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In least-squares fitting goals, the regularized inverse interpolation problem
can be stated as follows:
| |
(7) |

| (8) |

| (9) |

Operator maps traces in a gridded model to the earth's
continuous surface. Operators and are ``steering
filters'' Clapp et al. (1997) in the *x* and *y* direction, respectively.
The steering filters are initialized with a space-variable dip function and
decorrelate events which have that dip, and tend to steer the estimated model
along the dip direction. In this fashion we impose our prior model covariance
estimate on the missing traces. Scalars and balance
the two model residuals [equations (8) and (9)] with
the data residual [equation (7)].

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Stanford Exploration Project

10/14/2003