Numerical simulation and safety evaluation of multi-source leakage of buried product oil pipeline

References

• Adegboye, M. A., A. Karnik, and W. Fung. 2021. Numerical study of pipeline leak detection for gas-liquid stratified flow[J]. Journal of Natural Gas Science and Engineering 94:104054. doi:10.1016/j.jngse.2021.104054.
   Web of Science ®Google Scholar
• Analysis report on petroleum and chemical accidents at home and abroad[R]. SINOPEC Safety Engineering Institute, 2017.
   Google Scholar
• Araújo M D, V., F. D. T. Avares, and S. R. D. F. Barbosa. 2013. Numerical study of oil flow in tee junction with leaks[J]. Advances in Petroleum Exploration and Development 6 (2):1–11.
   Google Scholar
• Araújo M D, V., S. R. D. F. Neto, and A. G. B. D. Lima. 2013. Theoretical evaluation of two-phase flow in a horizontal duct with leaks[J]. Advances in Chemical Engineering and Science 03 (4):6–14. doi:10.4236/aces.2013.34A1002.
   Google Scholar
• Bertsch, M., R. Dal Passo, and V. C. J. Duijn. 2003. Analysis of oil trapping in porous media flow[J]. SIAM Journal on Mathematical Analysis 35 (1):245–67. doi:10.1137/S0036141002407375.
   Web of Science ®Google Scholar
• Bezaatpour, J., E. Fatehifar, and A. Rasoulzadeh. 2020. CFD investigation of natural gas leakage and propagation from buried pipeline for anisotropic and partially saturated multilayer soil[J]. Journal of Cleaner Production 277:123940. doi:10.1016/j.jclepro.2020.123940.
   Web of Science ®Google Scholar
• Bonvicini, S., G. Antonioni, and V. Cozzani. 2018. Assessment of the risk related to environmental damage following major accidents in onshore pipelines[J]. Journal of Loss Prevention in the Process Industries 56:505–16. doi:10.1016/j.jlp.2018.11.005.
   Web of Science ®Google Scholar
• Chang, A., H. Sun, C. Zheng, B. Lu, C. Lu, R. Ma, and Y. Zhang. 2018. A time fractional convection–diffusion equation to model gas transport through heterogeneous soil and gas reservoirs[J]. Physica A 502:356–69. doi:10.1016/j.physa.2018.02.080.
   Web of Science ®Google Scholar
• Chen, C., C. Li, G. Reniers, and Yang, F. 2021. Safety and security of oil and gas pipeline transportation: A systematic analysis of research trends and future needs using WoS[J]. Journal of Cleaner Production 279:123583.
   Web of Science ®Google Scholar
• Chinello, G., A. Ayati A, D. Mcglinchey, G. Ooms, and R. Henkes. 2019. Comparison of computational fluid dynamics simulations and experiments for stratified air-water flows in pipes[J]. JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME 141 (5). doi: 10.1115/1.4041667.
   PubMed Web of Science ®Google Scholar
• Deng, Q., M. Fu, and X. Ren. 2020. Does pipelaying method affect the development of pipeline geohazards and maintenance cost? A case study of Zhongxian-Wuhan gas pipeline, China[J]. Bulletin of Engineering Geology and the Environment 79 (1):97–107. doi:10.1007/s10064-019-01567-2.
   Web of Science ®Google Scholar
• Ebrahimi-Moghadam, A., M. Farzaneh-Gord, A. Arabkoohsar, and A. J. Moghadam. 2018. CFD analysis of natural gas emission from damaged pipelines: Correlation development for leakage estimation[J]. Journal of Cleaner Production 199:257–71. doi:10.1016/j.jclepro.2018.07.127.
   Web of Science ®Google Scholar
• Fereidooni, Z., H. Tahayori, and A. Bahadori-Jahromi. 2021. A hybrid model-based method for leak detection in large scale water distribution networks[J]. Journal of Ambient Intelligence and Humanized Computing 12 (2):1613–29. doi:10.1007/s12652-020-02233-2.
   Web of Science ®Google Scholar
• Fu, H., L. Yang, H. Liang, S. Wang, and K. Ling. 2020. Diagnosis of the single leakage in the fluid pipeline through experimental study and CFD simulation[J]. Journal of Petroleum Science and Engineering 193:107437. doi:10.1016/j.petrol.2020.107437.
   Web of Science ®Google Scholar
• GB50253: Code for design of oil transportation pipeline engineering[S].
   Google Scholar
• Gong, S., T. Zhang, X. Wang, and C. Liu. 2020. Numerical simulation on dynamic behaviour of deepwater J-lay systems[J]. Ocean Engineering 196:106771. doi:10.1016/j.oceaneng.2019.106771.
   Web of Science ®Google Scholar
• Gu, Y., Z. Zuo, C. Shi, and X. Hu. 2020. Feasibility study for spatial distribution of diesel oil in contaminated soils by laser induced fluorescence[J]. Applied Sciences. 10(3):1103. doi:10.3390/app10031103.
