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《Petroleum Geology and Recovery Efficiency》 2008-05
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Application of fuzzy optimization neural network in Ma5_1,reservoir identification in the central Changqing gas-field

Kuang Jianchao,Zeng Jianyi,Wang Zhong. Business College,Chengdu University of Technology,Chengdu City,Sichuan Province,610059,China  
The Ordovician Majiagou Formation in Ordos Basin belongs to dense reservoir with very complex lithology.Reservoir identification is the key issue and also one of the difficulties in natural gas development in this area.Considering the low accuracy and precision of traditional reservoir identification method,the fuzzy optimization neural network based on particle swarm algorithm was applied to identify the gas strata,water strata and dry zone in the reservoir.Ninty-two samples were acquired by zonal testing from the selected nineteen wells in central gas-field of Changqing.According to the analysis of parameters of physical property,logging,storage-permeability characteristics etc,five dominant control factors(resistivity,natural gamma-ray,productivity coefficient,storage-permeability factor and media type factor)were selected as the input of the model,and reservoir capacity assignment was selected as output.Then,a new reservoir identification model was constructed.Two optimization models were selected based on the trial calculation,and the recognition probability of each reached 96.2% and 92.3% respectively.In addition,the correct rate of identification reached 100%.
【Fund】: 2007年四川省学术和技术带头人培养基金(川人办发[2008]24号);; 2008年成都理工大学科研基金项目(Sxyzc08-09)
【CateGory Index】: P618.13
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