论文部分内容阅读
采用霍其士—莱赫曼法进行最优值选择，利用３７００测井资料，提取出地层胶结指数（ｍＦ），有效孔隙度与电阻率孔隙度比值（ＲＰＥＲ），视孔道弯曲度的对数值（ＴＡＡ），视地层水电阻率的ｍ次方值Ｐ１２，重构水线电阻率与实际电阻率比值（ＳＴＲＯ））等５组对判别稠油储层流体有利的聚类参数，对冷东地区稠油层标准样本进行均值模糊聚类并求取聚类中心，同时得到隶属于４种类别的隶属度。在计算过程中对测井曲线进行环境校正与畸变参数修复和重构工作。通过对冷东地区１８口井的流体识别，效果明显，具有较好的实用价值。
The optimal value was chosen by the method of Hohhot-Leichmann method. The 3700 well logging data were used to extract the mF, RPER and the logarithm of the tunnel curvature (TAA), the m-th power of the formation water resistivity P12, the ratio of the reconstructed water line resistivity to the actual resistivity (STRO) The regional heavy oil reservoir samples were averaged by fuzzy clustering and clustering centers were obtained, and at the same time, the membership degrees belonging to 4 categories were obtained. In the process of calculation, the logging curve is corrected and reconstructed by environmental correction and distortion parameters. Through the fluid identification of 18 wells in the cold East region, the effect is obvious and has good practical value.