Abstract: The invention relates to processing seismic data that contains both a desired signal and swell noise. The method is applicable to seismic data is in the frequency-space domain method and comprises determining a signal-only prediction filter from the seismic data at a first frequency at which swell noise is not present, and applying the prediction filter to seismic data at a second frequency at which swell noise is present. This attenuates swell noise in the seismic data at the second frequency. In one embodiment, the prediction filter for a frequency fL, the lowest frequency at which swell noise is present, is determined from seismic data at frequency fH+1, where fH is the highest frequency at which swell noise is present. The prediction filter for a frequency fL+1 is determined from seismic data at frequency fH+2, and so on, so that the prediction filter for frequency fH+1 is determined from seismic data at frequency f2H?L+1.

Abstract: The invention relates to processing seismic data that contains both a desired signal and swell noise. The method is applicable to seismic data is in the frequency-space domain method and comprises determining a signal-only prediction filter from the seismic data at a first frequency at which swell noise is not present, and applying the prediction filter to seismic data at a second frequency at which swell noise is present. This attenuates swell noise in the seismic data at the second frequency. In one embodiment, the prediction filter for a frequency fL, the lowest frequency at which swell noise is present, is determined from seismic data at frequency fH+1, where fH is the highest frequency at which swell noise is present. The prediction filter for a frequency fL+1 is determined from seismic data at frequency fH+2, and so on, so that the prediction filter for frequency fH+1 is determined from seismic data at frequency f2H?L+1.

Abstract: A method of attenuating noise in three dimensional seismic data using a projection algorithm is disclosed. A frequency—space—space (“f-xy”) projection algorithm is used which is a generalization of the f-x projection algorithm. The predictability of the seismic signals in the f-xy domain constitutes the basis of the algorithm. Specifically it is demonstrated that if the seismic events are planar in the t-xy domain, then in the f-xy domain they consist of predictable signals in the xy-plane for each frequency f. A crucial step of the 2-D spectral factorization is achieved through the helical coordinate transformation. In addition to the disclosed general algorithm for arbitrary coherent noise, a specialized algorithm for random noise is disclosed. It has been found that the disclosed projection algorithm is effective even in extreme cases of poor signal to noise ratio. The algorithm is also signal preserving when the predictability assumptions hold.