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Pseudo-primary generation from field data

The pseudo-primary-contribution gather, shown in Figure 13, does contain the water-bottom, top-of-salt, bottom-of-salt reflections, and water-bottom multiples, caused by the correlation between the water-bottom reflection and the first-order multiple of the water-bottom, top-of-salt, bottom-of-salt, and second-order water-bottom multiple, respectively. This cube is a series of cross-correlations of single traces, with no amplitude scaling or additional deconvolution performed before cross-correlation. The signal-to-noise ratio in the data is lower than that in the synthetic example. The side panel shows the same receiver-pair correlation for multiple shots that are later summed to produce a single output trace.

fieldin
fieldin
Figure 12.
A Gulf of Mexico dataset. The front panel is a constant-offset section, and the side panel is a single shout, with the negative offsets predicted by reciprocity. The image is scaled by $ t^{0.8}$ for display purposes. $ [{\bf ER}]$
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fieldcontrib
fieldcontrib
Figure 13.
Pseudo-primary contribution gather. The front face is a constant-offset section, while the side face contains the shots that will be summed to produce the pseudo-primaries. The image is scaled by $ t^{0.8}$ for display purposes. $ [{\bf CR}]$
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Figure 14 shows the volume of pseudo-primaries generated by summing the cross-correlations from all of the sources in the recorded data. The pseudo-primary data are somewhat poorer than the recorded field data in Figure 12, with the long wavelet present in the original data strongly featured in the pseudo-primaries. Additionally, when compared to the pseudo-primaries in the synthetic case, the quality of the pseudo-primaries for this example is significantly worse. Reviewing three of the points we made about the pseudo-primaries in Sigsbee, we see that these problems are even more pronounced in this field data example. For example, while there were variations in the relative amplitude of the Sigsbee pseudo-primaries, the variations in the pseudo-primaries from the field data are much more obvious; where the water-bottom reflection is dipping, the pseudo-primary reflection is nearly absent, and the pseudo-primaries of the salt body have higher amplitude than anywhere else. Second, the amplitude spectrum in the Sigsbee example was squared as a result of the cross-correlation involved in pseudo-primary generation. The much longer wavelet in the field data makes this more obvious, with the side-lobes of the water-bottom reflection appearing before the water-bottom reflection in the recorded data. This ringing is probably associated with a water bubble from the source. Third, the cross-talk in this field data is also present in this pseudo-primary result. These slight smile-shaped events have a slope the direction opposite that of the desired pseudo-primaries, and are more obvious at farther offsets, although the base of these smiles are at roughly zero-offset in Figure 14.

fieldpseudo
fieldpseudo
Figure 14.
Pseudo-primaries of data. The front face is a constant-offset section, and the side face is a shot gather. The gross structure of the original data is present, but the squared wavelet strongly dominates the data. The image is scaled by $ t^{0.8}$ for display purposes. $ [{\bf CR}]$
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next up previous [pdf]

Next: Interpolation of field data Up: Field data example Previous: Field data example

2009-04-13