** Next:** Acknowledgments
** Up:** Curry: Non-stationary interpolation in
** Previous:** Real Data Examples

Non-stationary f-x domain interpolation appears to be a promising route to generate
the vast quantities of data needed for surface-related multiple elimination.
The process is embarrassingly parallel and leaves the data in a similar state as
would be needed by subsequent processing algorithms. The process is also much
faster than a t-x approach, and needs orders of magnitude less memory to run.
However, the issue of non-stationarity in time is large, and impossible to ignore.
This problem is more pronounced on the poorest-sampled axes, such as cross-line offset.
Applying this non-stationary f-x methodology in time windows should hopefully address
this problem.
One important thing to note is that while higher-dimensionality of the interpolation
could improve the end result, this was only the case when the axis that was added was
well-sampled, such as the in line source or inline offset axis. The addition of
the 4 points on the cross-line offset axis did little to the end result.

In order to combine this approach with an extrapolator to quickly generate input data
for a 3D surface-related multiple prediction, the next steps will be to apply this method
in time-windows to address the time-non-stationarity issue as well as attempt to apply this
method in the log-stretch frequency domain so that an efficient AMO operator could be applied.

** Next:** Acknowledgments
** Up:** Curry: Non-stationary interpolation in
** Previous:** Real Data Examples
Stanford Exploration Project

5/6/2007