基于老井资料的碳酸盐岩储层测井解释研究

碳酸盐岩储层岩性复杂，老油气区测井系列不全，测井定量解释的难度很大。文章选取研究区有利构造部位测井项目齐全的井，以取心和测试层段为研究基础，通过深入分析典型储层岩性、物性及含油气性在电性上的响应特征，分类建立了中子、密度与其它测井曲线的关系数据样本，用BP神经网络方法建立中子和密度曲线的构建模型并预测其它老井的中子和密度曲线；用最优化测井解释方法，在准确识别岩性的基础上完成较高精度的测井资料数字处理；结合试气和投产资料，建立储层及有效厚度评价标准，进行储层测井综合解释。用该方法对老气田12口井三叠系嘉二段储层进行了精细测井处理和解释，取得了比较满意的效果。分析认为：在碳酸盐岩储层测井解释中，岩性识别是关键；BP神经网络在构建测井曲线中有其独到之处，该研究思路和方法对老井复查工作有一定的参考使用价值。

LOG INTERPRETATION OF CARBONATE RESERVOIR BY THE DATA COLLECTED FROM OLD WELLS

The quantitative log interpretation is very difficult because of the complex lithology of carbonate reservoir and the incomplete logging suite in old oil and gas region. Through selecting the wells at beneficial structural locations with complete logging suite, by taking the coring and testing intervals as the research targets and by means of analyzing thoroughly the log responses of the lithology, petrophysical property and hydrocarbon potential of typical reservoir, the data representative species of the relation between the neutron log and density log and the other logs were set up respectively; the construction models of the neutron log and density log were established by use of BP neural network method; and the two logs were predicted for the other old wells. On the basis of identifying accurately lithology, the log data numerical processing with high precision was finished by applying optimal log interpretation method. The reservoir log comprehensive interpretation was carried out through setting up the evaluation standards of reservoir and net pay thickness in combination with the testing and producing data, and a good result was obtained for the fine log processing and interpretation of T1j2 (second member of Jialingjiang Formation, Lower Triassic) reservoir of 12 wells in one old gas field in Sichuan by use of such a method. It is pointed out in the paper that the lithologic identification is crucial in the log interpretation of carbonate reservoir; the BP neural network method is of distinctive qualities in constructing logs; and this research has a certain application value in data reexamination of old wells.