Prestack imaging of seismic data using L-p iterative reweighted least-squares wavefield extrapolation filters in the frequency-space domain

A stable explicit depth wavefield extrapolation is obtained using L-p iterative reweighted least-squares (IRLS) frequency-space (omega-x) finite-impulse response digital filters. The problem of designing such filters to obtain stable images of challenging seismic data is formulated as an L-p IRLS minimization. Prestack depth imaging of the challenging Marmousi model data set was then performed using the explicit depth wavefield extrapolation with the proposed L-p IRLS-based algorithm. Considering the extrapolation filter design accuracy, the L-p IRLS minimization method resulted in an image with higher quality when compared with the weighted least-squares method. The method can, therefore, be used to design high-accuracy extrapolation filters.