IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v244y2022ipbs0360544221032801.html
   My bibliography  Save this article

Influence of the location of drilling fluid loss on wellbore temperature distribution during drilling

Author

Listed:
  • Zhang, Zheng
  • Wei, Yongqi
  • Xiong, Youming
  • Peng, Geng
  • Wang, Guorong
  • Lu, Jingsheng
  • Zhong, Lin
  • Wang, Jingpeng

Abstract

Circulation loss can occur at different positions during drilling, which has different effects on the wellbore temperature distribution. To ensure the safety and effectiveness of the drilling process, it is necessary to study the influence of circulation loss at different positions on the wellbore temperature distribution. In this study, we established mathematical models of wellbore temperature distribution corresponding to different situations in which circulation loss occurred and obtained the wellbore temperature distribution for each situation. When circulation loss occurred in the one-dimensional region, the annulus drilling fluid temperature at the circulation loss position changed suddenly; when it occurred in the two-dimensional region, the wellbore temperature at the circulation loss position was significantly disturbed. Under other conditions unchanged, as the circulation loss occurred closer to the bottom hole, the lower the wellbore temperature became at the same well depth. After circulation loss occurred, the formation temperature in the circulation loss area decreased significantly. The difference between the wellbore temperature distribution curve after circulation loss occurs and the wellbore temperature distribution curve when no circulation loss occurred can be used to monitor the location of the circulation loss in real time.

