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The Use of Coherence Cube Visualization in Picking Seismic Processing Parameters and Post Processing Hybrid Visualization Products
This talk details the use of Coherence cube visualization as an additional Q.C. tool to define processing parameters. In addition, combining other attributes in the coherence measurement can form custom visualization cubes.
Traditionally, processing analysts Q.C. their product by displaying inlines and crosslines from a 3D volume either on paper or interactively on their computer screen. The third dimension in a 3D volume is an amplitude slice. The amplitude slice, while offering a different view of our seismic data, does very little to help us understand processing improvements or see depositional environments.
Migrating and producing a coherence cube on each step within the processing sequence has given us a way to view a third dimension of our seismic data as a coherence time slice or a horizon slice. By viewing the data in this fashion we are able to see subtle differences in processing parameters which are not apparent by viewing inlines and crosslines alone. Some of the processes are: geometry, static's, dmo, migration velocity evaluation, migration algorithm evaluation and signal to noise evaluation.
The final result of this evaluation is normally a pre-stack time migrated seismic volume and a final coherence volume. Depending on the geology, we are able to combine other seismic attributes with coherence measurements to directly define hydrocarbons or define facies changes such as the boundary between sand and shale.
The paper details the use of coherence cube visualization as an additional quality control tool to define processing parameters. The added resolution that coherence cube gives us in the time slice and horizon slice domain allows us to see subtle differences in processing parameters which are not always readily apparent while looking at conventional displays of our seismic inlines and crosslines. The detailed examples will show the benefits and power of using coherence cubes to visualize the data during each step of the processing sequence.
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