A Novel Safety Early Warning Methodology for Pipelines under Landslide Geological Hazard
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 15, Issue 1
Abstract
Pipelines serve as a crucial infrastructure for long-distance and cost-efficient transportation of oil and gas resources. The safety and reliability of oil and gas pipelines crossing mountainous areas, however, are susceptible to rainfall-induced landslides. Landslide-induced pipeline leakage or fracture may result in the release of oil and gas, causing resource waste and environmental contamination as well as casualties. To date, user-friendly and comprehensive methods for early warning about pipeline safety issues under landslides are scarce. The present study develops a novel early warning degree (EWD)-based safety early warning framework for oil and gas pipelines subjected to landslides, including three monitoring indexes of disaster-inducing bodies, disaster-causing bodies, and disaster-bearing bodies. The use of an improved fuzzy decision-making trial and evaluation laboratory (DEMATEL) method determines the weight of each index. The hybrid application of fuzzy comprehensive evaluation approach and three-dimensional (3D) space method is used to develop the 3D early warning matrix. The matrix finally integrates an improved radar chart technique to estimate EWD-based early warning intervals. The proposed framework has been implemented through a case study on an in-service pipeline, demonstrating its capability to improve the safety of oil and gas pipelines traversing landslide-prone areas, and enhance the resilience of pipelines against landslides.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by National Natural Science Foundation of China (NSFC No. 50974105).
References
ASME. 2018. Gas transmission distribution piping system. ASME B31.8. New York: ASME.
Bai, W. G., C. L. Qiu, and J. Zhang. 2013. “Research on evaluation and detection method of print quality based on the CCD information.” Appl. Mech. Mater. 303 (May): 543–549. https://doi.org/10.4028/www.scientific.net/AMM.303-306.543.
Brand, E. W., J. Premchitt, and H. B. Phillipson. 1984. “Relationship between rainfall and landslides in Hong Kong.” In Vol. 1 of Proc., 4th Int. Symp. on Landslides, 276–284. Toronto: Canadian Geotechnical Society.
Chen, C. 2019. “Study on monitoring and early warning technology of natural gas pipeline in landslide area.” Ph.D. thesis, School of Petroleum Engineering, Univ. of Southwest Petroleum.
Chen, H., G. Li, R. Fang, and M. Zheng. 2021. “Early warning indicators of landslides based on deep displacements: Applications on Jinping landslide and Wendong landslide, China.” Front. Earth Sci. 9 (Nov): 747379. https://doi.org/10.3389/feart.2021.747379.
Chiang, J.-L., C.-M. Kuo, and L. Fazeldehkordi. 2022. “Using deep learning to formulate the landslide rainfall threshold of the potential large-scale landslide.” Water 14 (20): 3320. https://doi.org/10.3390/w14203320.
China National Petroleum Corporation Code. 2014. Specification for oil and gas pipeline landslide hazard monitoring. QSY 1673. Beijing: China National Petroleum Corporation Code.
Chinese Standard. 2015. Code for design of gas transmission pipeline engineering. GB 50251. Beijing: Chinese Standard.
Chinese Standard. 2016. Code for geological investigation of landslide prevention. GB 32864. Beijing: Chinese Standard.
Distefano, P., D. J. Peres, P. Scandura, and A. Cancelliere. 2022. “Brief communication: Introducing rainfall thresholds for landslide triggering based on artificial neural networks.” Nat. Hazards Earth Syst. Sci. 22 (4): 1151–1157. https://doi.org/10.5194/nhess-22-1151-2022.
Kasai, S., N. Li, and D. P. Fang. 2015. “A system-of-systems approach to understanding urbanization-state of the art and prospect.” Smart Sustainable Built Environ. 4 (2): 154–171. https://doi.org/10.1108/SASBE-07-2014-0038.
Keefer, D. K., R. C. Wilson, R. K. Mark, E. E. Brabb, W. M. Brown III, S. D. Ellen, E. L. Harp, G. F. Wieczorek, C. S. Alger, and R. S. Zatkin. 1987. “Real-time landslide warning during heavy rainfall.” Science 238 (4829): 921–925. https://doi.org/10.1126/science.238.4829.921.
