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My goal in this paper is to compare three different inversion schemes for the multiples attenuation
problem. They all aim to produce a velocity model where primaries are muted out
and the predicted multiples are subtracted from the original data. I successively solve
- 1.
- ,
- 2.
- ,
- 3.
- ,

and compare the results. I call arbitrarily ``*l*^{1} norm'' any Huber function with
a small threshold. Let us assume now that to the *l*^{1} norm, for the data residual, corresponds
a threshold
In addition, for the regularization term, let us say that to the *l*^{1} norm corresponds a threshold
is chosen smaller than before leading to a larger *l*^{1} treatment of the model.
I show later on that the convergence is greatly reduced by the addition of this regularization term.

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Stanford Exploration Project

4/27/2000