Abstract—Long distance oil and gas pipelines are the major
transporters of crude oil and other petroleum products which
are highly expensive and earning millions of dollars’ income.
Considered that they are the secure way of transporting those
products pipelines fail leaving catastrophic consequences
behind. The aim of this study was to build a fuzzy-based model
to forecast the type of failure in the future utilizing the
historical data of the pipeline records. This paper presents the
fuzzy risk analysis method proposed which is the IS appraisal,
the LIF evaluation, and the risk analysis. Fuzzy model showed
that all inputs and factors have significant influence on the
output results. Results obtained using this model exhibits more
accurate prediction compared to other methods.
Index Terms—Oil and gas, pipelines, failure rate prediction,
fuzzy logic.
Tahyr Garlyyev and Srinivasa Rao Pedapati are with the Dept. of
Mechanical Engineering, Universiti Teknologi PETRONAS, 32610, Perak,
Malaysia (e-mail: tahyrgarlyyev@gmail.com,
srnivasa.pedapati@utp.edu.my).
K. Venkateswara Rao is with Petroleum and Chemical Engineering
Department, University College of Engineering, JNTUK, Kakinada, India
(e-mail: profkvrao@gmail.com).
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Cite: Tahyr Garlyyev, Srinivasa Rao Pedapati, and K. Venkateswara Rao, "Prediction of Failure Rate in Long Distance Oil and Gas Pipelines Using Soft Computing Techniques," International Journal of Chemical Engineering
and Applications vol. 11, no. 1, pp. 42-47, 2020.
