IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v278y2023ipas0360544223012537.html
   My bibliography  Save this article

Spatiotemporal simulation of gas-liquid transport in the production process of continuous undulating pipelines

Author

Listed:
  • Li, Xiaoping
  • Yang, Qi
  • Xie, Xugang
  • Chen, Sihang
  • Pan, Chen
  • He, Zhouying
  • Gong, Jing
  • Hong, Bingyuan

Abstract

Large sections of gas accumulation easily form in continuously undulating liquid pipelines to impede the commissioning process affecting the safe operation of the pipeline. To solve the gas resistance and overpressure during the commissioning of continuously undulating pipeline in complex terrain, a whole process commissioning simulation model is proposed to quantitatively calculate the location and volume of gas accumulation and to monitor the pressure drop across the line in the real time. Based on a single V-shaped pipe compression process model, the proposed model considers the influence of back pressure, gas-liquid migration and integrates different process such as high point exhausting, pigging process and pump-pipe coordination. Multiple operating conditions of two real pipelines are simulated, and the results show that the proposed model has an accuracy of within ±15% for predicting the pressure along the pipeline and tracking the pigging device, indicating that the gas transport model of the continuous undulating pipeline production process has acceptable accuracy. In addition, the applicability of the proposed model under different operating condition is also verified. Specifically, the gas accumulation ratio and safety pressure of the entire pipeline are calculated by considering multiple sets of different exhaust Schemes for different flow rates, high points, and the use of pigging devices on two different real pipelines, demonstrating that the model has good generality and feasibility. Secondly, the model can calculate the pressure drop at different positions along the entire pipeline, monitor the position of the pigging device in real time, and simulate comprehensive production exhaust Schemes, demonstrating that the model has comprehensive functionality and some generality. In summary, the proposed model can provide validation and guidance for the subsequent production of related continuous undulating liquid pipelines.

Suggested Citation

  • Li, Xiaoping & Yang, Qi & Xie, Xugang & Chen, Sihang & Pan, Chen & He, Zhouying & Gong, Jing & Hong, Bingyuan, 2023. "Spatiotemporal simulation of gas-liquid transport in the production process of continuous undulating pipelines," Energy, Elsevier, vol. 278(PA).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pa:s0360544223012537
    DOI: 10.1016/j.energy.2023.127859
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223012537
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127859?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. Hong, Bingyuan & Li, Xiaoping & Song, Shangfei & Chen, Shilin & Zhao, Changlong & Gong, Jing, 2020. "Optimal planning and modular infrastructure dynamic allocation for shale gas production," Applied Energy, Elsevier, vol. 261(C).
    2. Liang Feng & Huafeng Zhu & Ying Song & Wenchen Cao & Ziyuan Li & Wenlong Jia, 2022. "Modeling of Gas Migration in Large Elevation Difference Oil Transmission Pipelines during the Commissioning Process," Energies, MDPI, vol. 15(4), pages 1-19, February.
    3. Ma, Tao & Yang, Hongxing & Guo, Xiaodong & Lou, Chengzhi & Shen, Zhicheng & Chen, Jian & Du, Jiyun, 2018. "Development of inline hydroelectric generation system from municipal water pipelines," Energy, Elsevier, vol. 144(C), pages 535-548.
    4. Hong, Bingyuan & Li, Xiaoping & Li, Yu & Chen, Shilin & Tan, Yao & Fan, Di & Song, Shangfei & Zhu, Baikang & Gong, Jing, 2022. "An improved hydraulic model of gathering pipeline network integrating pressure-exchange ejector," Energy, Elsevier, vol. 260(C).
    5. Tao Deng & Jing Gong & Haihao Wu & Yu Zhang & Siqi Zhang & Qi Lin & Huishu Liu, 2013. "Hydraulic Transients Induced by Pigging Operation in Pipeline with a Long Slope," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-9, October.
    6. Fan, Di & Gong, Jing & Zhang, Shengnan & Shi, Guoyun & Kang, Qi & Xiao, Yaqi & Wu, Changchun, 2021. "A transient composition tracking method for natural gas pipe networks," Energy, Elsevier, vol. 215(PA).
    7. Chu, Jiawei & Liu, Yu & Lv, Xin & Li, Qingping & Dong, Hongsheng & Song, Yongchen & Zhao, Jiafei, 2021. "Experimental investigation on blockage predictions in gas pipelines using the pressure pulse wave method," Energy, Elsevier, vol. 230(C).
    Full references (including those not matched with items on IDEAS)

