Seismic deconvolution revisited with curvelet frames

TitleSeismic deconvolution revisited with curvelet frames
Publication TypeConference
Year of Publication2005
AuthorsGilles Hennenfent, R. Neelamani, Felix J. Herrmann
Conference NameEAGE Annual Conference Proceedings
Month06
KeywordsEAGE, Presentation, SLIM
Abstract

We propose an efficient iterative curvelet-regularized deconvolution algorithm that exploits continuity along reflectors in seismic images. Curvelets are a new multiscale transform that provides sparse representations for images (such as seismic images) that comprise smooth objects separated by piece-wise smooth discontinuities. Our technique combines conjugate gradient-based convolution operator inversion with noise regularization that is performed using non-linear curvelet coefficient shrinkage (thresholding). The shrinkage operation leverages the sparsity of curvelets representations. Simulations demonstrate that our algorithm provides improved resolution compared to the traditional Wiener-based deconvolution approach.

URLhttps://slim.gatech.edu/Publications/Public/Conferences/EAGE/2005/Hennenfent05EAGEsdr/Hennenfent05EAGEsdr.pdf
Presentation
URL2
Citation Keyhennenfent2005EAGEsdr