Deblending a sparse OBN survey acquired with a generalized survey optimization scheme
Matthew Salgadoe, Bartosz Szydlik, Azat Kuliev, Christopher McMorland · 2024
We present the results of deblending a sparse ocean-bottom node survey located in Green Canyon, in the US Gulf of Mexico. The survey was designed using a constrained optimization scheme (Kumar et al., 2023) which resulted in optimized source locations in time and space. We show that these newly acquired data exhibit more randomization of interfering energy and this can prevent strong interference energy from contaminating weak signal. The high degree of randomization leads to improved deblending results when using an iterative multistage source separation process when compared with a conventional flip-flop-flap simultaneous source shooting scheme. This ultimately leads to better removal of interference noise. The combination of improved shooting geometry and source separation flow provides deblended data that shows uplift to subsalt structures even when imaged with an initial earth model.