Li, J., C. Chen, Y. Li, H. Wu, and X. Li. 2021a. “Difficulty assessment of shoveling stacked materials based on the fusion of neural network and radar chart information.” Autom. Constr. 132 (Dec): 103966. https://doi.org/10.1016/j.autcon.2021.103966.
Li, J., and K. Xu. 2021. “A combined fuzzy DEMATEL and cloud model approach for risk assessment in process industries to improve system reliability.” Qual. Reliab. Eng. Int. 37 (5): 2110–2133. https://doi.org/10.1002/qre.2848.
Li, X., M. Z. Bai, B. H. He, P. X. Li, L. B. Zong, Y. Chen, and H. Shi. 2021b. “Safety analysis of landslide in pipeline area through field monitoring.” J. Test. Eval. 51 (1): 3170–3182. https://doi.org/10.1520/JTE20200751.
Liao, Y., C. Liu, T. Wang, T. Xu, J. Zhang, and G. Liang. 2021. “Mechanical behavior analysis of gas pipeline with defects under lateral landslide.” Proc. Inst. Mech. Eng., Part C: J. Mech. Eng. Sci. 235 (23): 6752–6766. https://doi.org/10.1177/09544062211017161.
Macciotta, R., M. Hendry, and C. D. Martin. 2016. “Developing an early warning system for a very slow landslide based on displacement monitoring.” Nat. Hazard. 81 (2): 887–907. https://doi.org/10.1007/s11069-015-2110-2.
Naidu, S., K. S. Sajinkumar, T. Oommen, V. J. Anuja, R. A. Samuel, and C. Muraleedharan. 2018. “Early warning system for shallow landslides using rainfall threshold and slope stability analysis.” Geosci. Front. 9 (6): 1871–1882. https://doi.org/10.1016/j.gsf.2017.10.008.
Ni, P. P., G. X. Mei, and Y. L. Zhao. 2018. “Influence of raised groundwater level on the stability of unsaturated soil slopes.” Int. J. Geomech. 18 (12): 4018168. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001316.
Pandey, M., R. Litoriya, and P. Pandey. 2019. “Application of fuzzy DEMATEL approach in analyzing mobile app issues.” Program. Comput. Software 45 (Sep): 268–287. https://doi.org/10.1134/S0361768819050050.
Peng, W., Y. Li, Y. Fang, Y. Wun, and Q. Li. 2019. “Radar chart for estimation performance evaluation.” IEEE Access 7 (Dec): 113880–113888. https://doi.org/10.1109/ACCESS.2019.2933659.
Peres, D. J., and A. Cancelliere. 2021. “Comparing methods for determining landslide early warning thresholds: Potential use of non-triggering rainfall for locations with scarce landslide data availability.” Landslides 18 (9): 3135–3147. https://doi.org/10.1007/s10346-021-01704-7.
Qureshi, M. I., R. M. Yusoff, S. S. Hishan, A. F. Alam, K. Zaman, and A. M. Rasli. 2019. “Natural disasters and Malaysian economic growth: Policy reforms for disasters management.” Environ. Sci. Pollut. Res. 26 (15): 15496–15509. https://doi.org/10.1007/s11356-019-04866-z.
Segoni, S., L. Piciullo, and S. L. Gariano. 2018. “A review of the recent literature on rainfall thresholds for landslide occurrence.” Landslides 15 (8): 1483–1501. https://doi.org/10.1007/s10346-018-0966-4.
Shen, Y., D. Chen, M. Zhang, and T. Zuo. 2022. “Fuzzy comprehensive safety evaluation of pipeline disaster in China-Russia crude oil permafrost region based on improved analytic hierarchy process-entropy weight method.” Adv. Mater. Sci. Eng. 2022 (May): 1–10. https://doi.org/10.1155/2022/3157793.
Teng, M.-C., and S.-S. Ke. 2021. “Disaster impact assessment of the underground hazardous materials pipeline.” J. Loss Prev. Process Ind. 71 (Jul): 104486. https://doi.org/10.1016/j.jlp.2021.104486.
