Research on the control of slack flow of China-Kazakhstan crude oil pipeline
DOI:
https://doi.org/10.21152/1750-9548.15.4.409Abstract
China-Kazakhstan pipeline is the first land import transnational crude oil pipeline in China. It is also the only long-distance crude oil channel connecting the resources in the west of Kazakhstan and the two refineries in the east of Kazakhstan and exports to China. It undertakes the dual responsibilities of crude oil supply of the two refineries in the east of Kazakhstan and the crude oil guarantee of refineries in Western China. At present, the annual throughput of China-Kazakhstan crude oil pipeline accounts for about 20% of China's onshore crude oil imports. Therefore, the pipeline’s safe, stable and efficient operation plays an important role in ensuring the strategic security of energy in Western China. Since the China-Kazakhstan crude oil pipeline has commissioned, it has been found that there is slack flow in the pipeline under different working conditions, which has a great impact on the safe and stable operation of the pipeline and the measurement accuracy of commercial trade. In this paper, the causes of slack flow in China-Kazakhstan crude oil pipeline are studied, the potential location of slack flow is analyzed, and the boundary conditions of slack flow condition are defined. At the same time, control strategies to avoid slack flow under different conditions are formulated by using simulation technology. The research results will provide direct technical case support for reasonable formulation of operation scheme of China-Kazakhstan crude oil pipeline system and terminal station inlet pressure control strategy, so as to ensure safe, stable and efficient operation of the pipeline.
References
Xu, P., He, L., Yang, D. , Zhou, S., & Yang, D. Blocking characteristics of high water-cut crude oil in low-temperature gathering and transportation pipeline. Chemical Engineering Research and Design, 2021, (3-4). https://doi.org/10.1016/j.cherd.2021.07.019
Shaik, N. B. Pedapati, S. R. Othman, A. R. Bingi, K. , & Dzubir, F. An intelligent model to predict the life condition of crude oil pipelines using artificial neural networks. Neural Computing and Applications, 2021, (3). https://doi.org/10.1007/s00521-021-06116-1
Mcarthur S D J, Davidson E M, Hossack J A, et al. Automating power system fault diagnosis through multi-agent system technology. Proceedings of the Hawaii International Conference on System Sciences, IEEE Computer Society, 2004:20059.1. https://doi.org/10.1109/HICSS.2004.1265190
Wang, S. Zuo, L. Li, M., Wang, Q., Xue, X., & Liu, Q., et al. The data-driven modeling of pressure loss in multi-batch refined oil pipelines with drag reducer using long short-term memory (lstm) network. Energies, 2021, 14. https://doi.org/10.3390/en14185871
Lpg, A. Xue, H. A., Yun, L. B., Lei, W. C., Pfy, B., & Shuang, S. A. Study on the thixotropy and structural recovery characteristics of waxy crude oil emulsion. Petroleum Science. 2021.
Sun, K. Ma, X. & Hou, R. Upgrading siberian (Russia) crude oil by hydrodesulfurization: kinetic parameter estimation in a trickle-bed reactor. Chinese Journal of Chemical Engineering, 2021,29, 212-220. https://doi.org/10.1016/j.cjche.2020.07.021
Xu, L. Hou, L. Zhu, Z., Li, Y. , & Wu, X. Mid-term prediction of electrical energy consumption for crude oil pipelines using a hybrid algorithm of support vector machine and genetic algorithm. Energy, 2021,222(1), 119955. https://doi.org/10.1016/j.energy.2021.119955
Bao, Y. & Zhang, J. Restart behavior of gelled waxy crude oil pipeline based on an elasto-viscoplastic thixotropic model: a numerical study. Journal of Non-Newtonian Fluid Mechanics, 2020, 104377. https://doi.org/10.1016/j.jnnfm.2020.104377
