Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review

Yufei Wang

doi:10.47297/taposatWSP2633-456924.20250606

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Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review

Volume 6, Issue 6

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Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review
Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review
Changchun University of Technology, Changchun, Jilin, 130012, China
Vol. 6, Issue 6, Pages: 121-124(2025)
Published：30 June 2025
DOI：10.47297/taposatWSP2633-456924.20250606
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Wang Yufei.Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review[J].Theory and Practice of Science and Technology,2025,06(06):121-124.
DOI：

Wang Yufei.Research Status of Oil and Gas Pipeline Operation and Management: A Literature Review[J].Theory and Practice of Science and Technology,2025,06(06):121-124. DOI： 10.47297/taposatWSP2633-456924.20250606.

摘要

Abstract

As China's energy needs keep climbing

the oil and gas pipeline transport industry has been booming. The efficient and safe operation and management of these pipelines is vital for energy security. This paper reviews domestic and international research on oil and gas pipeline operation and management. It focuses on key technologies like sensor technology

data analysis

machine learning

and corrosion assessment and life prediction. It also discusses existing challenges and forecasts optimization strategies and development trends based on predictive maintenance and intelligent digitalization. The aim is to provide a reference for enhancing the operational efficiency and safety of pipeline management.

关键词

Keywords

references

Li R, Feng Q S, Cai M L, et al. Measurement of long-distance buried pipeline centerline based on multi-sensor data fusion [J]. *Acta Petrolei Sinica*, 2014, 35(5): 987-992.

Zhou J, Meng L X, Zhang J R, et al. A fully intelligent inspection system for oil and gas pipelines based on UAV remote sensing and deep learning [P]. Chengdu: University of Electronic Science and Technology of China, 2019.

Guo Y, Yang L J, Zhao B S, et al. Research status of leakage detection technology for long-distance oil pipelines [J]. *Journal of Liaoning Petrochemical University*, 2022, 42(4): 25-31.

Tu B J. Optimization of oil and gas pipeline operation efficiency based on big data analysis [J]. *Oil & Gas Storage and Transportation*, 2025, 44(1): 1-7.

Zhou D J, Xing T S, Zhang L, et al. Data mining and application of natural gas pipeline networks in the context of big data [J]. *Oil & Gas Storage and Transportation*, 2021, 40(3): 271-276.

Zhang W, Wang X K, Shi Y J, et al. Construction technology of intelligent manufacturing service system driven by industrial big data [J]. *Scientia Sinica (Technologica)*, 2023, 53(7): 1084-1096.

Tang S H, Yang J H, Xu C Y, et al. Application of industrial data-driven technology in the operation of large-scale complex natural gas pipeline networks [J]. *Natural Gas Industry*, 2021, 41(9): 135-141.

Gao P, Gao Z Y, Zhao S X, et al. New progress in China's oil and gas pipeline construction in 2020 [J]. *International Petroleum Economics*, 2021, 29(3): 48-56.

Qiu C W. Suggestions on improving the legal system for pipeline protection [EB/OL]. [2025-05-10]. http://mp.weixin.qq.com/s?__biz=MzAxODEzOTQ1OA==&mid=2651027516&idx=1&sn=520f6e1d92f38df8a250252d7497cd43.

Dai L S, Tang C J, Feng Z Z, et al. Risk assessment method and application for terrorist attacks on oil and gas pipelines [J]. *Oil & Gas Storage and Transportation*, 2011, 30(5): 337.

Fang X P, Li G X. Operation management of long-distance oil and gas pipelines under the new system [J]. *Oil & Gas Storage and Transportation*, 2011, 30(3): 238.

Liu Z Q. Guarding the "Giant Dragon" deep in the Arakan Mountains [EB/OL]. [2023-03-08]. http://mp.weixin.qq.com/s?__biz=MjM5MTQyNDczMA==&mid=2650908748&idx=7&sn=1d32fe35630cf9b555dec53bdcfba389.

CNPC establishes pipeline integrity management technology system [EB/OL]. [2025-04-21]. http://www.sasac.gov.cn/n2588025/n2588124/c3962983/content.html.

Practice and exploration of long-distance natural gas pipeline maintenance management in corporate cost reduction and efficiency enhancement [EB/OL]. [2024-05-09]. https://www.hanspub.org/journal/paperdownload?paperID=86818.

Current status of domestic and international oil and gas pipeline operation management and intelligentization trends [EB/OL]. [2019-02-28]. https://yqcy.paperonce.org/oa/darticle.aspx?type=view&id=201903001.

In-depth analysis and investment prospect research report on China's oil and gas pipeline industry (2022-2029) [EB/OL]. [2022]. https://m.chinabaogao.com/detail/608715.html.

Li Q Y, Zhao M H, Zhang B, Wen W, Wang L L, Zhang X Q, et al. Global oil and gas pipeline construction status and development trends in 2020 [J]. *Oil & Gas Storage and Transportation*, 2021, 40(12): 1330-1337, 1348.

Dong S H, Yuan S Y, Zhang L B, et al. Research on development strategy of safety and integrity management technology for long-distance oil and gas pipelines [J]. *Petroleum Science Bulletin*, 2022, 7(3): 386-402.

Gong J, Shi B H, Chen Y C, et al. Subsea multiphase transportation containing natural gas hydrates and its blockage risk management [J]. *Natural Gas Industry*, 2020, 40(12): 1-10.

