No abstract

No abstract

Ocean bottom node (OBN) SRME that combines OBN and streamer data is known to be an effective way to predict surface-related multiples in OBN data. However, the available streamer data often have limited offset/azimuth coverage. Additionally, the double source wavelets due to the convolution of OBN and streamer data limit the bandwidth (loss of low and high frequency) of the predicted multiples. OBN model-based water-layer demultiple (MWD) overcomes such limitations and is a good complement of OBN SRME; MWD replaces the streamer data with the water-bottom Green's function that has no offset/azimuth limitation and keeps the full bandwidth of the input data. With Gulf of Mexico (GOM) OBN data over the Atlantis field, we illustrate the benefit of joint SRME and MWD over SRME alone with the improved attenuation of low-frequency multiples and water layer-related multiples.

No abstract

No abstract