通过对松辽盆地南部长岭地区测井响应特征的研究,采用多种方法对营城组火山岩岩性进行判别分析。通过交会图法、自组织神经网络法、主成分分析法及模糊聚类法4种方法对样本进行了处理,最终优选了自组织神经网络方法作为研究区岩性识别的方法。 Based on the study of logging response characteristics in Changling area of ​​southern Songliao Basin, a variety of methods are used to discriminate the volcanic lithology of Yingcheng Formation. The samples were processed by four methods: intersection graph, self-organizing neural network, principal component analysis and fuzzy clustering. Finally, the self-organizing neural network method was selected as the method of lithology identification in the study area.