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Next: Comparison with adaptive subtraction Up: Multiple attenuation: Theory and Previous: Adaptive vs. Pattern based

Gulf of Mexico example

The pattern-based approach is tested on a 2-D line from the Mississippi Canyon. This dataset has been extensively used in the past to benchmark multiple attenuation techniques (special edition of The Leading Edge, January 1999). A stacked section of this dataset is shown in Figure [*]. Strong surface-related multiples are visible below 3 s. The tabular salt near the water bottom generates peg-legs in the data. The shot and receiver spacing is 26.6 m. and the first hydrophone is 100 m. away from the source. Ideally, before using SRMP, the missing short offset traces should be interpolated for improved separation Kabir and Verschuur (1995). No interpolation was performed here, thus creating wrong amplitudes in the multiple model, especially at short offset where amplitudes are zero. Note that SRMP creates a model for all multiples with at least one bounce at the sea surface. For this dataset both adaptive subtraction and pattern-based techniques are compared after migration.

The multiple attenuation starts with the estimation of 3-D PEFs from SRMP and the Spitz approximation. Then multiples and primaries are separated according to their multidimensional spectra. Figure [*] displays the multiple attenuation result for one shot gather outside the salt boundaries (X=4500 m). The multiple model in Figure [*]c demonstrates that the short offset traces are not accurately modeled. However, the estimated primaries (Figure [*]b) and multiples (Figure [*]d) show that the subtraction is working at short and far offsets. This robustness to modeling errors is increased by the smoothing of the filter coefficients during the PEFs estimation.

A second shot gather is shown in Figure [*] from inside the salt boundaries (X=12000 m). The estimated primaries (Figure [*]b) and multiples (Figure [*]d) are again separated well. However, looking closely at the primaries in Figure [*]b, some diffracted multiples seem to have leaked in. These diffractions (Figure [*]) can be either out of plane events or in plane events that SRMP cannot model due to limitations imposed by the acquisition geometry Kabir (2003).

Stacked sections of the input data, estimated multiples and primaries are displayed in Figure [*]. These stacks are located below the salt, as shown in Figure [*]a. The estimated primaries in Figure [*]b are still contaminated with diffracted multiples (shown as M). The multiples are attenuated very well otherwise. Comparing the stack of the multiple model (Figure [*]c) with the stack of the extracted multiples (Figure [*]d) indicates that no prominent primaries have been attenuated.

 
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Figure 19
Stacked section of a 2-D line from the Gulf of Mexico. Surface-related multiples appear below 3 s. Arrow WB indicates the water bottom, TS the top of salt, BS the base of salt, WBM1 the first order water-bottom multiple, TSWBM the top of salt/water bottom pegleg multiple, TSM the top of salt/top of salt multiple, and WBM2 the second order water-bottom multiple.
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Figure 20
Shot gathers outside the salt boundaries at 4500 m for (a) the input data, (b) the estimated primaries, (c) the multiple model with SRMP, and (d) the estimated multiples.
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Figure 21
Shot gathers inside the salt boundaries at 12000 m for (a) the input data, (b) the estimated primaries, (c) the multiple model with SRMP, and (d) the estimated multiples.
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Figure 22
A comparison of stacked sections for (a) the input data, (b) the estimated primaries, (c) the multiple model with SRMP, and (d) the estimated multiples. Some primaries (shown as P) in (b) are recovered while some diffracted multiples (shown as DM), not properly modeled by SRMP, are remaining.
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