Improving Multiple Removal by Cooperative Matched Filtering

The suppression of multiple events is a crucial task in seismic marine data processing and several multiple elimination techniques have been addressed in the last 20 years. Both model-driven as well as data-driven methods has been successfully developed to deal with various kind of subsurface structures and using different physical-mathematical approaches. Best results are often obtained by cascading different removal tools, each one focused on a single family of multiple events. However, this kind of processing scheme weights down the adaptive filtering task that has to be performed in each chain step with a consequent increasing of primaries corruption. In this paper we present an integrated subtraction scheme that allows to jointly remove different kind of multiples, predicted from as many techniques, simultaneously.