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Enhancement of the Signal-to-Noise Ratio in Sonic Logging Waveforms by Seismic Interferometry

Sonic logs are essential tools for reliably identifying interval velocities which, in
turn, are used in many seismic processes. One problem that arises, while logging, is
irregularities due to washout zones along the borehole surfaces that scatters the transmitted energy and hence weakens the signal recorded at the receivers. To alleviate
this problem, I have extended the theory of super-virtual refraction interferometry to
enhance the signal-to-noise ratio (SNR) sonic waveforms. Tests on synthetic and real
data show noticeable signal-to-noise ratio (SNR) enhancements of refracted P-wave
arrivals in the sonic waveforms.
The theory of super-virtual interferometric stacking is composed of two redatuming steps followed by a stacking procedure. The first redatuming procedure is of
correlation type, where traces are correlated together to get virtual traces with the
sources datumed to the refractor. The second datuming step is of convolution type,
where traces are convolved together to dedatum the sources back to their original
positions. The stacking procedure following each step enhances the signal to noise
ratio of the refracted P-wave first arrivals.
Datuming with correlation and convolution of traces introduces severe artifacts
denoted as correlation artifacts in super-virtual data. To overcome this problem, I replace the datuming with correlation step by datuming with deconvolution. Although
the former datuming method is more robust, the latter one reduces the artifacts
significantly. Moreover, deconvolution can be a noise amplifier which is why a regularization term is utilized, rendering the datuming with deconvolution more stable.
Tests of datuming with deconvolution instead of correlation with synthetic and real
data examples show significant reduction of these artifacts. This is especially true
when compared with the conventional way of applying the super-virtual refraction
interferometry method.

Identiferoai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/237272
Date04 1900
CreatorsAldawood, Ali
ContributorsMai, Paul Martin, Hoteit, Ibrahim
Source SetsKing Abdullah University of Science and Technology
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Rights2013-04-30, At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2013-04-30.

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