Imaging with surface multiples on OBN data with large acquisition gaps

Multiples have now become a useful commodity in seismicimaging as they travel different paths compared to primary waves, thereby extending the illumination of the subsurface. With the popularity of acquisition using ocean-bottom nodes (OBN), it becomes necessary to explore the different strategies of imaging with multiples rather than removing them. We discuss few such methods of using surface-related multiples to get around the problem of imaging with a large acquisition gap, e.g., due to a platform. We test the ‘linear’ least-squares imaging method that incorporates surface-related multiples via re-injection of measured data on numerically generated OBN data with a large acquisition gap. To reduce the dependency of such methods on dense surface acquisition, we will propose a ‘non-linear’ inversion approach in which the surface multiples are modeled from the original source field. Further improving the imaging result with such acquisition constraint, we build a ‘hybrid’ method that combines the ‘non-linear’ imaging method with the conventional ‘linear’ multiple imaging method. We demonstrate the methods on 2-D numerical data. Despite large acquisition gaps, the results indicate mitigation of effects on the image previously caused by incomplete data.