Title : 
A pattern recognition approach to detect oil/gas reservoirs in sand/shale sediments
         
        
            Author : 
Yao, Zheng-He ; Wu, Li-De
         
        
            Author_Institution : 
Shanghai Bur. of Marine Geological Survey, China
         
        
        
            fDate : 
30 Aug-3 Sep 1992
         
        
        
        
            Abstract : 
A hybrid structural and statistical pattern recognition approach to detect oil/gas reservoirs in sand/shale sediments is presented in the paper. On the basis of the sand fiducial profile derived from log data and seismic data, a tree-based region-detecting method is used to detect sand layers, and a Marr´s-operator-based clustering algorithm is used to find oil/gas reservoirs in the detected sand layers. The ability of the approach is demonstrated by a real-data example
         
        
            Keywords : 
geophysical prospecting; geophysical techniques; geophysics computing; pattern recognition; seismology; Marr´s-operator-based clustering algorithm; geophysical prospecting; hybrid structural/statistical pattern recognition; oil/gas reservoirs; sand fiducial profile; sand/shale sediments; seismology; tree-based region-detecting method; Application software; Clustering algorithms; Computer vision; Geology; Hydrocarbon reservoirs; Impedance; Partial response channels; Pattern recognition; Petroleum; Sediments;
         
        
        
        
            Conference_Titel : 
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
         
        
            Conference_Location : 
The Hague
         
        
            Print_ISBN : 
0-8186-2915-0
         
        
        
            DOI : 
10.1109/ICPR.1992.201818