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A 3-D field data example

I show with a 3-D field data example that the subtraction method works better than the filtering approach. The dataset is also used in Guitton (2003). Figure [*] shows the input data with an overwhelming amount of noise. For the subtraction and filtering methods, I use 3-D non-stationary prediction-error filters (PEFs) to approximate the modeling and inverse covariance operators, respectively. These filters have been estimated with a weighted PEF estimation scheme Guitton (2003) to take into account the amplitude variations in the data. The PEFs are estimated from a noise and signal model that I computed by band-passing the data: 0. to 45 Hz filtering for the signal model and 35 to 125 Hz. filtering for the noise model. Note that with the subtraction method, the modeling operators are computed with inverse PEFs. Unfortunately, these inverses are not guaranteed to be stable Rickett (1999). Therefore, with PEFs, the subtraction method might not be always feasible.

Figures [*] and [*] show the noise attenuation results for the filtering and subtraction method, respectively. Note that the PEFs and the patches for the two methods are identical. In addition, the convergence of both methods during the noise attenuation phase is very similar. It is interesting to notice that the subtraction method gives a cleaner panel, with more continuous reflectors everywhere. The amplitudes are also stronger with the subtraction method, as seen in the time slice section.

 
data3d
data3d
Figure 1
A near-offset section of a 3-D land survey. Some signal is visible near 0.42 s. This section is contaminated with ground-roll. The amplitude varies across time and offset with missing traces as well.
[*] view burn build edit restore

 
separ-ns-weight-AGC-3d
separ-ns-weight-AGC-3d
Figure 2
Estimated signal with the filtering approach. The noise is well attenuated.
[*] view burn build edit restore

 
separ-ns-weight-AGC-nemeth-3d
separ-ns-weight-AGC-nemeth-3d
Figure 3
Estimated signal with the subtraction method. The signal is stronger and more continuous than in Figure [*].
[*] view burn build edit restore


next up previous print clean
Next: Conclusion Up: Guitton: Signal/noise separation Previous: Why is it working
Stanford Exploration Project
7/8/2003