Dealiased seismic data interpolation by dynamic matching

Abstract

Interpolation is a critical step in seismic data processing. Gaps in seismic traces can lead to severe spatial aliasing phenomena in the corresponding F-K spectra. The aliasing caused by regularly spaced gaps has similar F-K spectra as those of the actual data. Existing dealiasing interpolation algorithms generally assume that seismic events are linear, and cannot handle non-stationary events. To address this shortcoming, we proposed a novel dealiased seismic data interpolation approach using dynamic matching. First, we matched two adjacent seismic traces using the local affine regional dynamic time-warping algorithm. Subsequently, we calculated the local slope between two seismic traces. Finally, we performed linear interpolation on the regularly missing seismic data using local slope information. The proposed approach was tested on both synthetic and field seismic datasets. The interpolation results showed that the proposed approach has a better anti-aliasing ability and computational efficiency than the traditional Spitz and seislet-based approaches. Additionally, this method can also be applied to interpolate irregularly sampled seismic data and for simultaneous seismic data interpolation and denoising.