Neural network gas chimney identification based on steering cube
Liu Wei1, Chen Xuehua2, He Zhenhua2, Zhang Gulan1, Tang Xiangrong2, Cai Hanpeng3, Gao Gang2
1. Development and Production Seismic Division,BGP Inc.,CNPC,Zhuozhou,Hebei 072751,China;
2. State Key Lab of Oil & Gas Reservoirs Geology and Exploitation,Chengdu University of Technology,Chengdu,Sichuan 610059,China;
3. Geophysical Exploration Company,Chuanqing Drilling Engineering Co.,Ltd.,CNPC,Chengdu,Sichuan 610213,China
Abstract：Identifying geological bodies such as gas chimney, fautt and satt dome is extremely important for hydrocarbon prediction since they are directly associated with oil & gas migration.These geological bodies have two oriental properties: trend and dip.Interpretation results will be totally different compared with the actual situation these two oriental properties cannot be correctly considered.In this paper, a method for neural networks gas chimney ldentiiication based on steering cube is proposed.With the dip and azimuth information of the steering cube, supervised neural networks analysis extracts best seismic attributes which reflect seismic anomaly.A real data example shows that this method has obvious advantages compared with conventional multi-attributes in chimney ldentification.
