Fuzzy modeling to define corrosivity potential in oil pipelines

Authors

DOI:

https://doi.org/10.31686/ijier.vol11.iss1.4063

Keywords:

Pipeline, Oil, Corrosion, Integrity, Fuzzy Logic

Abstract

In this work, a Fuzzy logic model was developed using the Fuzzy Logic Toolbox™ of the MATLAB® software, for monitoring the corrosivity potential in oil pipelines whose corrosion mechanism is predominantly by microbiological action. With the use of operational parameters, the model presents itself as an alternative to conventional monitoring methods, allowing to infer the corrosion rate in the pipeline, and therefore, the corrosivity potential. The model was applied to an oil pipeline and its results were compared with conventional monitoring methods. The analysis of the results concluded that the model can be used as a monitoring method for pipelines with those predominant corrosion mechanisms, helping to manage the integrity of oil pipelines.

Downloads

Download data is not yet available.

Author Biographies

  • Ivair Rafael Costa do Santos, Instituto Federal do Amazonas

    Academic, of the Post Graduate Program in Engineering, Process Management, Systems and
    Environmental (PGP.EPMSE) - Institute of Technology and Education Galileo of the Amazon

    Professor, Federal Institute of Amazon (IFAM).

  • Manoel Henrique Reis Nascimento, ITEGAM

    Professor, of the Post Graduate Program in Engineering, Process Management, Systems and
    Environmental (PGP.EPMSE) - Institute of Technology and Education Galileo of the Amazon

  • David Barbosa de Alencar, ITEGAM

    Professor, of the Postgraduate Program in Engineering, Process Management, Systems and

    Environmental (PGP.EPMSE) - Institute of Technology and Education Galileo of the Amazon

  • Manoel S. Santos Azevedo, University of the Amazon

    Professor, State University of Amazon (UEA).

  • Antonio Estanislau Sanches, University of the Amazon

    Professor

References

Alamri, A.H. Localized corrosion and mitigation approach of steel materials used in oil and gas pipelines – An overview. Journal Engineering Failure Analysis. 116, 104735, oct 2020. DOI: 10.1016/j.engfailanal.2020.104735. Disponível em: https://doi.org/10.1016/j.engfailanal.2020.104735. DOI: https://doi.org/10.1016/j.engfailanal.2020.104735

Askari, M.; Aliofhkazraei, M.; Afroukhteh, S. A comprehensive review on internal corrosion and cracking of oil and gas pipelines. Journal of Natural Gas Science and Engineering. 71, 102971, nov 2019. DOI 10.1016/j.jngse.2019.102971. Disponível em https://doi.org/10.1016/j.jngse.2019.102971. DOI: https://doi.org/10.1016/j.jngse.2019.102971

Badida, P.; Balasubramaniam, Y.; Jayaprakash, J. Risk Evaluation of oil and natural gas pipelines due to natural hazards using fuzzy fault tree analysis. Journal of Natural Gas Science and Engineering. 66, p.284-292, jun 2019. DOI 10.1016/j.jngse.2019.04.010. Disponível em http://dx.doi.org/10.1016/j.jngse.2019.04.010. DOI: https://doi.org/10.1016/j.jngse.2019.04.010

Biezma, V.M.; Agudo, D.; Barro, N, G. A fuzzy logic method: Predicting pipeline external corrosion rate. International. Journal of Pressure Vessels and Piping. 163, p.55-62, jun 2018. DOI 10.1016/j.ijpvp.2018.05.001. Disponível em https://doi.org/10.1016/j.ijpvp.2018.05.001. DOI: https://doi.org/10.1016/j.ijpvp.2018.05.001

Cox, W. A Strategic Approach to Corrosion Monitoring and Corrosion Management. Journal Procedia Engineering. 86, p. 567-574, nov 2014.. DOI: 10.1016/j.proeng.2014.11.082. Disponível em http://dx.doi.org/10.1016/j.proeng.2014.11.082. DOI: https://doi.org/10.1016/j.proeng.2014.11.082

Da Silva, A. A. R. Evaluation of corrosion in pipelines by gravimetric technique and electrical resistance. 2011.93 P. Dissertation (Master in Petroleum Science and Engineering) – Center for Exact and Earth Sciences (CCET), Federal University of Rio Grande do Norte, Natal, 2011.

Da Silva, A. B. Evaluation of corrosion inhibitors for carbon steel in high salinity environments containing CO2. 2013. 89p.Thesis (Doctorate in Metallurgical and Materials Engineering) – Alberto Luiz Coimbra Institute (COPPE) – Federal University of Rio de Janeiro, Rio de Janeiro, 2013.

