Multiple subtraction

In this section, the multiple model computed in the preceding section is subtracted from the data with two techniques. The model is obtained after shot interpolation with the sparseness constraint. The first technique is a pattern-based method introduced in Chapter that separates primaries from multiples according to their multivariate spectra. These spectra are approximated with prediction-error filters. The second technique adaptively subtract the multiple model from the data by estimating non-stationary matching filters (see Chapter ). The two methods are now briefly described.

 

• Pattern-based approach
• Adaptive subtraction
• Comparing the two methods
• Field data results