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Combined inversion: preconditioning with regularization

Marie L. Clapp

ABSTRACT

Iterative inversion schemes are becoming more common in seismic processing. The high cost of the operators generally used in these inversion schemes makes it very important to minimize the number of iterations needed to obtain a good model. In complex environments, inversion schemes can be improved by styling the model through regularization or preconditioning. At early iterations, regularization provides a result that has a frequency content comparable to that of the ``ideal'' model. Preconditioning defines a solution at every model point at earlier iterations than regularization. An ``improved'' model should combine these two characteristics. This paper examines a scheme that uses the result of preconditioned inversion as an initial model for regularized inversion. I show that this scheme allows us to obtain an improved model in fewer iterations than would be needed for preconditioned inversion or regularized inversion alone.



 
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Stanford Exploration Project
11/11/2002