REFERENCES

Canales, L. L., 1984, Random noise reduction: 54th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, Session: S10.1.

Chase, M. K., 1992, Random noise reduction by 3-D spatial prediction filtering: 62nd Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, Session: SP3.4.

Claerbout, J. F., 1992a, Earth $\mbox{S}$oundings $\mbox{A}$nalysis: Processing versus $\mbox{I}$nversion: Blackwell Scientific Publications.

Claerbout, J. F., 1992b, Information from smiles: mono-plane-annihilator weighted regression: Stanford Exploration Project-73, 409-420.

Gulunay, N., Sudhakar, V., Gerrard, C., and Monk, D., 1993, Prediction filtering for 3-D post-stack data: Preprint of an article submitted for the 63rd Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts.

Gulunay, N., 1986, FXDECON and complex Wiener prediction filter: 56th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, Session: POS2.10.

 

yplanesld
Figure 4 A comparison of smearing on with one- and two-pass t-x prediction. The top cube is the input, the middle cube is the result of a one-pass three-dimensional t-x prediction, and the bottom cube is the result of two passes of one-dimensional t-x prediction in the inline and crossline directions. The one-pass result shows no smearing of the fault; the two-pass result shows a smeared fault image.

 

Arcoorig
Figure 5 The input to the t-x and f-x predictions. A significant amount of noise is seen here.

 

Arcofx2d
Figure 6 The result of two passes of two-dimensional f-x prediction processing. While this result is an improvement over the input, some of the details is seen to be lost when compared to the three-dimensional f-x prediction.

 

Arcofx3d
Figure 7 The result of three-dimensional f-x prediction processing. This result preserves the details lost in the two-dimensional f-x prediction.

 

Arcotx2d
Figure 8 The result of two passes of two-dimensional t-x prediction processing. While this result is an improvement over the input, some of the details is seen to be lost when compared to the three-dimensional t-x prediction. More noise has been attenuated than with the two-dimensional f-x prediction.

 

Arcotx3d
Figure 9 The result of three-dimensional t-x prediction processing. This result preserves the details lost in the two-dimensional t-x prediction.