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Using a PEF to approximate the covariance matrix
(equation (1)) leads to a proper filtering of the coherent
noise present in the data. Nonetheless, this PEF has to estimate
accurately the noise pattern. If a noise model does not exist,
the PEF can be calculated from the residual of a previous inverse
problem in which no attempt has been made to attenuate the noise.
The next section describes what I call the subtraction
method which does not filter the noise but rather predicts it. This
method has the ability to decrease the effects of signal/noise
correlations.

** Next:** Subtracting coherent noise
** Up:** Approximating the noise covariance
** Previous:** Filtering the coherent noise
Stanford Exploration Project

4/29/2001