iipp publishingJournal of Applied Engineering Science

ASSESSMENT OF ANTHROPOGENIC FACTOR OF ACCIDENT RISK ON THE MAIN OIL PIPELINE PASCUALES – CUENCA IN ECUADOR


DOI: 10.5937/jaes16-17019
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions. 
Creative Commons License

Volume 16 article 533 pages: 307 - 312

Johnny Robinson Zambrano Carranza
Escuela Politécnica Nacional, Ladron de Guevara E11-253, Quito 01172759, Ecuador

Stanislav Kovshov
Saint Petersburg Mining University, 21st Line, St Petersburg 199106, Russia

Evgeniy Lyubin
Saint Petersburg Mining University, 21st Line, St Petersburg 199106, Russia


The pipeline infrastructure of Latin America countries, including the Republic of Ecuador, has a significant accident potential. Accidence rate is facilitated by the diversity of natural and climatic conditions in the region, military-political instability in its separate parts, and imperfection of the standards for the production of pipes and equipment.The technical condition of the pipeline systems operated in Latin America for 15 – 20 years is imperfect. Depreciation or replacement of spent equipment and elements of the pipeline infrastructure is not being carried out at an adequate pace. Ecuador, for example, has a stable dynamics of increasing accidents at pipeline infrastructure facilities. Therefore, an assessment of the risk of the condition of the main pipelines should be carried out. Anthropogenic risk is one of the most important accident factors (50 % of all risk on main oil pipelines in Ecuador). To evaluate it, the methodology of Federal Safety Manual is proposed. The anthropogenic risk is calculated for 3 main sections of Pascuales – Cuenca pipeline, which supports with oil the provinces of Cañar, Loja, Zamora Chinchipe and Morona Santiago. For the foothill area, the specific probability of accidents is the most, and for the coastal and flat areas less and equals to 0.15 and 0.14, respectively. The performed accident analysis will allow taking the necessary measures to maintain the pipeline in working condition.
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The article was prepared with the grant support of the Academic Council of the Mining University on the basis of the results of the internship and scientific work at the National Polytechnic School of Ecuador.

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Kovshov, S. V., & Kovshov, V. P. (2014). Biogenic fixation of dusting surfaces. Life Science Journal, 11 (9), 401 – 404.

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Peng, X. Y., Yao, D. C., Liang, G. C., Yu, J. S., & He, S. (2016). Overall reliability analysis on oil/gas pipeline under typical third-party actions based on fragility theory. Journal of Natural Gas Science and Engineering, 34, 993-1003.

Performance of European cross-country oil pipelines. Statistical summary of reported spillages in 2015 and since 1971. Concawe, Brussels, 2017.

Podavalov, I.Yu. (2008). Analysis of methods of technogenic risk calculation in the operation of main gas pipelines. Journal of Mining Institute, Vol. 178, P. 82 – 85.

Proskuryakov, R.M., Dementev A.S (2016). The building a system of diagnosing the technical condition of the pipeline on the basis of continuous pulsed magnetic field. Journal of Mining Institute, Vol. 218, P. 215 – 219.

Shabarchin, O., & Tesfamariam, S. (2016). Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model. Journal of Loss Prevention in the Process Industries, 40, 479-495.

Urquidi-Macdonald, M., Tewari, A., & Ayala H, L. F. (2014). A neuro-fuzzy knowledge-based model for the risk assessment of microbiologically influenced corrosion in crude oil pipelines. Corrosion, 70(11), 1157-1166.

Vtorushina, A.N., Anishchenko, Y.V., Nikonova, E.D. (2017). Risk assessment of oil pipeline accidents in special climatic conditions. IOP Conf. Ser.: Earth Environ. Sci. 66 012006.

Bravo, E. (2007). Los impactos de la explotación petrolera en ecosistemas tropicales y la biodiversidad. Acción ecológica, Vol. 24 (1), P. 35-42.

