A Deterministic Evaluation of eismic Fidelity using Velocity Modeling ...
A Deterministic Evaluation of eismic Fidelity using Velocity Modeling ...
A Deterministic Evaluation of eismic Fidelity using Velocity Modeling ...
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types <strong>of</strong> coherence. The first type developed by Bahorich and Farmer (1995) cross<br />
correlates each trace with neighboring inline and crossline, normalizes the energy and<br />
combines the results. Developed to improve the robustness <strong>of</strong> the technique developed<br />
by Bahorich and Farmer is a second generation <strong>of</strong> coherence Marfurt et al. (1998) that<br />
uses a multitrace semblance measure. The coherence I used in this study is a third<br />
generation method that also uses a multitrace coherence measure. What makes this<br />
different from the previous generation is that it is uses eigenvalues from the covariance<br />
matrix formed from traces in the analysis cube (Gersztenkorn, 1996; Gersztenkorn and<br />
Marfurt. 1996a, b; Gersztenkorn et al., 1999). To improve results I used filters and<br />
interpolations in this method. Eigenstructure measures projections only onto the signal<br />
subspace <strong>using</strong> a covariance matrix to partition signal and noise subspaces (Gersztenkorn<br />
and Marfurt, 1999).<br />
I made comparisons between the well-based velocity model PSDM, prestack time<br />
migrated velocity model PSDM, and the PSTM attributes. The setup parameters were<br />
similar to insure that comparisons were <strong>of</strong> the same events. Specifically the dip window<br />
height for the time migration was set at 2ms and the dip window height for the depth<br />
migrated data was set at 75 feet.<br />
5.4 Attributes for QC<br />
Rietveld et al. (1999) used coherence to compare results from prestack and post stack<br />
depth migrations. I used the same premise justified <strong>using</strong> attributes to compare the<br />
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