松辽盆地火山岩岩性识别中测井数据的选择及判别方法

依照松辽盆地深层火山岩岩性分类方案中的二级分类类型，对32口有准确岩心薄片定名资料的火山岩井段测井响应特征进行了总结，根据各测井响应区间值建立一个假设随机样本，应用逐步判别分析方法，在多个测井参数中按其对岩性分类判别能力的大小进行筛选，最终选取钾、铀、光电吸收截面指数、中子及自然伽马5个具有显著判别能力的参数，并在Bayers准则下建立判别函数，选择分类效果明显的两个判别函数建立岩性识别图版，克服了测井参数引入过多对岩性识别模型的不利影响。利用上述方法对松辽盆地徐家围子断陷火山岩井段的50个资料点的实测数据进行了处理，其回判数点正确率为88%。

Selection and identification of logging data for lithology recognition of volcanic rocks in Songliao Basin

According to the secondary taxonomic type in the lithology classification scheme for deep volcanic rocks in Songliao Basin,we summarized logging response characteristics of volcanic intervals in 32 wells that have exact nomination materials of core thin sections.A hypothetical random sample based on the interval value of logging response of each well was determined,and various logging parameters were screened according to their distinguishability in lithologic classification by using the stepwise discriminant analysis method.Five parameters with significant distinguishability,including potassium,uranium,photoelectric absorption coefficient,neutron and natural gamma ray,were finally chosen and discriminant functions were established with the Bayers criterion.In addition,two discriminant functions with obvious classification effect were adopted to establish a plate for lithology identification in order to diminish the negative impact of employing overmany logging parameters on lithology identification models.Moreover,the above-mentioned approach was applied to process measured data from 50 material points of faulted volcanic intervals in Xujiaweizi of Songliao Basin,and the rate to verify the correctness in counting the number of points had reached to 88%.