Dawuda, A-W.; Berrouane-Taleb, M.; Khan, F. A probabilistic model to estimate microbiologically influenced corrosion rate. Process Safety and Environmental Protection. 148, p.908-926, february 2021. DOI 10.1016/j.psep.2021.02.006. Disponível em https://doi.org/10.1016/j.psep.2021.02.006 DOI: https://doi.org/10.1016/j.psep.2021.02.006

Jamshidi, A.; Yasdani, A.; Yakhchali, S.; Khaleghi, S. Developing new fuzzy inference system for pipeline risk assessment. Journal of Loss Prevention in the Process Industries. 26, p.197-208, oct 2013. DOI /10.1016/j.jlp.2012.10.010. Disponível em http://dx.doi.org/10.1016/j.jlp.2012.10.010 DOI: https://doi.org/10.1016/j.jlp.2012.10.010

Khan, F; Yarveisy, R.; Abbassi, R. Risk-based pipeline integrity management: A road map for the resilient pipelines. Journal of Pipeline Science and Engineering. p.74-87, feb 2021. DOI /10.1016/j.jpse.2021.02.001. Disponível em http://dx.doi.org/10.1016/j.jpse.2021.02.001 DOI: https://doi.org/10.1016/j.jpse.2021.02.001

Kraidi, L.; Shah, R.; Matipa, W.; Borthwick, F. Using stakeholder´s judgement and fuzzy logic theory to analyze the risk influencing factors in oil and gas pipelines projects: Case study in Iraq, stage II. International Journal of Critical Infrastructure protection. 28, 100337, mar 2020. DOI 10.1016/j.ijcip.2020.100337. Disponível em http://dx.doi.org/10.1016/j.ijcip.2020.100337 DOI: https://doi.org/10.1016/j.ijcip.2020.100337

Li, K.; He, L.; Zeng, Y.; Luo, J-L. Influence of H2S on the general corrosion and sulfide stress cracking of pipelines steels for supercritical CO2 transportation. Journal Corrosion Science. 190, 109639, sep 2021. DOI 10.1016/j.corsci.2021.109639. Disponível em https://doi.org/10.1016/j.corsci.2021.109639 DOI: https://doi.org/10.1016/j.corsci.2021.109639

Li, X.; He, L.; Luo, X.; Liu, H.; He, S.; Li, Q. Transient pigging dynamics in gas pipelines: Models, experiments, and simulations. Journal Ocean Engineering. 232, 109126, may 2021. DOI 10.1016/j.oceaneng.2021.109126. Disponível em https://doi.org/10.1016/j.oceaneng.2021.109126 DOI: https://doi.org/10.1016/j.oceaneng.2021.109126

Magalhães, A. A., Pimenta, G. S. Corrosive Process Monitoring and Control Techniques Course, Rio de Janeiro, Handout, 2005.

Mamdani, E. H. Applications of fuzzy algorithms for control of simple dynamic plant. Proc. Iee. v. 121, p. 1585-1588, 1974. DOI: https://doi.org/10.1049/piee.1974.0328

NACE - National Association Corrosion Engineers International - SP0775-2018: Preparation, Installation, Analysis, and Interpretation of Corrosion Coupons in Oilfield Operations. Texas: NACE, 2018. 20p.

Nogueira, E.L. Fuzzy inference model for evaluating the SWOT analysis as a support in organizational decision making. 2021. 77p. Dissertation (Master in Process Engineering) - Graduate Program in Process Engineering, Institute of Technology, Federal University of Pará, Belém, 2021. Available at: http://repositorio.ufpa.br/jspui/handle/2011 /13583.

Olvera-Martínez, M. E.; Mendoza-Flores, J.; Genesca, J.; CO2 corrosion control in steel pipelines. Influence of turbulent flow on the performance of corrosion inhibitors. Journal of Loss Prevention in the Process Industries. 35, p. 19-28, october 2019. DOI 10.1016/j.jlp.2015.03.006. Disponível em http://dx.doi.org/10.1016/j.jlp.2015.03.006 DOI: https://doi.org/10.1016/j.jlp.2015.03.006

PETROBRAS – Petróleo Brasileiro - N-2785-2018: Monitoring, Interpretation and Control of Internal Corrosion in Pipelines. Rev. C. Rio de Janeiro. PETROBRAS, 2018, 75p.

