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

ecause of the higher signal-to-noise ratio in marine data. This is a reason why marine
data are better candidates for PSDM as well as for building an initial sediment velocity
model.
Typically, in areas containing salt such as the upper Gulf of Mexico Basin, the focus of
the velocity modeling is to image the shape of the salt. The first step in this iterative
process begins with an initial sediment velocity model. With this model, data are PSDM
and used to update the model by picking a top of salt horizon. Salt velocities are flooded
beneath the salt and the data are re-migrated. Using the new PSDM volume allows for
focusing details in the salt by iteratively updating and detailing the velocity model. The
iterative nature of this process requires that the initial sediment velocity model be as
accurate as possible. Removing errors that propagate throughout the process from the
beginning often require starting over. Starting with high signal-to-noise ratio data and
smoothing the velocity model reduces the spurious data in marine 3-D seismic surveys.
I explored an approach to minimize the lower signal-to-noise ratio typically found in land
data and to insure an accurate initial sediment velocity model.
I began deriving an initial sediment velocity model for a PSDM of 3-D surface seismic
land data by addressing the differences in data quality between 3-D marine data and land
data. Recognizing that land data has differences from the marine data that limit the
strength of the signal, I devised an approach to velocity modeling that did not use the
seismic velocities. I used sonic logs to build the initial sediment velocity model instead
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