Sergey Fomel
Bureau of Economic Geology,
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8972
Regularization is a required component of geophysical estimation
problems that operate with insufficient data. The goal of
regularization is to impose additional constraints on the estimated
model. I introduce shaping regularization, a general method for
imposing constraints by explicit mapping of the estimated model to
the space of admissible models. Shaping regularization is integrated
in a conjugate-gradient algorithm for iterative least-squares
estimation. It provides the advantage of a better control on the
estimated model in comparison with traditional regularization
methods and, in some cases, leads to a faster iterative
convergence. Simple data interpolation and seismic velocity
estimation examples illustrate the concept
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