RTDT – Technical Regulation of Onshore Pipelines for Handling Oil, By-products and Natural Gas. National Agency for Petroleum, Natural Gas and Fuel (ANP).

Seghier, M. E. A.B.; Höche, D.; Zheludkevich, M. Prediction of the internal corrosion rate for oil and gas pipeline: Implementation of ensemble learning techniques. Journal of Natural Gas Science and Engineering. 99, 104425, mar 2022. DOI 10.1016/j.jngse.2022.104425. Disponível em http://dx.doi.org/10.1016/j.jngse.2022.104425. DOI: https://doi.org/10.1016/j.jngse.2022.104425

Silva, C.R.P. Fuzzy logic: a perspective for evaluations. 2018. 69p. Dissertation (Professional Master's Degree in Mathematics in National Network - PROFMAT) – Federal University of Alagoas, Maceio, 2018.

Silveira, C.J.G.; Souza, A.M.P.; Akamine, R.N.; Evaluation of microbiological corrosion of the Orsol I pipeline. 16, p. Rio de Janeiro, Research and Development Center Leopoldo A. Miguez de Mello - CENPES, 2016 (CT BIO 003/2016).

Silveira, C.J.G.; Akamine, R.N.; Evaluation of microbiological corrosion of the Orsol I pipeline – Part III. 20, p. Rio de Janeiro, Leopoldo A. Miguez de Mello Research and Development Center - CENPES, 2016 (CT BIO 007/2017).

Sluce, P. Risk assessment proposal in hydraulic presses with fuzzy logic. 2021. 46p. Dissertation (Professional Master's Degree in Process Engineering) – Graduate Program in Process Engineering, Institute of Technology - Federal University of Pará, Belém, 2021.

Singh, M.; Pokhrel, M. A Fuzzy Logic-Possibilistic Methodology for Risk-Based Inspection (RBI) Planning of Oil and Gas Piping Subjected to Microbiologically Influenced Corrosion (MIC). International Journal of Pressure Vessels and Piping.159, p.45-54, jan 2018. DOI: 10.1016/j.ijpvp.2017.11.005. Disponível em http://dx.doi.org/10.1016/ j.ijpvp.2017.11.005. DOI: https://doi.org/10.1016/j.ijpvp.2017.11.005

Wang, Z.; Zhou, Z.; Xu, W. Lyu, W.; Yang, L.; Zhang,B.; Li,Y. Study on inner corrosion behavior of high strength product oil pipelines. Journal Engineering Failure Analysis. 115, 104659, jun 2020. DOI: 10.1016/j.engfailanal.2020.104659. Disponível em: https://doi.org/10.1016/j.engfailanal.2020.104659 DOI: https://doi.org/10.1016/j.engfailanal.2020.104659

Wasim, M.; Djukic, M. B. External corrosion of oil and gas pipelines: A review of failure mechanisms and predictive preventions. Journal of Natural Gas Science and Engineering. 100, 104467, apr 2022. DOI 10.1016/j.jngse.2022.104467. Disponível em http://dx.doi.org/10.1016/j.jngse.2022.104467. DOI: https://doi.org/10.1016/j.jngse.2022.104467

Wei, B.; Xu, J.; Sun, C.; Cheng, Y.F. Internal microbiologically influenced corrosion of natural gas pipelines: A critical review. Journal of Natural Gas Science and Engineering. 26, p.197-208, jun 2022. DOI 10.1016/j.jngse.2022.104581. Disponível em https://doi.org/10.1016/j.jngse.2022.104581 DOI: https://doi.org/10.1016/j.jngse.2022.104581

Zhou, Q.; Wu, W.; Liu, D.; Li, K.; Qiao, Q. Estimation of corrosion failure likelihood of oil and gas pipeline based on fuzzy logic approach. Engineering Failure Analysis. 70, p.48-55, dec 2016. DOI 10.1016/j.engfailanal.2016.07.014. Disponível em http://dx.doi.org/10.1016/j.engfailanal.2016.07.014 DOI: https://doi.org/10.1016/j.engfailanal.2016.07.014

Downloads

Published

2023-01-01

How to Cite

Santos, I. R. C. do, Nascimento, M. H. R., Alencar, D. B. de, Azevedo, M. S. S., & Sanches, A. E. (2023). Fuzzy modeling to define corrosivity potential in oil pipelines. International Journal for Innovation Education and Research, 11(1), 129-146. https://doi.org/10.31686/ijier.vol11.iss1.4063
Received 2022-11-27
Accepted 2022-12-16
Published 2023-01-01

Most read articles by the same author(s)

1 2 3 > >>