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The presence of such fluctuations can be modeled by
adding small random perturbations to the travel times. These random shifts
decrease the semblance values, especially for high-frequency
signals. The particular results will depend on different
circumstances (shape of the seismic array, frequency content
of the signal, etc.), so here I show the effect of adding random
velocity fluctuations to the data described above by
adding time shifts to each trace. Figure shows
the decrease of semblance that accompanies an increase in the standard
deviation of the time perturbations. Such time shifts can sometimes
be caused by the uppermost layer of the medium. In this
(favorable) case,
they can be treated as a function of geophone location and hopefully
can be compensated for (static corrections). Also, some kind of
static corrections can be made using crosscorrelations. Steve Cole
created an iterative algorithm for applying such corrections to
passive seismic data.
**vran
**

Figure 5 vran

Effect on semblance computation of small random velocity fluctuations.
The horizontal axis is the standard deviation of travel times divided by
the period of the signal.

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Stanford Exploration Project

12/18/1997