摘要
研究了 3种利用测井资料确定剩余油饱和度的方法 ,一是通过自然电位曲线的综合校正求取混合液电阻率 ,进而求得剩余油饱和度的常规测井解释方法 ;二是利用深度延迟技术通过网络的训练与学习来确定剩余油饱和度的深度延迟人工神经网络法 ;三是研究碳氧比资料在消除高矿化度地层水的影响后确定剩余油饱和度的方法。将 3种方法有效结合起来 ,综合分析评价中原油田层间剩余油饱和度的分布 。
Three methods to give the remaining oil saturation by using logging data are proposed. One, a conventional method,is to establish a mixed fluid resistivity by conducting a composite calibration of spontaneous potential(SP) curves and then derive the remaining oil saturation; the second, called a depth delay artificial neural network (DDNN) model, is to use the depth delay technique to determine the remaining oil saturation through training and learning of the neural network; the third is to calculate the remaining oil saturation from carbon/oxygen logging data, after dispelling the effect of high salinity of formation water The distribution of interbed remaining oil saturation is evaluated by intergrating the 3 methods mentioned in Zhongyuan oilfield and better results are obtained in application
出处
《江汉石油学院学报》
CSCD
北大核心
2000年第4期88-91,共4页
Journal of Jianghan Petroleum Institute
关键词
测井解释
自然电位测井
剩余油饱和度
中原油田
log interpretation
spontaneous potential curve
neural network
carbon oxygen logging
remaining oil saturation
Zhongyuan oilfiled