    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. Koo, Bonchan & Chang, Seungjoon & Kwon, Hweeung, 2023. "Digital twin for natural gas infrastructure operation and management via streaming dynamic mode decomposition with control," Energy, Elsevier, vol. 274(C).
    2. Yin, Xiong & Wen, Kai & Huang, Weihe & Luo, Yinwei & Ding, Yi & Gong, Jing & Gao, Jianfeng & Hong, Bingyuan, 2023. "A high-accuracy online transient simulation framework of natural gas pipeline network by integrating physics-based and data-driven methods," Applied Energy, Elsevier, vol. 333(C).
    3. Kai Wen & Hailong Xu & Wei Qi & Haichuan Li & Yichen Li & Bingyuan Hong, 2023. "Heat Transfer Model of Natural Gas Pipeline Based on Data Feature Extraction and First Principle Models," Energies, MDPI, vol. 16(3), pages 1-21, January.
    4. Yao, Yao & Shen, Zhicheng & Wang, Qiliang & Du, Jiyun & Lu, Lin & Yang, Hongxing, 2023. "Development of an inline bidirectional micro crossflow turbine for hydropower harvesting from water supply pipelines," Applied Energy, Elsevier, vol. 329(C).
    5. Vadim Fetisov & Aleksey V. Shalygin & Svetlana A. Modestova & Vladimir K. Tyan & Changjin Shao, 2022. "Development of a Numerical Method for Calculating a Gas Supply System during a Period of Change in Thermal Loads," Energies, MDPI, vol. 16(1), pages 1-16, December.
    6. Chen, Zherui & Dai, Sining & Chen, Cong & Lyu, Huangwu & Zhang, Shuheng & Liu, Xuanji & Li, Yanghui, 2024. "Hydrate aggregation in oil-gas pipelines: Unraveling the dual role of asphalt and water," Energy, Elsevier, vol. 290(C).
    7. Bingyuan Hong & Yanbo Li & Xiaoping Li & Shuaipeng Ji & Yafeng Yu & Di Fan & Yating Qian & Jian Guo & Jing Gong, 2021. "Numerical Simulation of Gas-Solid Two-Phase Erosion for Elbow and Tee Pipe in Gas Field," Energies, MDPI, vol. 14(20), pages 1-18, October.
    8. Andres Soage & Ruben Juanes & Ignasi Colominas & Luis Cueto-Felgueroso, 2024. "Optimization of Financial Indicators in Shale-Gas Wells Combining Numerical Decline Curve Analysis and Economic Data Analysis," Energies, MDPI, vol. 17(4), pages 1-25, February.
    9. Kele Yan & Dianqiang Xu & Qiong Wang & Jiawei Chu & Shengjie Zhu & Jiafei Zhao, 2023. "Experimental Investigation of Gas Transmission Pipeline Blockage Detection Based on Dynamic Pressure Method," Energies, MDPI, vol. 16(15), pages 1-10, July.
    10. Delgado, J. & Ferreira, J.P. & Covas, D.I.C. & Avellan, F., 2019. "Variable speed operation of centrifugal pumps running as turbines. Experimental investigation," Renewable Energy, Elsevier, vol. 142(C), pages 437-450.
    11. Wen, Kai & Jiao, Jianfeng & Zhao, Kang & Yin, Xiong & Liu, Yuan & Gong, Jing & Li, Cuicui & Hong, Bingyuan, 2023. "Rapid transient operation control method of natural gas pipeline networks based on user demand prediction," Energy, Elsevier, vol. 264(C).
    12. Zhang, Guangchao & Lv, Kai & Xie, Yudong & Wang, Yong & Shan, Kunshan, 2023. "Performance study of a control valve with energy harvesting based on a modified passive model," Energy, Elsevier, vol. 285(C).
    13. Zhou, Dengji & Jia, Xingyun & Ma, Shixi & Shao, Tiemin & Huang, Dawen & Hao, Jiarui & Li, Taotao, 2022. "Dynamic simulation of natural gas pipeline network based on interpretable machine learning model," Energy, Elsevier, vol. 253(C).
    14. Guojun Yu & Huihao Liu & Huijin Xu, 2023. "New Advancements in Heat and Mass Transfer: Fundamentals and Applications," Energies, MDPI, vol. 16(7), pages 1-4, March.
    15. Hong, Bingyuan & Du, Zhaonan & Qiao, Dan & Liu, Daiwei & Li, Yu & Sun, Xiaoqing & Gong, Jing & Zhang, Hongyu & Li, Xiaoping, 2024. "Sustainable supply chain of distributed multi-product gas fields based on skid-mounted equipment to dynamically respond to upstream and market fluctuations," Energy, Elsevier, vol. 292(C).
    16. Hong, Bingyuan & Cui, Xuemeng & Wang, Bohong & Fan, Di & Li, Xiaoping & Gong, Jing, 2022. "Long-term dynamic allocation and maintenance planning of modular equipment to enhance gas field production flexibility," Energy, Elsevier, vol. 252(C).
    17. Ye, Jihong & Jiang, Wei & Yang, Xinxiang & Hong, Bingyuan, 2023. "Emergency materials response framework for petrochemical enterprises based on multi-objective optimization," Energy, Elsevier, vol. 269(C).
    18. Dancker, Jonte & Wolter, Martin, 2022. "A coupled transient gas flow calculation with a simultaneous calorific-value-gradient improved hydrogen tracking," Applied Energy, Elsevier, vol. 316(C).
    19. Qi, Shikun & Zhao, Wei & Qiu, Rui & Liu, Chunying & Li, Zhuochao & Lan, Hao & Liang, Yongtu, 2023. "Capacity allocation method of hydrogen-blending natural gas pipeline network based on bilevel optimization," Energy, Elsevier, vol. 285(C).
    20. Qiao Guo & Yuan Liu & Yunbo Yang & Tao Song & Shouxi Wang, 2022. "Improved Adaptive Time Step Method for Natural Gas Pipeline Transient Simulation," Energies, MDPI, vol. 15(14), pages 1-14, July.

    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:278:y:2023:i:pa:s0360544223012537. 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.