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SIGNAL ADJUSTMENT OF VIBROSEIS AND IMPULSIVE SOURCE DATA *
Author(s) -
BRÖTZ R.,
MARSCHALL R.,
KNECHT M.
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.tb02256.x
Subject(s) - seismic vibrator , deconvolution , wavelet , algorithm , computer science , transformation (genetics) , distortion (music) , amplitude , signal processing , regional geology , autocorrelation , phase distortion , acoustics , filter (signal processing) , geology , mathematics , optics , digital signal processing , bandwidth (computing) , artificial intelligence , physics , computer vision , seismology , telecommunications , metamorphic petrology , tectonics , amplifier , chemistry , biochemistry , statistics , computer hardware , gene
A bstract In certain areas continuous Vibroseis profiling is not possible due to varying terrain conditions. Impulsive sources can be used to maintain continuous coverage. While this technique keeps the coverage at the desired level, for the processing of the actual data there is the problem of using different sources resulting in different source wavelets. In addition, the effect of the free surface is different for these two energy sources. The approach to these problems consists of a minimum‐phase transformation of the two‐sided Vibroseis data by removal of the anticipation component of the autocorrelation of the filtered sweep and a minimum‐phase transformation of the impulsive source data by replacement of the recording filter operator with its minimum‐phase correspondent. Therefore, after this transformation, both datasets show causal wavelets and a conventional deconvolution (spike or predictive) may be used. After stacking, a zero‐phase transformation can be performed resulting in traces well suited for computing pseudo‐acoustic impedance logs or for application of complex seismic trace analysis. The solution is also applicable to pure Vibroseis data, thereby eliminating the need for a special Vibroseis deconvolution. The processing steps described above are demonstrated on synthetic and actual data. The transformation operators used are two‐sided recursive (TSR) shaping filters. After application of the above adjustment procedure, remaining signal distortions can be removed by modifying only the phase spectrum or both the amplitude and phase spectra. It can be shown that an arbitrary distortion defined in the frequency domain, i.e., a distortion of the amplitude and phase spectrum, is noticeable in the time section as a two‐sided signal.