Despite recent dramatic advances in data processing and imaging algorithms, optimizing the acquisition geometry of seismic data still has a dominant effect on the quality of the seismic image. Optimizing acquisition is especially important when heterogeneous geology, such as salt, and acquisition holes caused by obstacles create irregular illumination.
We present several methods for analyzing illumination by using the same RTM that will be later used for imaging the acquired data. These methods are:
1) Migration of white noise filtered along dip of a desired horizon
2) Migration of white noise filtered for fault resolution along a horizon
3) Modeling and RTM migration of density blocks.
4) Analysis of the RTM imaging contribution of each shot to the illumination of a target.
We demonstrate these methods on the SEAM Gulf of Mexico model and compare our predicted results with the actual images.
Using RTM with its accurate wave propagation provides a wave equation based measure of illumination. Just as RTM was shown to produce better migration images than ray tracing Kirchhoff migration methods, we think wave equation illumination methods are more accurate than conventional ray tracing illumination methods.
Resolution of faults is often a vital feature, but since illumination is direction based, illumination maps of horizons do not accurately predict whether the faults are smeared. However, proper horizon analysis of RTM noise output and density block modeling can predict whether faults are smeared.
Moreover, using the same or similar RTM for illumination analysis as for later imaging provides a more accurate prediction of the expected target resolution than using a different imaging algorithm. Not only do RTM algorithms provide some illumination balancing that we want to capture in analysis, there are other algorithm features that influence imaging that are best captured by