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 nonstationary events. To address this shortcoming, we develop a novel dealiased seismic data interpolation approach using dynamic matching. First, we match two adjacent seismic traces using the local affine regional dynamic time-warping algorithm. Subsequently, we calculate the local slope between two seismic traces. Finally, we perform linear interpolation on the regularly missing seismic data using local slope information. Our approach is tested on synthetic and field seismic data sets. The interpolation results indicate that our approach has a better antialiasing ability and computational efficiency than the traditional Spitz and seislet-based approaches. In addition, this method can be applied to interpolate irregularly sampled seismic data and for simultaneous seismic data interpolation and denoising.