Efficient qualitative risk assessment of pipelines using relative risk score based on machine learning

Abstract

Pipelines are observed one of the economic modes of transport for transporting oil, gas, and water between various locations. Most of the countries in the world transport petroleum and other flammable products through underground pipelines. The underground and aboveground pipelines are facing various damages due to corrosion, dents, and ruptures due to the environment and operational fluid conditions. The danger of leaks and accidents increases as a result of these damages. Pipelines must be evaluated on a regular basis to make sure they are fit for transmission. By evaluating the effects of damages and the possibility of catastrophic failures using a variety of techniques, pipeline integrity is controlled. Applying the relative risk scoring (RRS) technique, pipeline failures are predicted. One of the probabilistic techniques used to forecast risk based on an impartial assessment is machine learning. With different parameters like corrosion, leakage, materials, atmosphere, surface, earth-movements, above-ground and underground facilities, etc., the RRS method provides an accuracy of 97.5% in identifying the risk and gives a precise classification of risk, whether the pipeline has a high, medium, or low risk without any delay on the prediction compared with Naive Bayes, decision tree, support vector machine, and graph convolutional network.

Towards Resilient Pipeline Infrastructure: Lessons Learned from Failure Analysis

“…Pipelines are recognised as the most cost-effective and reliable solution for energy transportation, playing a critical role in gas conveyance, especially within modern societies and in response to the escalating global demand for natural gas resources (Liao et al, 2022, Zhou et al, 2022Vanitha et al, 2023). Even though being characterized by a relatively low probability of operational failures in comparison with alternative transportation methods (Peng et al, 2009;Oliveira, 2018, Seghier et al, 2022Vandrangi et al, 2022), pipelines are complex systems carrying hazardous materials, subjected to several deterioration mechanisms, often operated by human beings, making them prone to catastrophic incidents (Abassi et al, 2022).…”