Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model

Li, Shuxin; Yu, Shurong; Zeng, Hai-Long; Li, Jianhua; Liang, Rui

doi:10.1016/j.petrol.2008.12.023

Cited by 110 publications

(34 citation statements)

References 14 publications

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“…This observation is also supported by Li et al [2]. They pointed out that Shell 92 has most conservative output and thus it is desirable for long term prediction.…”

Section: Related Researchessupporting

confidence: 70%

“…Approaches to those works can be broadly classified into deterministic and probabilistic ones. However, a recent attention is focused on the probabilistic approach because it provides more practical results as pointed out by Li et al [2]. The probabilistic approach to reliability assessment includes some moment-based methods such as first order second moment (FOSM), first order reliability method (FORM), and second order reliability method (SORM) [3].…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

Kim¹,

Choe²,

Kim³

et al. 2016

Journal of Korean Institute of Intelligent Systems

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Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.

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“…This observation is also supported by Li et al [2]. They pointed out that Shell 92 has most conservative output and thus it is desirable for long term prediction.…”

Section: Related Researchessupporting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

Kim¹,

Choe²,

Kim³

et al. 2016

Journal of Korean Institute of Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…(1) The safety margin domain is defined by G(X j ) > 0 and the failure domain is attributed to G(X j ) < 0, where X j are the random variables in the system [3][4][5][6][7][8][9][10]. The assessment of the reliability of the pipeline is summarized to evaluation of the reliability index β.…”

Section: Limit State Functionmentioning

confidence: 99%

Reliability of the High Strength Pipeline Steel under Corrosion Defect

et al. 2017

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The demand of energy based on hydrocarbons, such as gas and oil, requires construction of more and more new pipelines. Therefore, the assessment of the remaining life of these pipeline structures became increasingly important to ensure the continuity of production and distribution operations. The reliability of these industrial facilities is largely conditioned by specific characteristics of each system, by its conditions of use and its environment. Generally, the causes of deterioration of hydrocarbon transportation pipelines are related to the presence of apparent defects (pinholes, cracks, corrosion, etc). This study is aimed to estimate the reliability of pipeline structures. The B31G mechanical model of degradation was used to assess the probability of failure through dimensions of defects.

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“…If the deterministic corroded pit growth in this work is assumed to follow a linear random model which have been used by researchers to model different kinds of physical systems including pipelines deterioration [26,[35][36][37][38], then the progression of the deterministic pit depth ( ( )) will be of the form shown in Equation (23).…”

Section: Figure 2: Graphical Representation Of Chapman-kolmogorov Equmentioning

confidence: 99%

“…A multivariate regression analysis of the simulated data was used to obtain the regression coefficients of the operating variables and the intercept whereas the mean values of the operating parameters computed from the simulation result were used for the computation of the pitting rates of the corrosion categories according to Equation (36).…”

Section: Startmentioning

confidence: 99%

Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

Ossai

Boswell

Davies

2016

Engineering Failure Analysis

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A continuous time non-homogenous linear growth pure birth Markov model was used to predict the future pit depth distribution of internally corroded oil and gas pipelines. A negative binomial distribution was used for calculating the transition probability functions of the pit depths whilst pit depths growth was estimated for low, moderate, high and severe pitting corrosion rates using field measured data of pit depths, temperatures, CO2 partial pressures, pH and flow rates. The Markov predicted results agreed well with field measured pit depth data from X52 grade pipeline and L-80 and N-80 grades offshore well tubing.

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Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model

Cited by 110 publications

References 14 publications

A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

Reliability of the High Strength Pipeline Steel under Corrosion Defect

Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

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