F-X Adaptive Seismic Trace Interpolation

Exponentially Weighted Recursive Least Squares (EWRLS) is adopted to estimate adaptive prediction filters for f-x seismic interpolation. Adaptive prediction filters are able to model signals where the dominant wavenumbers are varying in space. This concept leads to a f-x interpolation method that does not require windowing strategies for optimal results. In other words, adaptive prediction filters can be used to interpolate waveforms with spatially variant dips. The performance of the interpolation method depends on two parameters: the filter length and a forgetting factor. Particular attention is paid to the selection of the forgetting factor, a parameter that controls the adaptability of the algorithm to changes in local dip. Finally, synthetic and real data examples are used to illustrate the performance of the proposed adaptive f-x interpolation method.