is a small plane of numbers that
is convolved over a big data plane of numbers.
One-dimensional convolution can use the mathematics
of **polynomial multiplication**, such as
*Y*(*Z*)=*X*(*Z*)*F*(*Z*),
whereas two-dimensional convolution
can use something like
*Y*(*Z _{1}*,

The typesetting software I am using
has no special provisions for two-dimensional filters,
so I will set them in a little table.
Letting ``'' denote a zero, we denote a
**two-dimensional filter**

that can be a dip-rejection filter as

(6) |

Fitting the filter to two neighboring traces
that are identical but for a time shift, we see that
the filter (*a*,*b*,*c*,*d*,*e*) should turn out to be
something like (-1,0,0,0,0) or
(0,0,-.5,-.5, 0),
depending on the dip (stepout) of the data.
But if the two channels are not fully coherent, we expect to see
something like
(-.9,0,0,0,0) or
(0,0,-.4,-.4,0).
For now we will presume that the channels are fully coherent.

10/21/1998