Figure 1

For this experiment I decided to create five random perturbed models in the first non-linear iteration. From these five models I generated twenty five models during the second non-linear iteration. I then used these twenty-five models in a conventional migration velocity updating scheme. This gives some measure on the effect of the starting guess on the final solution. Each of the twenty-five models were equally reasonable points from which start a tomographic loop. The difference between the final images gives me some measure of the uncertainty in this updating scheme.

The left panel of Figure shows my starting guess for the velocity problem. The right panel shows the resulting image. The velocity was created by applying a strong smoother to the correct velocity field then scaling the resulting model by .9. Figure shows the results after one non-linear iteration. The top panel are the five realizations of . The center panels are the resulting five velocity models, and the bottom five panels are the migrated images using these velocity models. The anticline trend is in all of the realizations but we still see significant differences in how the velocity estimate deals with the listric fault.

Figure 2

Figure 3

After four iterations, now with twenty-five different models, the differences are more dramatic. Figure show the twenty-five different gamma panels. We see an overall reduction in the amount move-out (closer to gray), but the realizations still have significantly different character. The twenty-five velocity models (Figure ) also show significant variation, especially as we go deeper in the model. After four iterations we see significant differences in the images (Figure ). In most of the models we have focused the anticline structure, but the images have significant variation below. The basement reflectors are discontinuous in many of the models.

Figure 4

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Figure 6

10/23/2004