   Google Scholar
• He, G., Y. Liang, Y. Li, M. Wu, L. Sun, C. Xie, and F. Li. 2017. A method for simulating the entire leaking process and calculating the liquid leakage volume of a damaged pressurized pipeline[J]. Journal of Hazardous Materials 332:19–32. doi:10.1016/j.jhazmat.2017.02.039.
   PubMed Web of Science ®Google Scholar
• He, G., Y. Li, Y. Huang, L. Sun, and K. Liao. 2019a. A framework of smart pipeline system and its application on multiproduct pipeline leakage handling[J]. Energy 188:116031. doi:10.1016/j.energy.2019.116031.
   Web of Science ®Google Scholar
• He, G., X. Lyu, K. Liao, Y. Li, and L. Sun. 2019b. A method for fast simulating the liquid seepage-diffusion process coupled with internal flow after leaking from buried pipelines[J]. JOURNAL OF CLEANER PRODUCTION. 240(118167):118167. doi:10.1016/j.jclepro.2019.118167.
   Google Scholar
• Hermansyah, H., M. Nur Hidayat, A. Kumaraningrum, M. Yohda, and A. Shariff. 2018. Assessment, mitigation, and control of potential gas leakage in existing buildings not designed for gas installation in Indonesia[J]. Energies. 11(11):2970. doi:10.3390/en11112970.
   Web of Science ®Google Scholar
• ISO14121: Safety of machinery - risk assessment[S].
   Google Scholar
• ISO15649: Petroleum and natural gas industries-Piping[S].
   Google Scholar
• Kotzakoulakis, K., and S. C. George. 2018. Predicting the weathering of fuel and oil spills: A diffusion-limited evaporation model[J]. Chemosphere 190:442–53. doi:10.1016/j.chemosphere.2017.09.142.
   PubMed Web of Science ®Google Scholar
• Lazhar, A., L. Hadj-Taïeb, and E. Hadj-Taïeb. 2013. Two leaks detection in viscoelastic pipeline systems by means of transient[J]. Journal of Loss Prevention in the Process Industries 26 (6):1341–51. doi:10.1016/j.jlp.2013.08.007.
   Web of Science ®Google Scholar
• Li, X., G. Chen, and H. Zhu. 2017. Modelling and assessment of accidental oil release from damaged subsea pipelines[J]. Marine Pollution Bulletin 123 (1–2):133–41. doi:10.1016/j.marpolbul.2017.09.004.
   PubMed Web of Science ®Google Scholar
• Li, Z., H. Feng, Y. Liang, N. Xu, S. Nie, and H. Zhang 2019. A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo[J]. International Journal of Critical Infrastructure Protection 27:100325. doi:10.1016/j.ijcip.2019.100325.
   Web of Science ®Google Scholar
• Liang, B., H. Lan, and N. Lin. 2018. Diffusion simulation and safety assessment of oil leaked in the ground[J]. Journal of Petroleum Science and Engineering 167:498–505. doi:10.1016/j.petrol.2018.04.034.
   Web of Science ®Google Scholar
• Liu, B. 2020. Fluid simulation from entry to mastery[M]. Xueyan Plaza,Tsinghua University, Beijing, China: Tsinghua University press.
   Google Scholar
• Lyu, S., W. Wang, and Y. Zhang. 2019. Leakage position of pipeline on the underground diffusion of crude oil[Z]. IOP Conference Series: Earth and Environmental Science 237:32119. doi:10.1088/1755-1315/237/3/032119.
   Google Scholar
• Mohammadmoradi, P., S. Taheri, L. Bryant S, and A. Kantzas . 2018. Solvent diffusion and dispersion in partially saturated porous media: An experimental and numerical pore-level study[J]. Chemical Engineering Science 191:300–17. doi:10.1016/j.ces.2018.06.072.
   Web of Science ®Google Scholar
• Ossai, C. I. 2020. Corrosion defect modelling of aged pipelines with a feed-forward multi-layer neural network for leak and burst failure estimation[J]. Engineering Failure Analysis 110:104397. doi:10.1016/j.engfailanal.2020.104397.
   Web of Science ®Google Scholar
• Pan, Y., Q. Zhang, Y. Yu, Y. Tong, W. Wu, Y. Zhou, W. Hou, and J. Yang. 2021. Three-dimensional migration and resistivity characteristics of crude oil in heterogeneous soil layers[J]. ENVIRONMENTAL POLLUTION. 268(115309A):115309. doi:10.1016/j.envpol.2020.115309.
   PubMedGoogle Scholar
• Qin, G., P. Zhang, X. Hou, S. Wu, and Y. Wang. 2020. Risk assessment for oil leakage under the common threat of multiple natural hazards[J]. Environmental Science and Pollution Research. 27(14):16507–20. doi:10.1007/s11356-020-08184-7.
   PubMed Web of Science ®Google Scholar
• Rashed, T., and J. Weeks. 2003. Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas[J]. International Journal of Geographical Information Science 17 (6):547–76. doi:10.1080/1365881031000114071.
