Although the modeling algorithm is not the focus of this paper, we
modeled surface-related multiples with a very fast 1-D algorithm.
The multiple model was simply the multi-dimensional autoconvolution of
common midpoint (CMP) gathers Kelamis and Verschuur (2000).
This auto-convolution reduces to a multiplication in the *f-k*
domain, and so it can be performed rapidly with multi-dimensional
FFT's.
More accurate multiple modelling algorithms will
better attenuate multiples associated with the dipping
salt-flanks. However, in 3-D examples, multiple prediction will always
be imperfect, so we were interested in how this algorithm would adapt
under less than ideal conditions.

Figures 1 and 2 show common-midpoint
and common-offset sections before and after multiple suppression.
With an imperfect multiple model, there is always a trade-off between
suppressing multiples and preserving primary energy.
For these results, we took a conservative approach - although some
multiple energy remains in the data, hopefully all the primary energy
remains too.
In the areas with no salt present (e.g. `cmp_x`>10000 m), the
multiples are almost entirely eliminated. However, in areas below the
salt, especially where steeply-dipping diffracted multiples are
present, some muliple energy remains.

Figure 1

Figure 2

4/29/2001