Focal Deblending Using Smart Subsets of OBN 5D Data

Abstract

SummaryAlthough theoretically straightforward, adapting focal deblending to realistic 5D acquisition scenarios can be challenging in practice. The two main issues that have to be dealt with are insufficiently sampled spatial dimensions and the computational effort needed for the deblending inversion. In order to deal with both issues, we propose dividing the data in 'smart' subsets, specialized for the acquisition type. Then, the deblending problem can be divided into a number of smaller problems that can be solved independently. The focal transform used for the deblending is also redefined to fit the geometry of the subsets. We examine the case of OBN acquisition and test the performance of the proposed scheme on numerically blended field data.

Focal deblending: Marine data processing experiences

“…(2016), a deblending comparison between the double focal transform (using one‐way propagation operators) and the single‐sided focal transform (using two‐way propagation operators) can be found. The single‐sided focal transform was then used in the smart sub‐set implementation of focal deblending for ocean bottom node (OBN) surveys (Kontakis & Verschuur, 2017a). A focal‐curvelet hybrid approach was investigated in Kontakis and Verschuur (2017b) on synthetic data.…”

“…In this work, all theory from previous publications, pertaining to marine data processing with focal deblending, is aggregated in one place. The OBN example found in Kontakis and Verschuur (2017a) is revisited, this time using a blending code that leads to a more difficult deblending problem. In addition, a new, challenging towed streamer example is presented.…”