The multiple prediction step, crucial for the success of the whole algorithm, involves one important assumption about the data acquisition geometry, that a source/receiver pair is needed wherever a multiple reflects. The Delft approach is quite successful in 2-D problem Verschuur and Prein (1999), since the assumption is relatively easily satisfied in the conventional 2-D acquisition geometry, which is not the case in 3-D.
Two different directions have been taken to resolve the conflict. One is to massively interpolate the trace at missing source and receiver positions to attain a dense coverage of the surface van Dedem and Verschuur (1998). However, the computational cost of this method is huge. The other is to predict the multiple based on the 2-D theory and then extend the subtraction step to handle incorrectly predicted multiples Ross et al. (1997); Ross (1997). The success of this approach is restricted to relatively simple 3-D cases.
This paper proposes an approach designed for the multi-streamer geometry. Two distinctive features make it more practical. First, this approach finds the most reasonable proxy from the collected dataset for any missing trace. There is no need to interpolate missing streamers and shotlines. Second, using a concept I call the partially-stacked multiple contribution gather (PSMCG) together with the multi-scale PEF theory Claerbout (1992), the proposed approach interpolates the PSMCG in the cross-line direction to get a densely-sampled multiple contribution from all possible Huygens' secondary sources before the summation step to remove aliasing noise.
Two numerical examples in the paper demonstrate how the approach works.