It is very difficult to predict thin and interbedded is used to attract gas reservoirs of carbonate rock with traditional inversion method. In this paper,parameter weighted synthesis is used to attract up to 35 seismic wave field characteristic parameters from seismic information of thin and interbedded reservoir and to compress and lower dimension through Karhune-Loeve commutation.
In the present investigation main uncertainty handling approach includes weighted parameter selection (of geometric fusion) by a trained neural network that is not available in standard manipulator robotic controller designs.
For example, it will provide a weighted parameter to calculate for important document indexing.
It would also be advantageous to obtain exposure weighted parameter estimates.
These exterior orientation estimates are then used as weighted parameter observations in a bundle adjustment.