Umer, Z., G. Alberto, and M. Stefano. 2020. “An analytical procedure for modelling pipeline-landslide interaction in gas pipelines.” J. Nat. Gas Sci. Eng. 81 (Sep): 103474. https://doi.org/10.1016/j.jngse.2020.103474.
Vasseghi, A., E. Haghshenas, A. Soroushian, and M. Rakhshandeh. 2021. “Failure analysis of a natural gas pipeline subjected to landslide.” Eng. Fail. Anal. 119 (Jan): 105009. https://doi.org/10.1016/j.engfailanal.2020.105009.
Xu, Q., D. Peng, S. Zhang, X. Zhu, C. He, X. Qi, K. Zhao, D. Xiu, and N. Ju. 2020. “Successful implementations of a real-time and intelligent early warning system for loess landslides on the Heifangtai terrace, China.” Eng. Geol. 278 (Aug): 105817. https://doi.org/10.1016/j.enggeo.2020.105817.
Xu, Q., Y. P. Zeng, J. P. Qian, and C. J. Wang. 2009. “An improved tangent angle and corresponding landslide warning criterion.” Geol. Bull. China 28 (4): 501–505. https://doi.org/10.3969/j.issn.1671-2552.2009.04.011.
Yan, Y., D.-S. Yang, D.-X. Geng, S. Hu, Z.-A. Wang, W. Hu, and S.-Y. Yin. 2019. “Disaster reduction stick equipment: A method for monitoring and early warning of pipeline-landslide hazards.” J. Mountain Sci. 16 (12): 2687–2700. https://doi.org/10.1007/s11629-019-5613-6.
Yang, J., M. Yue, X. Song, D. Shen, L. Chai, and W. Wang. 2020a. “Safety assessment of piping induced by crossing pipeline engineering.” Desalin. Water Treat. 187 (May): 47–55. https://doi.org/10.5004/dwt.2020.25282.
Yang, S., A. Jin, W. Nie, C. Liu, and Y. Li. 2022. “Research on SSA-LSTM-based slope monitoring and early warning model.” Sustainability 14 (16): 10246. https://doi.org/10.3390/su141610246.
Yang, Z., L. Wang, J. Qiao, T. Uchimural, and L. Wang. 2020b. “Application and verification of a multivariate real-time early warning method for rainfall-induced landslides: Implication for evolution of landslide-generated debris flows.” Landslides 17 (Oct): 2409–2419. https://doi.org/10.1007/s10346-020-01402-w.
Zhan, Q., S. Wang, F. Guo, Y. Chen, L. Wang, and D. Zhao. 2022. “Early warning model and model test verification of rainfall-induced shallow landslide.” Bull. Eng. Geol. Environ. 81 (8): 318. https://doi.org/10.1007/s10064-022-02827-4.
Zhang, L., M. Fang, X. Pang, X. Yan, and Y. Cao. 2018. “Mechanical behavior of pipelines subjecting to horizontal landslides using a new finite element model with equivalent boundary springs.” Thin-Walled Struct. 124 (Mar): 501–513. https://doi.org/10.1016/j.tws.2017.12.019.
Zhang, L., Y. Xie, X. Yan, and X. Yang. 2016. “An elastoplastic semi-analytical method to analyze the plastic mechanical behavior of buried pipelines under landslides considering operating loads.” J. Nat. Gas Sci. Eng. 28 (Jan): 121–131. https://doi.org/10.1016/j.jngse.2015.11.040.
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.” Energy 12 (6): 981. https://doi.org/10.3390/en12060981.
Zhou, S., Y. Liu, and J. Luo. 2013. “A cube based model for RFID coverage problem in three-dimensional space.” In Proc., 2013 IEEE 9th Int. Conf. on Mobile Ad-Hoc and Sensor Networks, 115–120. New York: IEEE.
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Journal of Pipeline Systems Engineering and Practice
Volume 15 • Issue 1 • February 2024
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© 2023 American Society of Civil Engineers.
History
Received: Jun 1, 2023
Accepted: Aug 14, 2023
Published online: Oct 14, 2023
Published in print: Feb 1, 2024
Discussion open until: Mar 14, 2024
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