A Study on Innovation in QHSE Regulatory Models for Petroleum Engineering Service Companies Empowered by Digital and Intelligent Technologies
DOI:
https://doi.org/10.54691/7yps8h90Keywords:
Petroleum Engineering Technical Services; QHSE Regulation; Digital and Intelligent Transformation; Data-driven; Intelligent Closed-loop Management.Abstract
Through a comparative analysis of domestic and international QHSE regulatory practices, considering the realities of the technical services industry in petroleum engineering, this paper proposes a path for establishing a new QHSE regulatory mechanism in the context of digital and intelligent technologies. The study confirms that digital and intelligent technologies serve as the core engine driving the paradigm shift in QHSE regulation from a “system-constrained” model to a “data-driven” one. By establishing an intelligent closed-loop system of “perception-early warning-collaboration-optimization,” it is possible to effectively resolve the structural challenges of traditional regulation, namely “incomplete oversight, inaccurate judgment, ineffective control, lack of connectivity, and difficulty in achieving a closed-loop.” This study aims to establish a new digital and intelligent QHSE regulatory ecosystem that is comprehensive in coverage, agile in response, and efficient in operation. Through an implementation strategy involving platform integration, overseas expansion, standardized training, and grassroots demonstrations, it seeks to provide QHSE management safeguards for the high-quality development of petroleum enterprises and the expansion of their overseas operations.
Downloads
References
[1] Xie, X. (2022). Analysis of the safety management situation and improvement strategies for state-owned petroleum engineering technology enterprises. Modern Occupational Safety, (07), 67–69.
[2] Yang, L. (2019). Intelligent management measures in digital oilfield production. Chemical Engineering and Equipment, (05), 301–302.
[3] Li, D. Z. (2026). Practice and efficiency improvement of digital technology in oilfield production operation scheduling. In Forum on New Quality Productivity Driving the Development of the Secondary Industry and Innovation in Tendering and Procurement—Proceedings on Exploring Practical Pathways and Case Sharing (Volume 1) (pp. 405–407). China Tendering Journal Co., Ltd.; Production Operations Department, China National Petroleum Corporation Jilin Oilfield Company.
[4] Hu, S. J., & Li, B. H. (2024). Application of big data technology in oilfield digital information systems. Electronic Technology, 53(08), 232–233.
[5] Xu, S. N. (2025). Intelligent management measures in digital oilfield production. China Petroleum and Chemical Standards and Quality, 45(17), 70–72.
[6] Zhao, B., Cai, Z. Q., & Huang, Y. L. (2024). Upgrading and implementation of a comprehensive production information management platform for the Luliang Oilfield based on multidimensional data fusion. Information Systems Engineering, (09), 16–19.
[7] Jiang, X. L. (2026). Research on smart grid fault diagnosis and rapid recovery strategies based on digital twin technology. In Proceedings of the Forum on New Quality Productivity Driving the Development of the Secondary Industry and Innovation in Tendering and Procurement—Exploration of Practical Pathways and Case Sharing (Volume 1) (pp. 50–52). China Tendering Journal Co., Ltd.; Wuhan Jiechuang Bota Automation Technology Co., Ltd.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Scientific Journal of Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.






