@article {kumar2016bls,
	title = {Beating level-set methods for 5D seismic data interpolation: a primal-dual alternating approach},
	journal = {IEEE Transactions on Computational Imaging},
	year = {2017},
	note = {(published online in IEEE Transactions on Computational Imaging)},
	month = {04},
	abstract = {Acquisition cost is a crucial bottleneck for seismic workflows, and low-rank formulations for data interpolation allow practitioners to {\textquoteright}fill in{\textquoteright} data volumes from critically subsampled data acquired in the field. Tremendous size of seismic data volumes required for seismic processing remains a major challenge for these techniques. Residual-constrained formulations require less parameter tuning when the target noise floor is known. We propose a new approach to solve residual constrained formulations for interpolation. We represent the data volume in a compressed manner using low-rank matrix factors, and build a block-coordinate algorithm with constrained convex subproblems that are solved with a primal-dual splitting scheme. The develop optimization framework works on the whole seismic temporal frequency slices and does not require windowing or non-trivial sorting of seismic data. The new approach is competitive with state of the art level-set algorithms that interchange the role of objectives with constraints. We use the new algorithm to successfully interpolate a large scale 5D seismic data volume (upto 1010 data-points), generated from the geologically complex synthetic 3D Compass velocity model, where 80\% of the data has been removed. We also develop a robust extension of the primal-dual approach to deal with the outliers (or noise) in the data.},
	keywords = {alternating minimization, matrix completion, primal-dual splitting, seismic data, seismic trace interpolation},
	doi = {10.1109/TCI.2017.2693966},
	url = {http://slim.gatech.edu/Publications/Public/Journals/IEEETransComputationalImaging/2017/kumar2016bls/kumar2016bls.pdf},
	author = {Rajiv Kumar and Oscar Lopez and Damek Davis and Aleksandr Y. Aravkin and Felix J. Herrmann}
}
