# Robust deblending of simultaneous source seismic data

## TL;DR

This paper introduces a robust inversion-based deblending algorithm for simultaneous source seismic data that effectively handles situations where traditional incoherence assumptions fail, improving seismic data quality.

## Contribution

The paper presents a novel robust deblending method that overcomes limitations of existing techniques by handling noise, amplitude variations, and non-random shooting times.

## Key findings

- Effective removal of interference in challenging conditions
- Improved seismic data quality in noisy environments
- Robustness to non-ideal acquisition scenarios

## Abstract

Simultaneous source seismic acquisition is an efficient method of seismic surveying that can considerably reduce the cost of high density seismic acquisition. The method results in overlapping records, or interference, that must be removed prior to subsequent processing. Deblending methods typically rely on the incoherence of the blending noise relative to the underlying signal. There are many common situations where these assumptions break down, for instance, when the underlying signal contains noise or erratic amplitudes, or when shooting times are not sufficiently random. We present a robust inversion based deblending algorithm that can overcome these challenges.