A stable explicit depth wavefield extrapolation is obtained using Lp iterative reweighted least-squares (IRLS) frequency-space (⁠ω-x⁠) finite-impulse response digital filters. The problem of designing such filters to obtain stable images of challenging seismic data is formulated as an Lp IRLS minimization. Prestack depth imaging of the challenging Marmousi model data set was then performed using the explicit depth wavefield extrapolation with the proposed Lp IRLS-based algorithm. Considering the extrapolation filter design accuracy, the Lp 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.

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