Applications to 3-D data

As discussed in Chapter , 3-D Kirchhoff datuming has the same algorithmic form as 2-D datuming. The Kirchhoff algorithm is well suited to 3-D data because it can accommodate any geometry; however, the same types of sampling issues which apply to 3-D migration will apply to 3-D datuming.

In many cases, the success of the datuming result will be highly dependent on data coverage. The simplest 3-D land acquisition geometry is one in which receivers cover the whole acquisition surface; sources are shot into this patch array. If the source and receiver locations cover the same area, datuming by extrapolating shot and receiver gathers can be implemented in a very straightforward manner. The critical issue is that the source sampling is often much sparser than the receiver sampling in 3-D. This could require data interpolation and lead to an increase in data volume.

Under conditions where the near-surface propagation is nearly vertical, but not close enough to vertical for static shifts to be valid, it would be adequate to perform 2-D Kirchhoff extrapolation along lines of shots and receivers. This could be viewed as a compromise that is better than statics, but which assumes that out-of-plane near-surface propagation is minimal.