   Web of Science ®Google Scholar
• Rui, Z., G. Han, H. Zhang, S. Wang, H. Pu, and K. Ling. 2017. A new model to evaluate two leak points in a gas pipeline[J]. Journal of Natural Gas Science and Engineering 46:491–97. doi:10.1016/j.jngse.2017.08.025.
   Web of Science ®Google Scholar
• Shahriar, A., R. Sadiq, and S. Tesfamariam. 2012. Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis[J]. Journal of Loss Prevention in the Process Industries 25 (3):505–23. doi:10.1016/j.jlp.2011.12.007.
   Web of Science ®Google Scholar
• Shan, X., K. Liu, and P. Sun. 2017. Risk analysis on leakage failure of natural gas pipelines by fuzzy bayesian network with a bow-tie model[J]. Scientific Programming 2017:1–11. doi:10.1155/2017/3639524.
   Web of Science ®Google Scholar
• Sinha, S. K., and M. D. Pandey. 2002. Probabilistic neural network for reliability assessment of oil and gas pipelines[J]. Computer-aided Civil and Infrastructure Engineering 17 (5):320–29. doi:10.1111/1467-8667.00279.
   Web of Science ®Google Scholar
• Trapper, P. A., and I. Mishal. 2020. Numerical analysis of offshore pipe-lay subjected to environment-induced non-uniformly distributed follower loads[J]. Applied Ocean Research 100:102149. doi:10.1016/j.apor.2020.102149.
   Web of Science ®Google Scholar
• Verde, C., L. Molina, and L. Torres. 2014. Parameterized transient model of a pipeline for multiple leaks location[J]. Journal of Loss Prevention in the Process Industries 29:177–85. doi:10.1016/j.jlp.2014.02.013.
   Web of Science ®Google Scholar
• Vuruna, M., Z. Veličković, S. Perić, J. Bogdanov, N. Ivanković, and M. Bučko. 2017. The influence of atmospheric conditions on the migration of diesel fuel spilled in soil[J]. Archives of Environmental Protection. 43(1):73–79. doi:10.1515/aep-2017-0004.
   Web of Science ®Google Scholar
• Wang, X.H., L.M. Wang, G. Zheng, S. W. Sun, and R. Z. Yang. 2013. Simulation of leakage model of long-distance oil pipeline based on FLUENT[J]. Applied Mechanics and Materials 310:280–86. doi:10.4028/scientific.net/AMM.310.280.
   Google Scholar
• Wang, H., T. Fischer, W. Wieprecht, and D. Möller. 2015. A predictive method for volatile organic compounds emission from soil: Evaporation and diffusion behavior investigation of a representative component of crude oil[J]. Science of the Total Environment 530-531:38–44. doi:10.1016/j.scitotenv.2015.05.063.
   PubMed Web of Science ®Google Scholar
• Xing, C. 2012. Analysis on heat transfer and multiphase flow in leakage process of buried oil pipeline[D]. No. 99, Xuefu Street, Daqing, Heilongjiang, P. R. China: Northeast Petroleum University.
   Google Scholar
• Xing, J., H. Meng, and X. Meng. 2020. An urban pipeline accident model based on system engineering and game theory[J]. Journal of Loss Prevention in the Process Industries 64:104062. doi:10.1016/j.jlp.2020.104062.
   Web of Science ®Google Scholar
• Yan, H., H. Ma, and L. Chen. 2014. The mechanical plugging technology research based on the leakage of hazardous pipeline[J]. Advances in Experimental Medicine and Biology 794:95–140. doi:10.1007/978-94-007-7429-2_5.
   PubMedGoogle Scholar
• Yu, J., H. Chen, Y. Yu, and Z.L. Yang. 2019. A weakest t-norm based fuzzy fault tree approach for leakage risk assessment of submarine pipeline[J]. Journal of Loss Prevention in the Process Industries 62:103968. doi:10.1016/j.jlp.2019.103968.
   Web of Science ®Google Scholar
• Zhang, P., G. Qin, and Y. Wang. 2019. Risk assessment system for oil and gas pipelines laid in one ditch based on quantitative risk analysis[J]. Energies 12 (6):981. doi:10.3390/en12060981.
   Web of Science ®Google Scholar
• Zhang, J., Y. Chen, and H. Zhang. 2020. Local buckling evolution mechanism of a buried steel pipe under fault movements[J]. Energy Science & Engineering 8 (2):412–25. doi:10.1002/ese3.524.
   Web of Science ®Google Scholar
• Zhang, Y., and W. G. Weng. 2020. Bayesian network model for buried gas pipeline failure analysis caused by corrosion and external interference[J]. Reliability Engineering & System Safety 203:107089. doi:10.1016/j.ress.2020.107089.
   Web of Science ®Google Scholar
• Zhao, B. 2014. Qingdao pipeline explosion: Introductions and reflections[J]. Natural Hazards (Dordrecht) 74 (2):1299–305. doi:10.1007/s11069-014-1232-2.
   Web of Science ®Google Scholar