu (BP) and David Whitcombe (BP) SUMMARY____________________________________________________________ This paper shows using synthetic examples how by using the wavelet transform we can exploit the principle of self-similarity to overcome a number of limitations within seismic data. Firstly we demonstrate that the plane wave solution to the wave equation has self-similarity when dispersion is too small to be considered. When seismic data is decomposed using the orthogonal wavelet basis this self-similarity is further enhanced by the fact that the orthogonal wavelet bases at different scales overlap in frequency. Decimation in the pyramid decomposition

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