摘要：Production management serves as a pivotal component in the operational activities of oilfield sites, with the effectiveness of management practices directly influencing the success of developmental outcomes. To enhance the maintenance-free operational period of oil production systems, elevate management standards, and reduce overall operational costs, advanced technologies such as artificial intelligence (AI) and big data analytics have been strategically integrated into oilfield operations. These technologies are able to incorporate data resources from all stages of oilfield production, thus providing a comprehensive view of oilfield production and guidance for production. This study uses a series of diagnostic and predictive methods to construct a management system that allows for the comprehensive monitoring and fault diagnosis of oil production systems, which can ensure the intelligent management of oil production systems at multiple levels throughout their life cycle. Automated monitoring workflows and proactive analytical processes are at the heart of the framework, enabling real-time monitoring and predictive decision-making. This not only minimizes the likelihood of system failure but also optimizes resource allocation and operational efficiency.

关键字：artificial intelligence; fault warning; comprehensive diagnosis; deep learning; production management

ISSN号：2227-9717

卷、期、页：卷: 13期: 1

发表日期：2025-01-01

影响因子：0.000000

期刊分区（SCI为中科院分区）：四区

收录情况：SCI（科学引文索引印刷版）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：PROCESSES

参与作者：隋先富,姬煜晨,杨阳,Peng, Jianlin,Li, Menglong

通讯作者：路鑫

第一作者：韩国庆

论文类型：期刊论文

论文概要：隋先富,路鑫,姬煜晨,杨阳,Peng, Jianlin,Li, Menglong,韩国庆，Intelligent Oil Production Management System Based on Artificial Intelligence Technology，PROCESSES，2025，卷: 13期: 1

论文题目：Intelligent Oil Production Management System Based on Artificial Intelligence Technology