Historically, seismic migration has been the practice (science, technology, and craft) of collapsing diffraction events on unmigrated records to points, thereby moving (“migrating”) reflection events to their proper locations, creating a true image of structures within the earth. Over the years, the scope of migration has broadened. What began as a structural imaging tool is evolving into a tool for velocity estimation and attribute analysis, making detailed use of the amplitude and phase information in the migrated image. With its expanded scope, migration has moved from the final step of the seismic acquisition and processing flow to a more central one, with links to both the processes preceding and following it. In this paper, we describe the mechanics of migration (the algorithms) as well as some of the problems related to it, such as algorithmic accuracy and efficiency, and velocity estimation. We also describe its relationship with other processes, such as seismic modeling. Our approach is tutorial; we avoid presenting the finest details of either the migration algorithms themselves or the problems to which migration is applied. Rather, we focus on presenting the problems themselves, in the hope that most geophysicists will be able to gain an appreciation of where this imaging method fits in the larger problem of searching for hydrocarbons.

Imaging with separated wavefields (SWIM) is an innovative depth-imaging technology that uses upgoing and downgoing wavefields at the surface to deliver high-resolution images of the subsurface. It takes advantage of the extended illumination provided by surface-multiple energy, and thus, it exploits data that the seismic industry historically has treated as unwanted noise. The fundamental concept behind SWIM is based on using each receiver as a “virtual” source, effectively expanding the surface coverage of the seismic experiment and enhancing the subsurface illumination, particularly for shallow reflectors. By effectively turning the streamer spread into a source (and receiver) array, the resulting equivalent survey has spatial sampling that is much improved and a richer distribution of offsets and azimuths. The improved spatial sampling enhances the angular illumination greatly at every image point. Therefore, SWIM produces densely sampled angle gathers that provide greater opportunities for velocity-model building and for improved interpretation of complex structures. Several issues need to be considered for proper imaging with SWIM: migration-imaging conditions, attenuation of cross talk, and acquisition design. The latter must be addressed to support proper sampling of both upgoing and downgoing wavefields used for imaging. A broad overview and examples of these subjects are presented. Applications to a deepwater wide-azimuth (WAZ) survey from the Gulf of Mexico and a shallow-water narrow-azimuth (NAZ) data set from offshore Malaysia demonstrate the enhanced areal illumination and improved imaging resolution from imaging using multiple-reflection energy.

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We demonstrate a novel workflow using reflections, refractions and multiples for building highly accurate PSDM velocity models for a complex geological setting. By combining wavelet shift tomography, full waveform inversion and separated wavefield imaging, we are able to produce high-resolution velocity models that are ideally suited for imaging of broadband data. Leveraging dual sensor streamer technology and the wavefield separation that comes with it, we are using up-and down-going wavefields in imaging and tomography to improve resolution and illumination. Further, we utilize the refracted, low-frequency energy for FWI. As the streamer is towed deep, we preserve the low frequencies that are so important for the success of FWI, but without sacrificing a broadband signal that is key for producing high-resolution reflection images of the shallow overburden and deep reservoir sections.

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