摘要
储层分类评价是油藏研究的重要内容,为了使储层分类更准确、合理,本文采用Q型聚类分析和贝叶斯判别算法相结合的方法,进行储层分类评价研究。综合优选砂岩厚度、孔隙度、渗透率、碳酸盐含量及泥质含量等各种储层参数,应用数理统计方法将这些参数集合起来,采用Q型聚类分析的算法对储层进行分类;在此基础上,采用贝叶斯判别算法,建立这些储层参数与储层分类评价的定量判别关系,即建立进行储层分类评价的判别函数,依据此判别函数对非取心井的目的层进行了定量分类评价。实例证明,应用Q型聚类分析和贝叶斯判别算法相结合进行储层分类评价是有效的,其应用效果良好。
The reservoir classification and evaluation is an important topic of study,and in order to make reservoir classification more accurate and reasonable,in this paper,the method of Q cluster analysis combined with Bayesian discrimination algorithm is adopted. First,various reservoir parameters are optimized globally,including sandstone thickness,porosity,permeability,carbonate content,shale content and others,with the mathematical statistics method to assemble the parameters,and the algorithm of Q cluster analysis to do the reservoir classification. On this basis,Bayesian discrimination algorithm is adopted to establish the discriminant relationship between reservoir parameters and reservoir classification and evaluation,together with the discriminant function of reservoir classification and evaluation,based on which,the target beds of non-coring wells are classified and evaluated. Examples show that the method of Q cluster analysis combined with Bayes discrimination algorithm is effective to achieve reservoir classification and evaluation.
出处
《科技导报》
CAS
CSCD
北大核心
2011年第3期29-33,共5页
Science & Technology Review
关键词
储层分类评价
储层参数
Q型聚类分析
贝叶斯判别
reservoir classification and evaluation
reservoir parameter
Q cluster analysis
Bayesian discrimination algorithm