Li Q P, Chu J W, Yao H Y, et al. Research on blockage detection in natural gas pipelines using pressure pulse wave method [J]. *Journal of Safety Science and Technology*, 2021, 17(7): 1-8.

Zhang D H. Research progress in pipeline crack arrest control based on crack tip opening angle [J]. *Oil & Gas Storage and Transportation*, 2021, 40(8): 1-7.

Li G Y, Cao Y P, Ma W, et al. Permafrost disaster problems and prevention countermeasures for the China-Russia crude oil pipeline [J]. *Bulletin of Chinese Academy of Sciences*, 2021, 36(2): 1-8.

Huang W Q, Xu X, Lou J J, et al. Research progress on oil evaporation and vapor diffusion for tracing carbon emissions from storage tanks [J]. *Oil & Gas Storage and Transportation*, 2022, 41(2): 1-7.

Shi X L, Wei X X, Yang C H, et al. Problems and countermeasures in the construction of China's strategic salt-cavern petroleum reserve storage [J]. *Bulletin of Chinese Academy of Sciences*, 2023, 38(1): 1-8.

Cheng Q L, Chang T, Wang Y X, et al. Establishment and analysis method of energy efficiency indicator system for oilfield surface gathering systems [J]. *Journal of Petrochemical Universities*, 2020, 33(5): 1-7.

Yao H Y, Chen H H, Wu Z, et al. Research progress on flow assurance technology for deepwater oil and gas fields [J]. *Ocean Engineering Equipment and Technology*, 2022, 9(3): 1-8.

Li Y, Xue Z J, Cheng Z, Jiang H J, Wang R Y. Progress and development direction of deep oil and gas exploration and development in China [J]. *China Petroleum Exploration*, 2020, 25(1): 45-57.

Duan T Y, Xu B, Zhang Y. Analysis of China's natural gas pipeline network development trends during the "14th Five-Year Plan" period [J]. *World Petroleum Industry*, 2020, 27(3): 5-12.

Zhang W. Leveraging the role of oil and gas pipeline networks to safeguard national energy security [J]. *Qiushi*, 2022(20): 58-62.

Yang H W, Liu F, Han Y S. Simulation analysis of supply-demand balance on the user side for interconnected natural gas pipeline networks [J]. *Oil & Gas Storage and Transportation*, 2023, 42(4): 473-480.

Guo Z W, Fan R X, Shen X D, Lin H, Yang J C, Yu H L. Design and development of a non-contact ultrasonic pig passage indicator for subsea pipelines [J]. *Chemical Equipment Technology*, 2024, 45(5): 65-70.

Guo Z W, Yang Y, Chai Y Y. Internal corrosion assessment and remaining life prediction of a platform natural gas pipeline [J]. *Product Reliability Report*, 2024(5): 110-112.

Guo Z W, Lian B, Qin L G, Yang Y, Chai Y Y. Failure analysis of corrosion perforation in the center pipe of an oilfield production well [J]. *Modern Manufacturing Technology and Equipment*, 2024, 60(3): 50-52+56.

Guo Z W, Fan R X, Yang J C, Yu H L, Shen X D, Lin H. Research on non-contact pig passage indicators for subsea pipelines [J]. *Petroleum Engineering Construction*, 2024, 50(5): 71-75.

Liu W Y, Liu Y, Zhang H, et al. A review of machine learning applications in oil and gas pipeline operations [J]. *Journal of Petroleum Science and Engineering*, 2021, 203: 108483.

Wang X, Liu Y, Zhang H, et al. Smart pipeline systems: A review of technologies and applications [J]. *Journal of Natural Gas Science and Engineering*, 2020, 80: 103486.

Zhang H, Liu Y, Liu Y, et al. A data-driven approach for pipeline leak detection using machine learning techniques [J]. *Journal of Loss Prevention in the Process Industries*, 2020, 66: 104143.

Smith J, Johnson R, Williams P. Future scenario of China's downstream oil reform: Improving the energy-environmental efficiency of the pipeline networks through interconnectivity [J]. *Energy Policy*, 2020, 140: 111403.

Tu R F, Zhang H, Xu B, et al. Machine learning application in batch scheduling for multi-product pipelines: a review [J]. *Journal of Pipeline Science and Engineering*, 2024, 4(3): 100180.

Tu R F, Zhang H, Xu S Y, et al. Pipeline sharing: boosting multi-product pipeline transport biofuels in the shift to low-carbon energy [J]. *Journal of Cleaner Production*, 2024, 437: 140663.

Zhang H, Liu Y, Wang X, et al. Intelligent pipeline monitoring system based on IoT and big data analytics [J]. *Measurement*, 2021, 172: 108987.

Liu Y, Zhang H, Wang X, et al. Pipeline integrity management in the era of digital transformation: A review [J]. *Engineering Applications of Computational Fluid Mechanics*, 2022, 16(1): 1-18.

Wang X, Liu Y, Zhang H, et al. A novel method for pipeline corrosion assessment using machine learning [J]. *Corrosion Science*, 2023, 212: 109876.

Zhang H, Liu Y, Wang X, et al. Advances in pipeline safety monitoring technologies: A review [J]. *Safety Science*, 2021, 139: 105293.

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