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