Comprehensive Treatment Technology for Downhole Complex Problems in Old Oilfields and Its Application Effect
DOI: https://doi.org/10.62381/I265101
Author(s)
Xiaoning Cheng
Affiliation(s)
CCDC Changqing Down Hole Technology Company, Xi'an, China
Abstract
Old oilfields have entered a stage of high water cut and high recovery, characterized by complex downhole problems such as casing damage, crossflow, and blockage. Traditional single-treatment technologies have significant limitations. This paper proposes an intelligent integrated treatment technology system that integrates big data, artificial intelligence, and digital twins to address the complex downhole challenges faced by high water-cut old oilfields in my country, including reservoir blockage, casing damage, and inter-layer interference. The system achieves precise diagnosis through multi-source data integration, machine learning, and digital twins; it develops core technologies such as integrated wellbore repair and reservoir-based collaborative unblocking and permeability enhancement, and supports dynamic optimization processes based on big data. Field applications show that this system achieves a 267% increase in oil production, 12 months of recurrence-free casing repair, and a 15 percentage point reduction in water cut in typical wells, significantly improving single-well productivity and the effectiveness of treatments while reducing operating costs. This system represents a shift from "segmented treatment" to "systematic rehabilitation" in the management of downhole problems in old oilfields, providing key technical support for the precise and intelligent development of secondary development of old oilfields.
Keywords
Old Oilfield; Complex Downhole Problems; Integrated Treatment Technology; Well Workover Operations; Application Effects
References
[1]Yue D T. A Review of Improvement and Enhanced Oil Recovery Technologies for Old Oilfields. Acta Petrolei Sinica, 1998, 19(3): 46.
[2]Sneider R M, Sneider J S. New oil in old places: The value of mature-field redevelopment. 2001.
[3]Wang Y A, Wu Y G, Men X Y. Situation, Challenges and Prospects for Stable Production of China’s Old Oilfields//Oil Forum. 2024, 43(3): 18.
[4]Wang H, Lin X, Jiang L, et al. An oilfield production prediction method based on clustering and long short-term memory neural network. Petroleum Science Bulletin, 2024, 9(1): 62-72
[5]Zhang Q, Zhou Z, Yi X, et al. Experimental Study and Molecular Dynamics Simulation of Oil Displacement Using Different Microemulsions in the Fang2 Block of Songfangtun Oilfield. ACS omega, 2024, 9(49): 48438-48451.
[6]Rezk R S, Abd-Elhamed M S, Hegazy M, et al. Brown Fields Development: Strategies, Challenges, and Opportunities//SPE EOR Conference at Oil and Gas West Asia. SPE, 2025: D031S051R001.
[7]Tao F, Yang Q H, Bairu S, et al. Downhole Power Generation: Status, Problems, and Prospects//Abu Dhabi International Petroleum Exhibition and Conference. SPE, 2024: D041S136R005.
[8]Zhang J, Wang H, Ji G, et al. Technologies and Achievements for Drilling and Completion of Onshore Deep and Ultra-Deep Wells in China//International Petroleum Technology Conference. IPTC, 2025: D032S009R016.
[9]Chen Z, Xie X, Hou Y, et al. Research on Downhole Blocking and Acidizing Technology for Low Pressure Oil and Gas Wells in Old Oil and Gas Fields//Journal of Physics: Conference Series. IOP Publishing, 2023, 2610(1): 012048.
[10]Zheng J, Li J, Wu J, et al. Review of Downhole Throttle Failure in Oil and Gas Wells. Journal of Failure Analysis and Prevention, 2023, 23(2): 609-621.
[11]Aseel A, Roy R, Sunil P. Predictive big data analytics for drilling downhole problems: A review. Energy Reports, 2023, 9: 5863-5876.
[12]Lai W, Zhang H, Jiang D W, et al. Digital twin and big data technologies benefit oilfield management//Abu Dhabi International Petroleum Exhibition and Conference. SPE, 2022: D031S079R002.
[13]Wang D M, Zhang H Y, Wang Y, et al. Injection and production technology in the same well and its application in the field. Daqing Petroleum Geology and Development, 2023, 42(04): 45-54.