西南石油大学学报（自然科学版）Issue(2)：71-78,8.DOI:10.11885/j.issn.1674-5086.2013.08.30.01
新场气田须二气藏单井气水层识别模型研究
Study on Gas-water Layer Identification Model in the Single Well of Xu 2 Gas Reservoir of Xinchang Gas Field
摘要
Abstract
Xu 2 Gas Reservoir,which is in Xinchang Gas Field in western Sichuan Basin,is a typical low-permeability and tight clastic gas reservoir. Due to the complicated geological conditions and serious heterogeneity in this area,the gas-water layer distribution is very complicated,and the bound water’s content is high. The boundaries of resistivity between gas reservoir and gas-water layer are blurred,so that some mistakes arise in log interpretation. We use kernel principal component analysis and support vector machine,also known as KPCA-SVM model,which is based on particle swarm optimization(PSO),to solve the problem. Firstly,the model extracts non-linear properties of variables by kernel principal component analysis(KPCA), and then inputs the properties of a variable into the support vector machine(SVM). And in the identification process,we use the particle swarm optimization(PSO)to seek the optimization algorithm. Finally,the gas-water layer identification is implemented in the SVM. We applied this model to gas&water layer prediction of Xu 2 Member gas reservoir of Xinchang Gas Field,and the recognition result is in line with the actual situation of the study area.关键词
粒子群算法/核主成分分析/支持向量机/气水层识别/新场须二气藏Key words
particle swarm optimization/kernel principal component analysis/support vector machine/gas-water layer iden-tification/Xu 2 Member gas reservoir of Xinchang Gas Field分类
能源科技引用本文复制引用
庞河清,匡建超,蔡左花,廖开贵,王众..新场气田须二气藏单井气水层识别模型研究[J].西南石油大学学报（自然科学版）,2014,(2):71-78,8.基金项目
教育部规划基金项目（11YJAZH043）；四川石油天然气研究中心项目（川油气科SKA09-01）。 （）
