Swell noise attenuation is the first step in the processing sequence of marine seismic data. Often this filtering requires a good amount of testing to achieve optimal results, particularly when swell noise characteristics vary considerably along the survey. In the context of on-board processing this filtering is the bottleneck of the production sequence. It would be very useful both technically and economically if there exists a solution that automate this process. This paper proposes a data driven method for swell noise attenuation. It is based on improving the detection of swell noise by deriving its characteristics from the data. The filtering parameters are automatically tailored to suit the spatial and temporal frequency spread of swell noise in each filtered gather. When compared to a conventional method, it gives similar results but with much less testing effort. It is highly data adaptive and can be used to attenuate gathers with different noise level using the same minimal parameterisation.


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