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Practical approach to joint imaging of multicomponent data

Chevron Petroleum Technology, San Ramon, California, U.S.

Elena Shoshitaishvili

University of Arizona, Tucson, Arizona, U.S.

Clint Frasier

Consultant, Irvine, California, U.S.

Corresponding author:O. Mikhailov, ovmi@chevron.com

The first 20% of the full text of this article appears below.

Recent advances in the ocean-bottom cable (OBC) acquisition technology allow recording of high quality multi-component data in the marine environment. These data have been used to image reservoirs obscured by gas clouds (e.g., Valhall) and reservoirs with low P-wave impedance contrast that are hard to see in conventional streamer data (e.g., Alba). Further benefits of using multicomponent data in exploration may come from analyzing P-wave (PP) and converted-wave (PS) data jointly to obtain more information about a reservoir than is available from PP data alone.

Joint interpretation of multicomponent data is complicated by the fact that PP data are traditionally imaged in PP time and PS data are imaged in PS time. Thus, the PP and PS images have different vertical scales. To reconcile these scales, an interpreter has to identify events in both images that correspond to the same reflector and then stretch one of the images to match the other. The event identification is not always straightforward because some interfaces generate PP and PS reflections of the same polarity and other interfaces of the opposite polarity. Thus, there may not be a natural choice of troughs or peaks to correlate. To eliminate the need to stretch PP and PS images and to facilitate joint interpretation, we developed a methodology for joint imaging of multicomponent data in depth.

We image PP and PS data in depth by anisotropic pre-stack depth migration. For PS data, our migration algorithm combines P-wave propagation from a source and S-wave propagation from a receiver to a reflection point. The algorithm also handles the OBC acquisition geometry.

Prestack depth migration of multicomponent data requires a complete transversely isotropic (TI) velocity model for the subsurface. This model consists of four parameters: P-wave velocity, S-wave velocity, and . . . [Full Text of this Article]

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