This work shows a cascaded internal multiple attenuation workflow based on top-down inverse scattering series (ISS) predictions followed by adaptive subtraction. The ISS multiple modeling is purely data driven and does not assume a priori subsurface information such as velocity field and known generating horizons. Adaptive subtraction is employed to match the predicted model with the internal multiples present in the data set. A case study using the topdown cascaded workflow was applied to a pre-stack field data set located in western Alberta, Canada, where the interval between the Duvernay formation and the shale/basin contact is contaminated by strong internal multiples. The workflow attenuated most of the internal multiples present in the target zone, improving the overall primary resolution and highlighting weak events previously hindered by multiples.

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.

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