Recent case study examples have demonstrated how imaging with multiples could extend imaging with primaries, providing processing solutions in cases of insufficient illumination of targets by primaries. While imaging all multiples as signal would provide the largest increase in illumination with respect to imaging primaries only, it would suffer also the most from cross-talk noise generated during imaging.

Here we discuss properties of processing methods (as opposed to inversion methods) that use selected subsets of multiples to achieve fit-for-purpose objectives in extending images from primaries. We illustrate these methods with examples using 3D streamer data in a test area with water depths ranging from shallow to deep. We note that source-side multiples contribute effectively to fill gaps between source lines, while receiver-side multiples contribute to increased resolution (reduced near offset gap) and broader range of angles available for analysis of shallow targets. We customize our pre-processing of the data and our imaging methods for selected subsets of multiples thus minimizing crosstalk noise. We discuss an example application of shallow imaging providing input to better attenuation of multiples and conditioning of data for imaging of deep targets.


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