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I present a method for missing-trace interpolation of linear events.
For a two-dimensional dataset which contains linear events,
a post-interpolation spectrum can be estimated from a portion of
the original aliased spectrum.
The restoration of missing trace data is accomplished by minimizing
the energy after applying a filter which has an amplitude spectrum
that is inverse to the estimated spectrum.

Stanford Exploration Project

12/18/1997