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FIELD DATA TESTS

I scanned the forty Yilmaz and Cumro shot profiles for strong low-velocity noises and I selected six examples. To each I applied an AGC that is a slow function of time and space (triangle smoothing windows with triangle half widths of 200 time points and 4 channels). Since my process simultaneously does both low velocity rejection and deconvolution I prepared more traditional 1-D deconvolutions for comparison. This is done in windows of 250 time points and 25 channels, the same filter being used for each of the 25 channels in the window. In practice, of course, considerably more thought would be given to optimal window sizes as a function of the regional nature of the data. The windows were overlapped by about 50%. The same windows are used on the steep-dip deconvolution.

Unexpectedly, results in Figures 1-6 show that the conventional 1-D deconvolution also suppresses low velocity noises. An explanation can be that these noises are often either low frequency or quasimonochromatic.

 
wz.09
wz.09
Figure 1
Bottom is an Alaska vibrator shot profile (Y&C #09) after AGC. Middle is gapped 1-D decon. Top is steep-dip decon.


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Filters are never allowed off the edges of their application windows. Thus on all the deconvolutions at early times you see zero valued output of duration equal the filter length. Likewise, on the steep-dip deconvolutions, you see some missing output traces along the sides. The number of missing traces matches the halfwidth of the filter. These missing outputs may be unacceptable in a production environment. Fundamentally, my process cannot work ideally along the edges, but with a little extra coding, nonzero but nonideal outputs could be produced there. More drastically, you can imagine spatially one-sided filters like

                 x  x  x  x  x
                 x  x  x  x  x
                 .  x  x  x  x
                 .  x  x  x  x
                 .  .  x  x  x
                 .  .  x  x  x
                 .  .  .  x  x
                 .  .  .  x  x
                 .  .  .  .  .
                 .  .  .  .  .
                 .  .  .  .  1
being applied on one side of the shot with the opposite orientation being applied on the other side. Such filters would not have missing outputs at wide offset, but would have an inner offset problem. The advantage of a double sided filter is that it should be able to extinguish backscattered noises as well as direct noises. We see this effect on Figure 4, but unfortunately, there are no interesting signals beneath the backscattered noises. I did not test the spatially one-sided filters, though it is simply a matter of changing a parameter in the existing code.


previous up next print clean
Next: ARE FIELD ARRAYS REALLY Up: Claerbout: Steep-dip deconvolution Previous: WHICH COEFFICIENTS ARE REALLY
Stanford Exploration Project
11/17/1997