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Non‐minimum‐phase wavelet estimation using second‐ and third‐order moments
Author(s) -
Lu Wenkai
Publication year - 2005
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.1365-2478.2005.00430.x
Subject(s) - wavelet , inversion (geology) , gaussian , amplitude , independent and identically distributed random variables , seismic inversion , phase (matter) , geology , synthetic seismogram , algorithm , statistics , computer science , mathematics , seismology , optics , random variable , physics , geometry , artificial intelligence , quantum mechanics , azimuth , tectonics
This paper presents a new algorithm for estimating non‐minimum‐phase seismic wavelets by using the second‐ and higher‐order statistics (HOS) of the wavelets. In contrast to many, if not most, of the HOS‐based methods, the proposed method does not need to assume that subsurface seismic reflectivity is a non‐Gaussian, statistically independent and identically distributed random process. The amplitude and phase spectra of the wavelets are estimated, respectively, using the second‐order statistics (SOS) and third‐order moment (TOM) of the wavelets, which will, in turn, be derived from the HOS of the seismic traces. In our approach, the wavelets can be ‘calculated’ from seismic traces efficiently; no optimization or inversion is necessarily required. Very good results have been obtained by applying this method to both synthetic and real‐field data sets.