针对渤海湾盆地冀东油田南堡2-1区东营组存在大量低对比度油气层,常规测井方法不能准确评价其含油性的问题,引入自然伽马相对值、视地层水电阻率作为有效参数,运用测井图版识别法,剔除岩性、水性对电性的干扰,同时探索多信息融合技术,采用概率神经网络方法,增强测井识别能力,达到了解决电性与含油性矛盾的目的,形成以放大电性特征为核心的评价技术.研究成果对低对比度油气层测井识别具有指导意义.%Regarding the problems that a large number of low-contrast pay zones exist in Dongying formation of the Block Nanpu 2-1 in Jidong oilfield,Bohai Bay basin and conventional logging methods cannot be used to accurately evaluate oil-beating properties of reservoirs,the paper introduces the natural gamma relative value and apparent formation water resistivity as valid parameters,uses logging chart to eliminate influences of lithology and water on electrical properties,applies probabilistic neural network (PNN) method to enhance logging identification accuracy,which could solve the contradiction between electrical and oil-bearing properties,and finally develops an evaluation technology taking amplifying electrical characteristics as the core.The research results have guiding significance for low-contrast pay zone identification by well-logging analysis.
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