统计分析方法在长庆油田超低渗透油藏分类中的应用

doi:10.3969/j.issn.1006-6535.2020.04.015

特种油气藏 ›› 2020, Vol. 27 ›› Issue (4): 98-104.DOI: 10.3969/j.issn.1006-6535.2020.04.015

统计分析方法在长庆油田超低渗透油藏分类中的应用

刘亚茹¹, 刘保磊^1,2,3, 雷征东⁴, 陈新彬⁴, 余勤⁵, 钟鸣¹

1.长江大学,湖北武汉 430100;
2.油气钻采工程湖北省重点实验室,湖北武汉 430100;
3.油气资源与勘探技术教育部重点实验室,湖北武汉 430100;
4.中国石油勘探开发研究院,北京 100083;
5.中国石油长城钻探工程有限公司,辽宁盘锦 124000

收稿日期:2019-11-10 修回日期:2020-05-11 出版日期:2020-08-25 发布日期:2022-02-18
通讯作者: 刘保磊(1982—),男,讲师, 2006年毕业于长江大学石油工程专业,2014年毕业于中国石油勘探开发研究院油气田开发工程专业,获博士学位,现主要从事油气田开发规划战略研究工作。
作者简介:刘亚茹(1995—),女,2014年毕业于太原科技大学油气储运工程专业,现为长江大学石油与天然气专业在读硕士研究生,主要从事油气田开发规划战略方向研究。
基金资助:
国家科技重大专项“大型油气田及煤层气开发”(2016ZX05031);国家自然基金“低渗透油藏提高原油采收率的生物化学基础研究”(51634008)、"油-水-岩体系中酚类化合物分配规律及其应用研究"(4187020482)

Application of Statistical Analysis in the Ultra-Low Permeability Reservoir Classification of Changqing Oilfield

Liu Yaru¹, Liu Baolei^1,2,3, Lei Zhengdong⁴, Chen Xinbin⁴, Yu Qin⁵, Zhong Ming¹

1. Yangtze University, Wuhan,Hubei 430100,China;
2. Hubei Province Key Laboratory of Drilling & Oil Production Engineering, Wuhan, Hubei 430100, China;
3. MOE Key Laboratory of Oil & Gas Resources and Exploration Technology, Wuhan, Hubei 430100, China;
4. PetroChinaResearch Institute of Petroleum Exploration and Development, Beijing 100083, China;
5. CNPC Greatwall Drilling Company,Panjin, Liaoning 124000, China

Received:2019-11-10 Revised:2020-05-11 Online:2020-08-25 Published:2022-02-18

摘要/Abstract

摘要： 为了分类指导超低渗透油藏的生产开发,提高超低渗透油藏采收率,综合考虑超低渗透油藏的地质与开发特点,对油藏参数开展相关性分析,优选出7项参数作为油藏分类指标,利用因子分析法对长庆油田90个超低渗透区块进行分析,提取出4个主因子,进而利用K-均值聚类分析法进行分类,并根据判别分析法获得各类油藏的判别公式,最终将90个油藏区块划分为3类,对其进行评价。实例应用表明,该分类方法能有效区分各类超低渗透油藏区块的开发特征,分类结果与实际开发特征相吻合。该研究能够为超低渗透油藏的合理开发提供分类依据,正确指导超低渗透油藏的生产开发。

关键词: 超低渗透油藏, 因子分析, 动态分析, 开发效果, 长庆油田

Abstract: In order to specifically improve the production and development performances of ultra-low permeability reservoirs by classification and enhance their oil recovery, a correlation analysis on reservoir parameters was conducted by comprehensively considering the geology properties and development performances. A total of 7 parameters was taken as the indicators for reservoir classification and factor analysis was used to analyze 90 ultra-low permeability blocks in Changqing Oilfield. 4 major indicators were further taken to classify these reservoirs by K-means clustering analysis method. The discriminant formulas for various reservoir categories were obtained according to discriminant analysis, which finally classified the 90 reservoir blocks into three categories and provided a comprehensive evaluation. This classification can effectively characterize the development performances of various ultra-low permeability reservoir blocks and the corresponding classification is consistent with that of actual development performance. This research could provide certain reservoir classification reference for the reasonable development of ultra-low permeability reservoirs and favorably guide the production and development of ultra-low permeability reservoir.

Key words: ultra-low permeability reservoir, factor analysis, production performance analysis, development performance, Changqing Oilfield

中图分类号:

TE348

刘亚茹, 刘保磊, 雷征东, 陈新彬, 余勤, 钟鸣. 统计分析方法在长庆油田超低渗透油藏分类中的应用[J]. 特种油气藏, 2020, 27(4): 98-104.

Liu Yaru, Liu Baolei, Lei Zhengdong, Chen Xinbin, Yu Qin, Zhong Ming. Application of Statistical Analysis in the Ultra-Low Permeability Reservoir Classification of Changqing Oilfield[J]. Special Oil & Gas Reservoirs, 2020, 27(4): 98-104.

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统计分析方法在长庆油田超低渗透油藏分类中的应用

Application of Statistical Analysis in the Ultra-Low Permeability Reservoir Classification of Changqing Oilfield

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