A Deterministic Evaluation of eismic Fidelity using Velocity Modeling ...

38-42). For QC I would brute stack the data. I recognized attenuation of the data,
especially in the eastern half of the survey (Figure 40).
To balance the amplitudes I applied automatic gain control (AGC) after the data were
filtered. I also used a second application of AGC before migration. By balancing the
amplitudes, the stack eliminated what had been higher amplitude low frequency noise
caused by ground roll before the second application of AGC. Improvement of the signal
justified opening the filter to 5-6-70-80, increasing the bandwidth and further improving
fidelity. Another issue was the presence of high amplitude first breaks. These appear to
have been creating artifacts (Figure 43). I muted these before the filter (Figure 44).
Results of this processing flow (Table 2) show reduction in migration swirls (Figure 45).
Those that remain are possibly the result of sedimentary velocity model that lacked the
detail to precisely model the velocities at the salt/sediment interface. A comparison of
data processed with the minimal parameters and those with the more aggressive approach
show differences in both the sections (Figure 46) and in the depth slices (Figure 47). I
used improvements I recognized from these comparisons to select the processing flow
from Table 2.
3.4 Conclusions and Discussion
Processing 3-D land surveys present several challenges with respect to noise. In the
Vinton Dome survey these challenges are compounded by nontraditional acquisition
parameters. My goal was to improve the fidelity of the 3-D seismic data by using an
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