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 & 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).
    2. 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).
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    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. Chen, Qian & Guan, Aocheng & Chen, Feng & Huang, Wei & Jin, Antai & Gadalla, Mamdouh & Wang, Bohong, 2024. "A transient gas pipeline network simulation model for decoupling the hydraulic-thermal process and the component tracking process," Energy, Elsevier, vol. 301(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. 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).
    4. 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.
    5. Zhao, Yiming & Hu, Dapeng & Yu, Yang & Li, Haoran, 2023. "Study on gas wave ejector with a novel wave rotor applied in natural gas extraction," Energy, Elsevier, vol. 277(C).
    6. Bingyuan Hong & Xiaoping Li & Yanbo Li & Yu Li & Yafeng Yu & Yumo Wang & Jing Gong & Dihui Ai, 2021. "Numerical Simulation of Elbow Erosion in Shale Gas Fields under Gas-Solid Two-Phase Flow," Energies, MDPI, vol. 14(13), pages 1-15, June.
    7. Bao, Mupeng & Xie, Yudong & Zhang, Xinbiao & Ju, Jinyong & Wang, Yong, 2023. "Performance improvement of a control valve with energy harvesting," Energy, Elsevier, vol. 263(PC).
    8. 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).
    9. 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.
    10. 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).
    11. Ashraf Virk, Mati-ur-Rasool & Mysorewala, Muhammad Faizan & Cheded, Lahouari & Aliyu, AbdulRahman, 2022. "Review of energy harvesting techniques in wireless sensor-based pipeline monitoring networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    12. 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.
    13. Wen, Kai & Lu, Yangfan & Lu, Meitong & Zhang, Wenwei & Zhu, Ming & Qiao, Dan & Meng, Fanpeng & Zhang, Jing & Gong, Jing & Hong, Bingyuan, 2022. "Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation," Energy, Elsevier, vol. 257(C).
    14. 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.
    15. Bilel Jarraya & Hatem Afi & Anis Omri, 2023. "Analyzing the Profitability and Efficiency in European Non-Life Insurance Industry," Methodology and Computing in Applied Probability, Springer, vol. 25(2), pages 1-25, June.
    16. 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).
    17. Hu, Yili & Yi, Zhiran & Dong, Xiaoxue & Mou, Fangxiao & Tian, Yingwei & Yang, Qinghai & Yang, Bin & Liu, Jingquan, 2019. "High power density energy harvester with non-uniform cantilever structure due to high average strain distribution," Energy, Elsevier, vol. 169(C), pages 294-304.
    18. 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.
    19. Shen, Zhicheng & Yao, Yao & Wang, Qiliang & Lu, Lin & Yang, Hongxing, 2023. "A novel micro power generation system to efficiently harvest hydroelectric energy for power supply to water intelligent networks of urban water pipelines," Energy, Elsevier, vol. 268(C).
    20. 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.

    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.