Cheng, Y., & Akkar, S. (2017). Probabilistic permanent fault displacement hazard via Monte Carlo simulation and its consideration for the probabilistic risk assessment of buried continuous steel pipelines. Earthquake Engineering & Structural Dynamics, 46(4), 605-620.

El-Abbasy, M. S., Senouci, A., Zayed, T., & Mosleh, F. (2015). A condition assessment model for oil and gas pipelines using integrated simulation and analytic network process. Structure and Infrastructure Engineering, 11(3), 263-281.

Gharabagh, M. J., Asilian, H., Mortasavi, S. B., Mogaddam, A. Z., Hajizadeh, E., & Khavanin, A. (2009). Comprehensive risk assessment and management of petrochemical feed and product transportation pipelines. Journal of Loss Prevention in the Process Industries, 22(4), 533-539.

Guo Y., Meng X., Wang D., Meng T., Liu S., He R. (2016). Comprehensive risk evaluation of long-distance oil and gas transportation pipelines using a fuzzy Petri net model. Journal of Natural Gas Science & Engineering, Vol. 33, P. 18 – 29, doi: 10.1016/j.jngse.2016.04.052.

Hu, Y., Liu, K., Xu, D., Zhai, Z., & Liu, H. (2017, August). Risk Assessment of Long Distance Oil and Gas Pipeline Based on Grey Clustering. In Big Knowledge (ICBK), 2017 IEEE International Conference on (pp. 198-201). IEEE.

Kabir, G., Sadiq, R., & Tesfamariam, S. (2015). A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Structure and Infrastructure Engineering, 12(8), 874-889.

Kovshov, S. (2013). Biological ground recultivation and increase of soil fertility. International Journal of Ecology & Development, 25(2), 105-113.

Kovshov, S. V., Garkushev, A. U., & Sazykin, A. M. (2015). Biogenic technology for recultivation of lands contaminated due to rocket propellant spillage. Acta Astronautica, 109, 203-207.

Kovshov, S. V., & Kovshov, V. P. (2014). Biogenic fixation of dusting surfaces. Life Science Journal, 11 (9), 401 – 404.

Muhlbauer, W. K. (2004). Pipeline risk management manual: ideas, techniques, and resources. Elsevier.

Pashkevich M.A., Antciferova T.A. (2013). Risk assessment of anthropogenic impact of the fuel and energy complex. Journal of Mining Institute, Vol. 203, P. 225 – 228.

Peng, X. Y., Yao, D. C., Liang, G. C., Yu, J. S., & He, S. (2016). Overall reliability analysis on oil/gas pipeline under typical third-party actions based on fragility theory. Journal of Natural Gas Science and Engineering, 34, 993-1003.

Performance of European cross-country oil pipelines. Statistical summary of reported spillages in 2015 and since 1971. Concawe, Brussels, 2017.

Podavalov, I.Yu. (2008). Analysis of methods of technogenic risk calculation in the operation of main gas pipelines. Journal of Mining Institute, Vol. 178, P. 82 – 85.

Proskuryakov, R.M., Dementev A.S (2016). The building a system of diagnosing the technical condition of the pipeline on the basis of continuous pulsed magnetic field. Journal of Mining Institute, Vol. 218, P. 215 – 219.

Shabarchin, O., & Tesfamariam, S. (2016). Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model. Journal of Loss Prevention in the Process Industries, 40, 479-495.

Urquidi-Macdonald, M., Tewari, A., & Ayala H, L. F. (2014). A neuro-fuzzy knowledge-based model for the risk assessment of microbiologically influenced corrosion in crude oil pipelines. Corrosion, 70(11), 1157-1166.

Vtorushina, A.N., Anishchenko, Y.V., Nikonova, E.D. (2017). Risk assessment of oil pipeline accidents in special climatic conditions. IOP Conf. Ser.: Earth Environ. Sci. 66 012006.