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《Geological Science and Technology Information》 2007-03
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Flow Unit of the Clastic Rock Reservoir with ANN Technique on Genetic Algorithms

LI Hai-yan,PENG Shi-mi(School of Resource and Information,China University of Petroleum,Beijing 102249,China)  
Taking the middle member of Shahejie Formation in Wen72 block as an example,the pattern recognition method based on genetic artificial neural network is used to study flow units of the clastic rock reservoir.Based on the cluster analysis of core wells,six parameters including flow zone index,porosity,permeability,median grain size,mud content and max pore throat radius,are selected to classify the flow units into four types.Then the neural network pattern recognition method is used to identify the flow unit types in all wells of Wen72 block by building learning and predicting models.At the same time,the analysis of the characteristics of each flow unit and the simulation of the sequential indicator simulation make it possible to realize the time-space distributions of four flow unit types.A comparison of the spatial distribution of reservoir flow units with the sedimentary micro-facies shows that the main flow units with superior reservoir petrophysical properties lie in the middle of the channels and mouth bars,the main sedimentary micro-facies with superior controlling properties.The flow units show better underground structure of the reservoir fluid flowing than the sedimentary micro-facies.It is believed that the distribution of remaining oil can be forecasted by studying the flow units.
【Fund】: 国家“973”项目重大基础研究前期研究专项(2002CCA00700)
【CateGory Index】: P618.13
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