摘要
通过提取反映稠油油藏储层动态的特征参数，应用模糊模式识别方式对稠油储层类型进行划分，在比较原钻井及其侧钻井的水淹状况与测井响应关系的基础上，提出用电阻率减小率作为划分稠油储层水淹级别的标准，并应用人工神经网络技术实现了稠油储层水淹程度的动态测井解释。
By drawing the characteristic parameters of the heavy oil reservoir, the types of reservoir are divided by fuzzy pattern recognition method. Based on comparing flooding situation and log responses of the orginal holes and side holes ,Rr(resitivity reducing rate)is proposed as the criterion for divided flooding level of the heavy oil reservoir and the dynamic logging interpretation for the flooding degree of the heavy oil reservoir is achiveed by ANN (artificial neural network).
出处
《中国海上油气（地质）》
1998年第3期213-216,共4页
China Offshore Oil and Gas(Geology)
关键词
稠油油藏
储层动态
测井
评价方法
模糊模式识别
人工神经网络
heavy oil reservior
reservior performance
fuzzy pattern recognition
artificial neural network
logging interpretation
