Many seismic processing techniques require integration of the data. This integration is commonly done using a binning technique. Binning techniques work well if the integration grid is regular. In practice, however, this is often not the case. We describe an alternative integration technique that takes irregular sampling into account, by assigning weights to the integration points. The weights are computed by triangulating the integration domain.<br><br>The two algorithms were tested on a synthetic dataset and a marine dataset from the Gulf of Mexico. The irregular imaging gives better results than the binning method in the cross line direction: acquisition footprints are reduced, resulting in clearer images. In the inline direction there is not much difference between the two methods. Since the irregular imaging algorithm is easy to implement and the additional CPU is negligible, it is an attractive alternative to binning.


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