Current status and prospect for the research and application of big data and intelligent optimization methods in oilfield development

被引：0
|
作者：
Zhang K. [1 ]
Zhao X. [1 ]
Zhang L. [1 ]
Zhang H. [2 ]
Wang H. [1 ]
Chen G. [1 ]
Zhao M. [1 ]
Jiang Y. [1 ]
Yao J. [1 ]
机构：
[1] School of Petroleum Engineering in China University of Petroleum(East China), Qingdao
[2] College of Science in China University of Petroleum(East China), Qingdao
来源：
Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science) | 2020年 / 44卷 / 04期
关键词：
Big data; Intelligent oilfield; Intelligent optimization; Machine learning; Production optimization;
D O I：
10.3969/j.issn.1673-5005.2020.04.004
中图分类号：
学科分类号：
摘要：
In this paper, the current status and research prospect of big data and intelligent optimization methods in oilfield development were reviewed and discussed, including the basic concepts and characteristics of the techniques, the production problems in intelligent oilfields, the application of big data analysis, machine learning methods as well as intelligent optimization. Two major research areas were summarized: forming oilfield big data analysis theories by integrating the data with reservoir engineering methods and constructing intelligent optimization theories collaboratively driven by data and intelligent modeling. Combined with these two research areas, the current research progress and their future development perspectives were discussed. It is concluded that accurately constructing the models and rapid optimization of complex reservoir systems based on big data and physics law is the core of the intelligent oilfield production and development, which is of great significance to promote an intelligent transformation and upgrading of China's petroleum industry. © 2020, Editorial Office of Journal of China University of Petroleum(Edition of Natural Science). All right reserved.
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页码：28 / 38
页数：10
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