鄂尔多斯盆地西部页岩油储层成岩相测井识别与预测
Logging-based identification and prediction of diagenetic facies in shale oil reservoirs in the Western Ordos Basin
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- 引用格式:
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董越,路巍,陈华,王振宇,姬程伟,李妍蓉,朱玉双.鄂尔多斯盆地西部页岩油储层成岩相测井识别与预测[J].天然气与石油,2025,43(1):93-102.doi:10.3969/j.issn.1006-5539.2025.01.013
DONG Yue, LU Wei, CHEN Hua, WANG Zhenyu, JI Chengwei, LI Yanrong, ZHU Yushuang.Logging-based identification and prediction of diagenetic facies in shale oil reservoirs in the Western Ordos Basin[J].Natural Gas and Oil,2025,43(1):93-102.doi:10.3969/j.issn.1006-5539.2025.01.013
- DOI:
- 10.3969/j.issn.1006-5539.2025.01.013
- 作者:
- 董越1 路巍2 陈华2 王振宇1 姬程伟3 李妍蓉4 朱玉双4
DONG Yue1, LU Wei2, CHEN Hua2, WANG Zhenyu1, JI Chengwei3, LI Yanrong4, ZHU Yushuang4
- 作者单位:
- 1. 延长油田股份有限公司, 陕西 延安 716099; 2. 中国石油长庆油田分公司第五采油厂, 陕西 西安 710200; 3. 中国石油长庆油田分公司第九采油厂, 陕西 西安 717600; 4. 西北大学地质学系, 陕西 西安 710069
1. Yanchang Oilfield Co., Yan'an, Shaanxi, 716099, China; 2. No.5 Oil Production Plant, Changqing Oilfield Company, CNPC, Xi'an, Shaanxi, 710200, China; 3. No.9 Oil Production Plant, Changqing Oilfield Company, CNPC, Xi'an, Shaanxi, 717600, China; 4. Department of Geology, Northwest University, Xi'an, Shaanxi, 710069, China
- 关键词:
- 鄂尔多斯盆地西部;姬塬地区;长7页岩油;成岩相测井识别
Western Ordos Basin; Jiyuan area; Chang 7 shale oil; Diagenetic facies identification through well logging
- 摘要:
不同的成岩组合决定着储层孔隙发育和储层的不同特征,为了对姬塬地区未知成岩相井段的成岩相进行预测,应用岩心、铸体薄片、阴极发光及扫描电镜等实验,依据成岩作用类型、成岩矿物组合将鄂尔多斯盆地姬塬地区长7页岩油储层划分出6种成岩相类型;并利用SPSS软件在Fisher判别法的基础上构建出成岩相识别的主因子与次因子,建立二者图版；同时建立不同成岩相的判别函数,进而对未知成岩相井段的成岩相进行预测。与常规交会图法相比,Fisher判别法对成岩相的正确识别率达到了91.4%，大大提高了识别精度;为研究区长7页岩油储层下一步油气勘探开发提供依据。
Different diagenetic combinations control the development of reservoir pores and the different characteristics of reservoirs. In order to predict the diagenetic facies of unknown diagenetic facies well sections in the Jiyuan area, this paper applies experimental techniques such as core analysis, casting thin sections, cathodoluminescence, and scanning electron microscopy to classify the Chang 7 shale oil reservoir in the Jiyuan area of the Ordos Basin into six types of diagenetic facies based on the types of diagenesis and mineral assemblages. Using SPSS software and Fisher's dimensionality reduction approach, the main and secondary factors for identifying diagenetic facies were established, and corresponding graphs were created. At the same time, discriminant functions for different diagenetic facies were developed to predict the diagenetic facies of unknown well sections. Compared with the conventional intersection plot method, the Fisher discriminant method improves the accuracy of diagenetic facies identification through well logging, achieving a correct identification rate of 91.4%, which improves the identification accuracy considerably and provides a foundation for further oil and gas exploration and development in the Chang 7 shale oil reservoir of the study area.
