Sparseness-constrained seismic deconvolution with curvelets
Title | Sparseness-constrained seismic deconvolution with curvelets |
Publication Type | Conference |
Year of Publication | 2005 |
Authors | Gilles Hennenfent, Felix J. Herrmann, R. Neelamani |
Conference Name | CSEG Annual Conference Proceedings |
Month | 05 |
Publisher | CSEG |
Keywords | Presentation, SLIM |
Abstract | Continuity along reflectors in seismic images is used via Curvelet representation to stabilize the convolution operator inversion. The Curvelet transform is a new multiscale transform that provides sparse representations for images that comprise smooth objects separated by piece-wise smooth discontinuities (e.g. seismic images). Our iterative Curvelet-regularized deconvolution algorithm combines conjugate gradient-based inversion with noise regularization performed using non-linear Curvelet coefficient thresholding. The thresholding operation enhances the sparsity of Curvelet representations. We show on a synthetic example that our algorithm provides improved resolution and continuity along reflectors as well as reduced ringing effect compared to the iterative Wiener-based deconvolution approach. |
URL | https://slim.gatech.edu/Publications/Public/Conferences/CSEG/2005/Hennenfent05CSEGscs/Hennenfent05CSEGscs.pdf |
Presentation | |
Citation Key | hennenfent2005CSEGscs |