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鄂尔多斯盆地姬塬地区长6储层矿物含量与孔隙度的线性关系
引用本文:李小燕,乔华伟,张建魁,马俊杰,闫江涛,李树同. 鄂尔多斯盆地姬塬地区长6储层矿物含量与孔隙度的线性关系[J]. 岩性油气藏, 2019, 31(2): 66-74. DOI: 10.12108/yxyqc.20190208
作者姓名:李小燕  乔华伟  张建魁  马俊杰  闫江涛  李树同
作者单位:1. 中国科学院 兰州文献情报中心/中国科学院 西北生态环境资源研究院, 兰州 730000;2. 甘肃省油气资源研究重点实验室/中国科学院 油气资源研究重点实验室, 兰州 730000;3. 中国科学院大学, 北京 100049;4. 中国石油长庆油田分公司 第三采油厂, 银川 710065;5. 中国石油长庆油田分公司 第五采油厂, 西安 710020
基金项目:国家自然科学基金面上项目“青海湖细粒沉积纹层特征与其沉积环境要素耦合关系研究”(编号:41772142)资助
摘    要:矿物含量是影响储层物性的重要因素之一。为了较全面地分析不同类型矿物含量对储层孔隙度的影响,以鄂尔多斯盆地姬塬地区长6砂岩储层为例,探索性地运用多元逐步线性回归法分析了石英含量(x1)、长石含量(x2)、岩屑含量(x3)、绿泥石含量(x4)、伊利石含量(x5)、高岭石含量(x6)、硅质含量(x7)以及铁方解石含量(x8)与孔隙度(y)的关系,建立了矿物含量(xi)与孔隙度(y)之间的回归模型:y=21.131-0.086 x2-0.113 x3-0.554 x4-0.370 x5-0.199 x6-0.659 x7-0.465 x8。结果表明:绿泥石、伊利石、硅质含量及铁方解石含量对长6储层孔隙度的影响较大,而长石、岩屑、高岭石含量对孔隙度影响较小,石英含量对孔隙度几乎没有影响。对多元回归模型的检验发现,实测孔隙度与模型孔隙度之间具有较好的拟合度,多元逐步回归分析法在多因素影响储层物性问题研究中具有一定的优越性,相比单因素分析法更能揭示出影响储层物性的本质。

关 键 词:多元线性回归  矿物含量  孔隙度预测  回归模型  鄂尔多斯盆地  
收稿时间:2018-10-11

Linear relationship between mineral content and porosity of Chang 6 reservoir in Jiyuan area,Ordos Basin
LI Xiaoyan,QIAO Huawei,ZHANG Jiankui,MA Junjie,YAN Jiangtao,LI Shutong. Linear relationship between mineral content and porosity of Chang 6 reservoir in Jiyuan area,Ordos Basin[J]. Northwest Oil & Gas Exploration, 2019, 31(2): 66-74. DOI: 10.12108/yxyqc.20190208
Authors:LI Xiaoyan  QIAO Huawei  ZHANG Jiankui  MA Junjie  YAN Jiangtao  LI Shutong
Abstract:Mineral content is one of the important factors affecting the physical properties of reservoir. In order to comprehensively analyze the influences of contents of different types of minerals on reservoir porosity,taking Chang 6 sandstone reservoir in Jiyuan area of Ordos Basin as an example,the regression model between mineral content (xi) and porosity (y) was established by multiple stepwise linear regression method:y=21.131-0.086 x2-0.113 x3-0.554 x4-0.370 x5-0.199 x6-0.659 x7-0.465 x8, with the quartz content (x1), feldspar content (x2),lithic content (x3),chlorite content (x4),illite content (x5),kaolinite content (x6),siliceous content (x7) and ferrocalcite content (x8) and porosity (y). The results show that the contents of chlorite,illite,siliceous and ferrocalcite have great effects on the porosity of Chang 6 reservoir, the contents of feldspar, lithic and kaolinite have little effect on the porosity,while the quartz content has almost no effect on porosity. The test of multiple regression model shows that there is a good fit between measured porosity and model porosity,and multiple stepwise regression analysis has some advantages in the study of multifactor affecting reservoir physical properties,and it can reveal the essence of influencing reservoir physical properties better than single factor analysis.
Keywords:multiple linear regression  mineral content  porosity prediction  regression model  Ordos Basin  
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