# Beating level-set methods for 3D seismic data interpolation: a primal-dual alternating approach

arXiv: https://arxiv.org/abs/1607.02624 · HTML: https://mlsanity.com/paper/1607.02624/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jul 2016.

## Built on by (most cited first, 1 of 1)

- [Anti-Aliasing Add-On for Deep Prior Seismic Data Interpolation](https://mlsanity.com/paper/2101.11361/) (2021)

## Abstract (arXiv)

Acquisition cost is a crucial bottleneck for seismic workflows, and low-rank formulations for data interpolation allow practitioners to `fill in' 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. We propose a new approach to solve residual constrained formulations for interpolation. We represent the data volume using matrix factors, and build a block-coordinate algorithm with constrained convex subproblems that are solved with a primal-dual splitting scheme. 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, generated from the geologically complex synthetic 3D Compass velocity model, where 80% of the data has been removed.