Suppressing random noise to broaden the useful bandwidth of seismic reflection data

The signal-to-noise ratio (SNR) of seismic reflection data in many areas is rather poor and conventional two-dimensional filters designed to suppress noise with different moveout from the signal tend to generate artifacts. We have extended a method of multichannel filtering, based on the hypothesis that signals on adjacent channels are similar, for enhancing the SNR on stacked sections. Using only the mid-range frequencies where the SNR is highest, the event trend is found for overlapping windows on the section and the average signal vector is calculated. Then the data from the full bandwidth section are projected onto the spatially varying unit similarity vectors and the results are merged for the overlapping windows. Application of the method to synthetic data containing steeply dipping events and to a stacked section for a marine 2D line has produced good results. The modifications we have introduced carry a small overhead in computing time but they should enable the method to be used effectively even on sections containing steep dips.