Hafez, K. M. The role of a plain dent on the failure mode of a crude oil pipeline. Engineering Failure Analysis, 2021,122, 105291. https://doi.org/10.1016/j.engfailanal.2021.105291
Shengzhu, Zhang, Xu, Wang, Frank, Y., & Cheng, et al. Modeling and analysis of a catastrophic oil spill and vapor cloud explosion in a confined space upon oil pipeline leaking. Petroleum Science, 2020, v.17 (02), 280-290. https://doi.org/10.1007/s12182-019-00403-2
Wang, Y., Magda, J., Venkatesan, R., Sambath, K., & Deo, M. Experimental and theoretical investigations of waxy crude oil in steady and transient pipe flows. Industrial And Engineering Chemistry Research, 2020, 59(30), 13783-13798. https://doi.org/10.1021/acs.iecr.0c00769
Yang, W. Q., Stott, A. L., & Beck, M. S. Development of capacitance tomographic imaging systems for oil pipeline measurements. Review of Scientific Instruments,1995, 66(8), 4326-4332. https://doi.org/10.1063/1.1145322
Sepehr, H., Nikrityuk, P., Breakey, D. , & Sanders, R. S. Numerical study of crude oil batch mixing in a long channel. Petroleum Science, 2019,16(1), 187-198. https://doi.org/10.1007/s12182-018-0276-4
Al-Busaidi, Z., Baawain, M., Sana, A., Ebrahimi, A., & Omidvarborna, H. Sustainable risk-based analysis towards remediation of an aquifer impacted by crude oil spills. Journal of Environmental Management, 2019,247(Oct.1), 333-341. https://doi.org/10.1016/j.jenvman.2019.05.121
Niermann, M., Druenert, S. , Kaltschmitt, M. , & Bonhoff, K. Liquid organic hydrogen carriers (lohcs) - techno-economic analysis of lohcs in a defined process chain. Energy & Environmental Science, 2019,12(1), 290-507. https://doi.org/10.1039/C8EE02700E
Liu, Y., Cheng, Q. , Gan, Y. , Wang, Y. , Li, Z. , & J Zhao. Multi-objective optimization of energy consumption in crude oil pipeline transportation system operation based on exergy loss analysis. Neurocomputing, 2019, 332(MAR.7), 100-110. https://doi.org/10.1016/j.neucom.2018.12.022
Yang, S. , Xi, W. , Jin, H. , & Wu, Q. Pyrosequencing investigation into the bacterial community in permafrost soils along the china-russia crude oil pipeline (crcop). PLoS ONE, 2012, 7(12), e52730. https://doi.org/10.1371/journal.pone.0052730
Magda, J. J. , El-Gendy, H. , Oh, K. , MD Deo, Montesi, A. , & Venkatesan, R. Time-dependent rheology of a model waxy crude oil with relevance to gelled pipeline restart. Energy & fuels, 2009,23(2), 1311-1315. https://doi.org/10.1021/ef800628g
Arora, H. , Hooper, P. , Del Linz, P. , Yang, H. , Chen, S. , & Dear, J. Modelling the behaviour of composite sandwich structures when subject to air-blast loading. International Journal of Multiphysics, 2012, 6(3), 199-218. https://doi.org/10.1260/1750-9548.6.3.199
Singh, P. , Fogler, H. S. , & Nagarajan, N. Prediction of the wax content of the incipient wax-oil gel in a pipeline: an application of the controlled-stress rheometer. Journal of Rheology, 1999,43(6), 1437-1459. https://doi.org/10.1122/1.551054
Abedi, S. S. , Abdolmaleki, A. , & Adibi, N. Failure analysis of scc and srb induced cracking of a transmission oil products pipeline - science direct. Engineering Failure Analysis, 2007,14( 1), 250-261. https://doi.org/10.1016/j.engfailanal.2005.07.024
Nixon, J. , & Macinnes, K. L. Application of pipe temperature simulator for norman wells oil pipeline. Canadian Geotechnical Journal, 2011,33(1), 140-149. https://doi.org/10.1139/t96-029
Singh, S. , Sarma, P. M. , & Lal, B. Biohydrogen production by thermoanaerobacterium thermosaccharolyticum teri s7 from oil reservoir flow pipeline. International Journal of Hydrogen Energy, 2014,39(9), 4206-4214. https://doi.org/10.1016/j.ijhydene.2013.12.179
Wu, Z. , Barosh, P. J. , Wang, L. , Hu, D. , & Wei, W. Numerical modeling of stress and strain associated with the bending of an oil pipeline by a migrating pingo in the permafrost region of the northern tibetan plateau. Engineering Geology, 2008,96(1-2), 62-77. https://doi.org/10.1016/j.enggeo.2007.10.001
