Shot-domain deblending using least-squares inversion

Abstract

Simultaneous source acquisition, which allows a temporal overlap between shot records, has significant advantages to improve data quality (e.g., denser shooting) and reduce acquisition cost (e.g., efficient wide-azimuth shooting). We have developed a novel shot-domain deblending approach for a wide-azimuth simultaneous shooting survey based on an inversion scheme. The inverse problem is formulated by introducing two convolution operators that can respectively destruct the signal and interference and is solved by a conjugate-gradient algorithm in the least-squares sense. Our approach breaks down the limit that source separation can only be implemented in some domains other than the shot domain based on the incoherency principle. Our shot-domain approach does not require the random dithering time; thus, it is very flexible to use in a wide-azimuth simultaneous shooting survey. Three numerically blended synthetic examples were developed to demonstrate the excellent performance of our method. The feasibility has been further validated via a field-data example that is numerically blended from two realistic marine towed streamers.