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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
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    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. 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.
    3. 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).
    4. 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.
    5. 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.
    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).
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