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Discussion

It is worth repeating that it is the simplicity of the flat layer model which makes the standard design approach so inflexible. This in turn forces compromises between the geophysical requirements of the survey and its cost. Moreover, since the geometry is fixed, subsurface variations would imply variations in the illumination as well. Exploiting all the available subsurface information has two main benefits: first, it allows target illumination to be the main goal of the design, and second it allows the geometry parameters to be locally optimum to satisfy the target local characteristics, such as depth, dip, curvature or presence of fractures.

Although not illustrated here, the resulting geometry should be used to compute illumination maps of the subsurface targets to make sure that the resulting illumination is indeed appropriate. If it is not, the density of rays in the problem areas may be increased and the process repeated perhaps with more relaxed constraints. Also, comparison with illumination maps computed with standard geometries should allow a better appreciation of the quality of the final design.

Different source-receiver geometries can be tested against each other by the optimization process, and, if desired, the optimum geometry can incorporate elements of each. Notice also that sources do not need to be along continuous lines (in land acquisition at least) and this fact can be exploited to improve the fit of the geometry to the emergence position of the rays, that is, to the illumination. The receivers are forced to be stringed together, but even so, we can use additional strings and stagger them to allow some flexibility without upsetting the logistics of the acquisition.

Another advantage of the methodology proposed here is the information we can gather about the relative contribution of each source (or group of sources), to the target illumination. This is important when we try to overcome obstacles that prevent us from placing sources or receiver in their design positions. A river, for example, may force the displacement of sources or receivers several hundred meters. If the path of the river is known, we can use it as a constraint in the placement of sources and receivers in the optimization stage to compute the best geometry compatible with it. Even if we can't anticipate the presence of the obstacle at design time, we can still benefit from our knowledge of how much contribution the affected sources or receivers have on the target illumination. This information is of great help in choosing alternative positions to make up for those sources or receivers.

Finally, I would like to emphasize that the most important contribution of my methodology is flexibility. I have illustrated only one issue here, that of shallow targets, but you can easily think of other issues that would benefit from the more flexible approach. What constraints and what relative weights to assign to each one is clearly a problem-dependent decision and should reflect all the subsurface knowledge as well as the particulars of the survey.


next up previous print clean
Next: Conclusion and Future Work Up: Alvarez: 3-D survey design Previous: The bottom line
Stanford Exploration Project
7/8/2003