Probabilistic and Statistical Techniques to Study the Impact of Localized Corrosion Defects in Oil and Gas Pipelines: A Review

Corrosion is a major cause of the loss of hermeticity in oil and gas pipelines. Corrosion defects affect the remaining life of in-service pipelines and can lead to failures, ruptures, hydrocarbon leakage, product loss, interruptions, environmental damage, economic losses, or, in the worst cases, fatalities. The existence of localized corrosion defects is a significant issue in pipeline integrity analysis, mainly because these structures are commonly buried and cover large extensions, amounting to hundreds or even thousands of miles; thus, it is difficult to size and locate all minor but possibly deep defects. Consequently, probabilistic and statistical modeling methods have been widely used to assess the integrity of corroded pipelines. Statistical modeling methods used to estimate the remaining life of the pipeline have focused on three main aspects: applications to estimate the defect depths and rates of corrosion, Bayesian applications in pipeline integrity to update the probability distribution for corrosion defects (depth, length, and spatial distribution), and pipeline reliability estimations. This paper reviews several methods proposed in the literature for these issues as well as their applications in real life. In addition, some of the present and future challenges related to preventing corrosion in the oil and gas pipeline industry are described.

Corrosion-Fatigue Evaluation of Uncoated Weathering Steel Bridges

Uncoated weathering steel (UWS) bridges have been extensively used to reduce the lifecycle cost since they are maintenance-free and eco-friendly. However, the fatigue issue becomes significant in UWS bridges due to the intended corrosion process utilized to form the corrodent-proof rust layer instead of the coating process. In this paper, an innovative model is proposed to simulate the corrosion-fatigue (C-F) process in UWS bridges. Generally, the C-F process could be considered as two relatively independent stages in a time series, including the pitting process of flaw-initiation and the fatigue crack propagation of the critical pitting flaw. In the proposed C-F model, Faraday’s law has been employed at the critical flaw-initiation stage to describe the pitting process, in which the pitting current is applied to reflect the pitting rate in different corrosive environments. At the crack propagation stage, the influence of pitting corrosion is so small that it can be safely ignored. In simulating the crack propagation stage, the advanced NASGRO equation proposed by the NASA is employed instead of the classic Paris’ law, in which a modified fatigue limit is adopted. The fatigue limit is then used to determine the critical size of pitting flaws, above which the fatigue effect joins as a parallel driving force in crack propagation. The model is then validated through the experimental data from published articles at the initiation stage as well as the whole C-F process. Two types of structural steel, i.e., HPS 70W and 14MnNbq steel, have been selected to carry out a case study. The result shows that the C-F life can be notably prolonged in the HPS 70W due to the enhancement in fatigue strength and corrosion resistance. Besides, a sensitivity analysis has been made on the crucial parameters, including the stress range, stress ratio, corrosive environment and average daily truck traffic (ADTT). The result has revealed the different influence of the above parameters on the initiation life and propagation life.