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机构地区:[1]成都理工大学管理科学学院,四川成都610059 [2]数学地质四川省重点实验室,四川成都610059
出 处:《山西大同大学学报(自然科学版)》2014年第6期63-66,共4页Journal of Shanxi Datong University(Natural Science Edition)
基 金:数学地质四川省重点实验室开放基金项目[SCSXDZ2009012]
摘 要:致密碎屑岩储层具有致密、低孔隙和非均质性强等特点,岩性识别是储层预测中的难点之一。文章针对这一问题,提出将核Fisher判别方法用于致密碎屑岩储层的岩性识别,结果表明核Fisher判别方法能有效的识别川西XC地区致密碎屑岩中的砂岩和粉砂岩。Tight clastic reservoir with low porosity, because of its dense, multi-layered stacked and strong heterogeneity characteristics caused by the complexity and particularity, lithology recognition is one of difficulties in reservoir prediction. Aiming at this problem, the kernel Fisher discriminant with strong nonlinear extraction ability was used for tight clastic lithology identification. The first task is the extraction of characteristic parameters as variables, then the kernel Fisher discriminant was introduced to apply to the lithology identification. And taking the Xujiahe formation of western Sichuan as an example, the experimental results show that the method of tight clastic rock lithology identification is effective.
分 类 号:TU528[建筑科学—建筑技术科学]
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