Challenges are reviewed for multiple-attenuation workflows for shallow-water surveys, including the 3D surfacerelated multiple elimination (3D SRME) workflow as well as workflows that combine wavefield extrapolation and 3D SRME. A proposed workflow improves on 3D SRME results for shallow-water surveys while aiming to remove all surfacerelated multiples rather than just a subset from those multiples.The key step in this workflow is a 3D SRME prediction of freesurface multiples using two input data sets -the recorded data and another data set preprocessed to remove a subset of waterlayer-related multiples. This approach reduces some of the amplitude distortions in the SRME model and leads to overall improvement in results. Properties of the proposed workflow are illustrated with data from two shallow-water surveys acquired in the North Sea with multimeasurement steamers. Processing of the densely sampled 3D shot gathers obtained by joint interpolation and deghosting using the multimeasurement data provides more accurate wavefield extrapolation, better constrained adaptive subtraction, and overall better multiple-attenuation results than processing data from each streamer independently.
This paper discusses the workflow for high-resolution model building and imaging of a broadband multimeasurement towed streamer survey over the Mariner field in the North Sea. The model-building strategy combines the complementary techniques of full waveform inversion (FWI) and reflection tomography to generate an accurate, high resolution and geologically consistent velocity model, using both refraction and reflection energy. The 3D deghosted and reconstructed wavefield generated by the generalized matching pursuit (GMP) algorithm is densely sampled in all directions, and provides the ideal input for imaging techniques such as Kirchhoff prestack depth migration (KDM) and high-frequency reverse time migration (RTM). The combination of such a high resolution earth model and broadband, densely sampled input data provides the significant benefits for both overburden and reservoir characterization in this setting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.