Suggested Citation

  • Zhang, Zheng & Wei, Yongqi & Xiong, Youming & Peng, Geng & Wang, Guorong & Lu, Jingsheng & Zhong, Lin & Wang, Jingpeng, 2022. "Influence of the location of drilling fluid loss on wellbore temperature distribution during drilling," Energy, Elsevier, vol. 244(PB).
  • Handle: RePEc:eee:energy:v:244:y:2022:i:pb:s0360544221032801
    DOI: 10.1016/j.energy.2021.123031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221032801
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.123031?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marshall L. Fisher, 2004. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 50(12_supple), pages 1861-1871, December.
    2. Cheng, Wen-Long & Nian, Yong-Le & Li, Tong-Tong & Wang, Chang-Long, 2014. "A novel method for predicting spatial distribution of thermal properties and oil saturation of steam injection well from temperature logs," Energy, Elsevier, vol. 66(C), pages 898-906.
    3. Zhang, Zheng & Xiong, Youming & Gao, Yun & Liu, Liming & Wang, Menghao & Peng, Geng, 2018. "Wellbore temperature distribution during circulation stage when well-kick occurs in a continuous formation from the bottom-hole," Energy, Elsevier, vol. 164(C), pages 964-977.
    4. Zhang, Zheng & Xiong, Youming & Pu, Hui & Sun, Zheng, 2021. "Effect of the variations of thermophysical properties of drilling fluids with temperature on wellbore temperature calculation during drilling," Energy, Elsevier, vol. 214(C).
    5. Mou Yang & Yingfeng Meng & Gao Li & Yongjie Li & Ying Chen & Xiangyang Zhao & Hongtao Li, 2013. "Estimation of Wellbore and Formation Temperatures during the Drilling Process under Lost Circulation Conditions," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-11, July.
    6. Abbas, Ahmed K. & Bashikh, Ali A. & Abbas, Hayder & Mohammed, Haider Q., 2019. "Intelligent decisions to stop or mitigate lost circulation based on machine learning," Energy, Elsevier, vol. 183(C), pages 1104-1113.
    7. Marshall L. Fisher, 2004. "Comments on ÜThe Lagrangian Relaxation Method for Solving Integer Programming ProblemsÝ," Management Science, INFORMS, vol. 50(12_supple), pages 1872-1874, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xishun & Shi, Junfeng & Zhao, Ruidong & Ma, Gaoqiang & Li, Zhongyang & Wang, Xiaofei & Zhang, Jinke, 2024. "Simulation of wellbore pipe flow in oil production engineering: Offshore concentric double-tube CO2-assisted superheated steam wellbore during SAGD process of heavy oil reservoirs," Energy, Elsevier, vol. 294(C).
    2. Guo, Junyu & Wan, Jia-Lun & Yang, Yan & Dai, Le & Tang, Aimin & Huang, Bangkui & Zhang, Fangfang & Li, He, 2023. "A deep feature learning method for remaining useful life prediction of drilling pumps," Energy, Elsevier, vol. 282(C).
    3. Pang, Boxue & Ren, Xianghui & Liu, Zaobao & Wang, Xin & Liu, Xu, 2023. "Investigation on multiphase flow of multi-size cuttings particles and non-Newtonian drilling fluids in oil and gas horizontal well drilling using kinetic theory of granular flow," Energy, Elsevier, vol. 282(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Xishun & Shi, Junfeng & Zhao, Ruidong & Ma, Gaoqiang & Li, Zhongyang & Wang, Xiaofei & Zhang, Jinke, 2024. "Simulation of wellbore pipe flow in oil production engineering: Offshore concentric double-tube CO2-assisted superheated steam wellbore during SAGD process of heavy oil reservoirs," Energy, Elsevier, vol. 294(C).
    2. An, Yu & Zhang, Yu & Zeng, Bo, 2015. "The reliable hub-and-spoke design problem: Models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 103-122.
    3. Dollevoet, Twan & van Essen, J. Theresia & Glorie, Kristiaan M., 2018. "Solution methods for the tray optimization problem," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1070-1084.
    4. Alexandre Belloni & Mitchell J. Lovett & William Boulding & Richard Staelin, 2012. "Optimal Admission and Scholarship Decisions: Choosing Customized Marketing Offers to Attract a Desirable Mix of Customers," Marketing Science, INFORMS, vol. 31(4), pages 621-636, July.
    5. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.
    6. Junming Liu & Weiwei Chen & Jingyuan Yang & Hui Xiong & Can Chen, 2022. "Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 769-789, March.
    7. Zheng, Jianfeng & Meng, Qiang & Sun, Zhuo, 2014. "Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design," European Journal of Operational Research, Elsevier, vol. 234(3), pages 874-884.
    8. Vasile BRÄ‚TIAN, 2018. "Portfolio Optimization. Application of the Markowitz Model Using Lagrange and Profitability Forecast," Expert Journal of Economics, Sprint Investify, vol. 6(1), pages 26-34.
    9. Miguel A. Lejeune & John Turner, 2019. "Planning Online Advertising Using Gini Indices," Operations Research, INFORMS, vol. 67(5), pages 1222-1245, September.
    10. Claudio Gambella & Joe Naoum-Sawaya & Bissan Ghaddar, 2018. "The Vehicle Routing Problem with Floating Targets: Formulation and Solution Approaches," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 554-569, August.
    11. Zhang, Zhi-Hai & Jiang, Hai & Pan, Xunzhang, 2012. "A Lagrangian relaxation based approach for the capacitated lot sizing problem in closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 249-255.
    12. Xia, Jun & Wang, Kai & Wang, Shuaian, 2019. "Drone scheduling to monitor vessels in emission control areas," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 174-196.
    13. Ahmadi-Javid, Amir & Hoseinpour, Pooya, 2019. "Service system design for managing interruption risks: A backup-service risk-mitigation strategy," European Journal of Operational Research, Elsevier, vol. 274(2), pages 417-431.
    14. Fatemeh Keshavarz-Ghorbani & Seyed Hamid Reza Pasandideh, 2022. "A Lagrangian relaxation algorithm for optimizing a bi-objective agro-supply chain model considering CO2 emissions," Annals of Operations Research, Springer, vol. 314(2), pages 497-527, July.
    15. Margarita P. Castro & Andre A. Cire & J. Christopher Beck, 2020. "An MDD-Based Lagrangian Approach to the Multicommodity Pickup-and-Delivery TSP," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 263-278, April.
    16. Hoseinpour, Pooya & Ahmadi-Javid, Amir, 2016. "A profit-maximization location-capacity model for designing a service system with risk of service interruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 113-134.
    17. Steeger, Gregory & Rebennack, Steffen, 2017. "Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem," European Journal of Operational Research, Elsevier, vol. 257(2), pages 669-686.
    18. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    19. Thomas L. Magnanti, 2021. "Optimization: From Its Inception," Management Science, INFORMS, vol. 67(9), pages 5349-5363, September.
    20. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2023. "A general purpose exact solution method for mixed integer concave minimization problems," European Journal of Operational Research, Elsevier, vol. 309(3), pages 977-992.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:244:y:2022:i:pb:s0360544221032801. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.