Multiple attenuation using multifocusing technology

The removal of multiples energy on seismic data has been a major issue on many datasets worldwide. The primary advantage of MultiFocusing (MF) is the enhancement of the signal-to-noise ratio of both stacked sections and prestack data through stacking a much larger number of traces than in conventional CMP processing. We present a modification of the MF-based approach when multiples are recognized directly in the MF attribute domain. First, they are predicted according to MF wavefront parameters and then they are subtracted using an adaptive least squares method. The key elements of the proposed procedure are the MF attributes. We identify and predict the multiples in the MF attribute domain through interpretation of the RMS velocity and emergence angle panels, which are determined from the pre-stack data during the MF multidimensional analysis. We compute a multiple model based on the partial coherent summation of the original data along the predicted traveltime surfaces. For the final stage, we adaptively subtract the predicted multiples from the original data using a least squares adaptive subtraction procedure similar to SRME-type multiple attenuation methodology. We presented a multiple attenuation methodology using MF applied on a real data example.