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新场气田须二气藏单井气水层识别模型研究

Journal of Southwest Petroleum University (Science & Technology Edition)(2014)

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Abstract
川西新场气田须二气藏为典型的低渗致密碎屑岩气藏,由于地质条件复杂,储层非均质性严重,气水分布十分复杂,束缚水含量较高,气层、气水同层电阻率界限模糊不清,测井解释往往造成很大误判。针对这一难点,应用基于粒子群算法(PSO)的核主成分分析与支持向量机(KPCA-SVM)模型进行气水层识别。模型先通过核主成分分析(KPCA)进行非线性属性变量提取,再将提取的属性变量作为支持向量机(SVM)的输入变量,在识别过程中利用粒子群算法(PSO)寻优,最终实现气水层识别。将模型应用于新场气田须二气藏气水层识别,识别结果符合研究区的实际情况。
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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
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