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Again, the Amoco 2.5-D dataset provides an excellent test dataset for
comparing flavors of weighting function.
Unfortunately the data-space weights proved susceptible to coherent
noise in the form of multiples not predicted by the modeling
operator. While data-space weights did improve the signal in poorly
illuminated areas, they also boosted up the noise level causing an
increase in NSD. So further work will be required to make this
approach useful.
Stanford Exploration Project
4/29/2001