--> Abstract: Complex Imaging Challenges Offshore South East India, by Pranaya Sangvai, Ajoy Biswal, Mohit Mathur, Ian F. Jones, Juergen Fruehn, Phil Smith, David King, and Michael Goodwin; #90081 (2008)

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Complex Imaging Challenges Offshore South East India

Pranaya Sangvai2, Ajoy Biswal2, Mohit Mathur2, Ian F. Jones1, Juergen Fruehn1, Phil Smith1, David King1, and Michael Goodwin1
1ION - GXT Imaging Solutions, Westhill, United Kingdom
2Reliance Industries Ltd, Mumbai, India

Imaging in deep water environments poses a specific set of challenges, both in data pre-conditioning and imaging. Off the east coast of India, the transition from the shallower coastal waters to the deep shelf often encounters significant topographical variation in the sea bed, which gives rise to numerous effects which must be dealt with by the processing geophysicist. In addition to deep channels and steep slopes, we also encounter buried channels with low velocity fills and gas hydrates. Diffracted and “out-of-plane” multiples are the norm in these environments and must be eliminated to derive a reliable velocity model and deliver an acceptable structural image. In this paper, we describe our approach to tackling these problems, concentrating our attention on multiple suppression, scattered noise attenuation, iterative velocity model building and depth imaging.

We examine how differential velocity based demultiple methods such as Parabolic Radon which have often been used in deep water fail for complex multiples. In recent years, the SRME technique has become popular in deep water and cascading 2D SRME and Radon has become an industry standard approach. With the advent of 3D SRME, a theoretically more correct approach has become available, and here we demonstrate its effectiveness as compared to the ‘conventional’ approach.

In order to derive a velocity model for depth imaging we used a hybrid-gridded approach, where we combined conventional gridded tomography, high resolution gridded tomography, auto-picked layers, and detailed manually interpreted layers. Using such an approach for data offshore eastern India has resulted in an improvement in image quality compared to a recent pre-stack time migration, avoiding the structural distortion introduced by localized velocity variation in the near surface sediments, delivering gathers suitable for attribute work.