Conclusions and Future Work

Incorporating pseudo-primary data into a non-stationary prediction-error filter based interpolation method gives promising results for large gaps in the near offset. While most interpolation algorithms suffer from an objective measure of the quality of interpolation in practical applications, the usefulness of the pseudo-primaries can be judged in a relatively objective manner by looking at the convolution of the pseudo-primary based PEF with the recorded data. Future work includes reducing this difference and examining the final results after SRME compared to a high-resolution parabolic radon transform.