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This step can be accomplished either by interpolating linearly along
the picked dip or by finding missing traces which minimize the filtered output.
A shortcoming of the former approach is that it cannot handle more than
one dip at a point, which happen at the crossing of linear events.
I choose the latter approach, which finds missing traces by minimizing
the filtered output using the filter simulated from the previous section.
For minimization, I use Claerbout's conjugate-gradient
algorithm (Claerbout, 1991) because other algorithms must
formulate the problem in the form of known values, splitting unknown values,
which is very difficult if unknown values are randomly spread among
known values.

** Next:** Summary of the algorithm
** Up:** THREE STEP INTERPOLATION
** Previous:** Simulating PEF using dips
Stanford Exploration Project

11/18/1997