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A reliable velocity estimation in a complex deep-water environment using downward continued long offset multi-channel seismic (MCS) data

Abstract : The estimation of a reliable velocity-depth model from towed streamer marine seismic data recorded in deep water, especially with a complex seafloor environment, is challenging. The determination of interval velocities from the normal move-out (NMO) of the reflected seismic signals for shallow reflectors (<1 km below the seafloor) is compromised by the combination of a long wave path in the water column and the complex ray paths due to topography, leading to small move-out differences between reflectors. Furthermore, low sediment velocities and deep water produce refraction arrivals only at limited far offsets that contain information about deeper structures. Here, we present an innovative method where towed streamer seismic data are downward continued to the seafloor leading to the collapse of the seafloor reflection and the emergence of refraction events as first arrivals close to zero offset, which are used to determine a high-resolution near surface velocity-depth model using an efficient tomographic method. These velocities are then used to perform pre-stack depth migration. We found that the velocity-depth model derived from tomography of downward continued towed streamer data provides a far superior pre-stack depth migrated image than those produced from velocity-depth models derived from conventional velocity estimation techniques.
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Submitted on : Friday, February 25, 2022 - 7:37:34 PM
Last modification on : Friday, August 5, 2022 - 12:01:21 PM

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Dibakar Ghosal, Satish C. Singh. A reliable velocity estimation in a complex deep-water environment using downward continued long offset multi-channel seismic (MCS) data. Journal of Earth System Science, 2021, 130, ⟨10.1007/s12040-020-01531-9⟩. ⟨insu-03589769⟩

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