Hennessy, A. J. , Neville, A. , & Roberts, K. J. An examination of additive-mediated wax nucleation in oil pipeline environments. Journal of Crystal Growth, 1999,198-199(1), 830-837. https://doi.org/10.1016/S0022-0248(98)01198-1
MD Chapetti, Otegui, J. L. , & Motylicki, J. Fatigue assessment of an electrical resistance welded oil pipeline. International Journal of Fatigue, 2002,24(1), 21-28. https://doi.org/10.1016/s0142-1123(01)00111-6
Yan, S. Z. , & Chyan, L. S. Performance enhancement of botdr fiber optic sensor for oil and gas pipeline monitoring. Optical Fiber Technology, 2010, 16(2), 100-109. https://doi.org/10.1016/j.yofte.2010.01.001
Zhu, H. , Lin, P. , & Pan, Q. A cfd (computational fluid dynamic) simulation for oil leakage from damaged submarine pipeline. Energy, 2014, 64, 887-899. https://doi.org/10.1016/j.energy.2013.10.037
Lei, H. , Huang, Z. , Liang, W. , Mao, Y. , & Que, P. W. Ultrasonic pig for submarine oil pipeline corrosion inspection. Russian Journal of Nondestructive Testing, 2009, 45(4), 285-291. https://doi.org/10.1134/S106183090904010X
Xu, P. , He, L. , Yang, D. , Zhou, S. , & Yang, D. Blocking characteristics of high water-cut crude oil in low-temperature gathering and transportation pipeline. Chemical Engineering Research and Design. 2021, (3-4). https://doi.org/10.1016/j.cherd.2021.07.019
Bao, Y. , Zhang, J. , Wang, X. , & Liu, W. Effect of pre-shear on structural behavior and pipeline restart of gelled waxy crude oil. Rsc Advances, 2016, 6(84), 80529-80540. https://doi.org/10.1039/C6RA16346G
Gan, Y. , Cheng, Q. , Sun, W. , Gao, W. , Liu, X. , & Liu, Y. The stability criterion model and stability analysis of waxy crude oil pipeline transportation system based on excess entropy production. Journal of Thermal Science, 2018,27(06), 1-14. https://doi.org/10.1007/s11630-018-1048-6
Mendoza-Cantu, A., Heydrich, S. C. , Cervantes, I. S. , & Orozco, O. O. Identification of environmentally vulnerable areas with priority for prevention and management of pipeline crude oil spills. Journal of Environmental Management, 2011,92(7), 1706-1713. https://doi.org/10.1016/j.jenvman.2011.02.008
Roehner, R. M., Fletcher, J. V. , Hanson, F. V. , & Dahdah, N. F. Comparative compositional study of crude oil solids from the transalaska pipeline system using high-temperature gas chromatography. Energy & Fuels, 2002,16(1), 211-217. https://doi.org/10.1021/ef010218m
Azevedo, C. Failure analysis of a crude oil pipeline. Engineering Failure Analysis, 2007,14(6), 978-994. https://doi.org/10.1016/j.engfailanal.2006.12.001
Yanhu, M. , Guoyu, L. , Wei, M. , Zhengmin, S. , Zhiwei, Z. , & Wang, F. Rapid permafrost thaw induced by heat loss from a buried warm-oil pipeline and a new mitigation measure combining seasonal air-cooled embankment and pipe insulation. Energy, 2020,203. https://doi.org/10.1016/j.energy.2020.117919
Hafez, K. M. The role of a plain dent on the failure mode of a crude oil pipeline. Engineering Failure Analysis, 2021,122, 105291. https://doi.org/10.1016/j.engfailanal.2021.105291
Xu, L., Hou, L., Zhu, Z., Li, Y., & Wu, X. Mid-term prediction of electrical energy consumption for crude oil pipelines using a hybrid algorithm of support vector machine and genetic algorithm. Energy, 2021, 222(1), 119955. https://doi.org/10.1016/j.energy.2021.119955
Wang, Q. , Ai, M., Shi, W. , Lyu, Y., & Yu, W. Study on corrosion mechanism and its influencing factors of a short distance intermittent crude oil transmission and distribution pipeline. Engineering Failure Analysis, 2020,118(3), 104892. https://doi.org/10.1016/j.engfailanal.2020.104892
Published
How to Cite
Issue
Section
Copyright (c) 2021 J Yang, Z Liu, W Wu, Z An, L Zhao, Q Sun

This work is licensed under a Creative Commons Attribution 4.0 International License.