Abstract: In order to recognize sedimentary microfacies automatically by well-logging curves，by means of coding the tendency of well-logging curves and implementing the operators such as clone immunity and aberrance，the clustering well-logging curves is presented by variant feature vectors，and then recognition model of sedimentary macrofacies with the well-logging curves is constructed by the basis on Artificial Immune System（AIS）.The recognition model is applied to recognizing 150 sedimentary microfacies of ShengLi oil field，and the accuracy of recognition is up to 95%，which proves the recognition model based on AIS is very efficient in recognition of sedimentary microfacies.

Key words: artificial immune algorithm, pattern recognition, time-series data, well-logging curve, sedimentary microfacies

摘要： 为了采用测井曲线实现沉积微相的自动识别，通过测井曲线变化趋势的编码和人工免疫系统的克隆免疫、变异等算子，建立基于人工免疫系统的测井曲线识别模型，实现了不等长特征曲线匹配过程的快速收敛。对胜利油田150个沉积微相进行识别，正确率达到95%，证实了该模型应用的有效性。

关键词: 人工免疫算法, 模式识别, 时序数据, 测井曲线, 沉积微相