Multiples Attenuation for Variable-depth Streamer Data, Shallow and Deep Water Cases

Abstract

Processing the variable-depth streamer acquisition has recently become possible, with a new joint deconvolution algorithm (Soubaras, 2010). In this particular acquisition,called BroadSeis, the receiver depth regularly increases with offset, which allows a wide diversity of receiver ghosts and so increases dramatically the possible frequency bandwidth, in both low & high-frequencies sides. Compared to conventional flat-streamer data, processing BroadSeis data implies a major change: the receiver ghosts are rigorously taken into account. In conventional processing, both source and receiver ghosts are included in a wavelet that is assumed to be consistent from offsets to offsets. On the contrary, with a BroadSeis dataset, the receiver ghosts change from near offsets to far offsets and so cannot be included in a wavelet. This breaks an implicit assumption of many processing steps such as Surface Related Multiple Elimination (SRME). These receiver ghosts will then be removed from the final image with a pre-stack or post-stack joint deconvolution. Of course, the receiver ghost preservation is a constraint for some programs developed for conventional processing. One of the key challenges, presented in this paper, is how to deal with de-multiples techniques and Variable-depth streamer data, in both deep & shallow-water environments.