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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Chapter 7<br />
Conclusions and Discussion<br />
7.1 Introduction<br />
The goal <strong>of</strong> this study was to improve the spatial fidelity <strong>of</strong> s<strong>eismic</strong> imaging through a<br />
deterministic evaluation <strong>of</strong> surface s<strong>eismic</strong> data with velocity modeling and attribute<br />
analysis. To achieve the goal I modeled sediment velocities <strong>using</strong> sonic log velocities, a<br />
well-based model, and migrated <strong>using</strong> a Kirchh<strong>of</strong>f PSDM. I compared the well-based<br />
method <strong>of</strong> velocity modeling to a more traditional method <strong>of</strong> <strong>using</strong> residual migration<br />
velocities or prestack time migrated velocity model velocities to model sediment<br />
velocities for the migration. I evaluated the results through velocity analysis <strong>using</strong> CIGs,<br />
interpretation, and an innovative use <strong>of</strong> attributes as a QC tool. Using a velocity model<br />
derived from sonic logs improved the spatial fidelity <strong>of</strong> the land 3-D surface s<strong>eismic</strong> data<br />
at Vinton Dome Louisiana and that coherence is an attribute for quantifying<br />
improvements is a conclusion I reached in this study.<br />
7.2 <strong>Evaluation</strong> <strong>of</strong> Methods<br />
7.2.1 Processing<br />
Generally, 3-D surface s<strong>eismic</strong> land data have a lower signal-to-noise ratio than 3-D<br />
marine surface s<strong>eismic</strong> data because <strong>of</strong> noise sources and irregular acquisition and 3-D<br />
land surface s<strong>eismic</strong> data require a higher degree <strong>of</strong> processing than do marine data. The<br />
lower signal-to-noise ratio is a reason why marine data are generally better candidates for<br />
PSDM. The goal <strong>of</strong> this study was to improve the spatial fidelity <strong>of</strong> s<strong>eismic</strong> imaging<br />
<strong>using</strong> velocity modeling and attribute analysis. Field data were processed to reduce noise<br />
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