Sparsity- and continuity-promoting seismic image recovery with curvelet frames
نویسندگان
چکیده
منابع مشابه
Sparsity- and continuity-promoting seismic image recovery with curvelet frames
A nonlinear singularity-preserving solution to seismic image recovery with sparseness and continuity constraints is proposed. We observe that curvelets, as a directional frame expansion, lead to sparsity of seismic images and exhibit invariance under the normal operator of the linearized imaging problem. Based on this observation we derive a method for stable recovery of the migration amplitude...
متن کاملNon-parametric seismic data recovery with curvelet frames
Seismic data recovery from data with missing traces on otherwise regular acquisition grids forms a crucial step in the seismic processing flow. For instance, unsuccessful recovery leads to imaging artifacts and to erroneous predictions for the multiples, adversely affecting the performance of multiple elimination. A non-parametric transform-based recovery method is presented that exploits the c...
متن کامل4255 Seismic Deconvolution Revisited with Curvelet Frames
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 operat...
متن کاملCurvelet reconstruction with sparsity-promoting inversion: successes and challenges
SUMMARY In this overview of the recent Curvelet Reconstruction with Sparsity-promoting Inversion (CRSI) method, we present our latest 2-D and 3-D interpolation results on both synthetic and real datasets. We compare these results to interpolated data using other existing methods. Finally, we discuss the challenges related to sparsity-promoting solvers for the large-scale problems the industry f...
متن کاملSeismic data denoising through multiscale and sparsity-promoting dictionary learning
Seismic data comprise many traces that provide a spatiotemporal sampling of the reflected wavefield. However, such informationmay suffer from ambient and random noise during acquisition, which could possibly limit the use of seismic data in reservoir locating. Traditionally, fixed transforms are used to separate the noise from the data by exploiting their different characteristics in a transfor...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied and Computational Harmonic Analysis
سال: 2008
ISSN: 1063-5203
DOI: 10.1016/j.acha.2007.06.007