Estimation of Internal Pit Depth Growth and Reliability of Aged Oil and Gas Pipelines— A Monte Carlo Simulation Approach

Abstract

To estimate the internal pit depth growth and reliability of aged oil and gas pipelines, a Monte Carlo simulation approach was adopted. The average maximum pit depths of corroded pipelines were correlated with the operating parameterstemperature, CO 2 partial pressure, pH, flow rate, sulfate ion concentration, chloride ion concentration, water cut, and wall shear stress via a multivariate regression analysis. Poisson square wave model was used to predict the time lapse of the pit depth growth using the statistical best fit of the maximum pit depth and operating parameters as boundary conditions. Weibull probability function was used to determine the failure intensity and survivability of the pipelines for different distribution types, whereas inspection data from a magnetic flux leakage in-line inspected transmission pipeline were used to test the application of the model. The future pit depth distribution, survivability, and failure rate of this transmission pipeline were also determined, with the result showing that the model is vital for future internal pit depth growth and reliability estimation from single field inspection data.

Finite Element Modelling and Retained Life Estimation of Corroded Pipelines in Consideration of Burst Pressures—A Fractural Mechanics Approach

“…It is evident from the information in Figure 8 that the burst pressure retention ratio (Rr) of the pipes reduced with the increase in d/t, which is similar to the findings of other researchers [5][6][7][8][9]. This scenario was necessitated by the increasing corrosion defect depth, which generally results in increased stress concentration on pipelines [18][19][20]. For a given L/D and L/√Dt (Figures 9 and 10 It is evident from the information in Figure 8 that the burst pressure retention ratio (R r ) of the pipes reduced with the increase in d/t, which is similar to the findings of other researchers [5][6][7][8][9].…”

“…For a given L/D and L/√Dt (Figures 9 and 10 It is evident from the information in Figure 8 that the burst pressure retention ratio (R r ) of the pipes reduced with the increase in d/t, which is similar to the findings of other researchers [5][6][7][8][9]. This scenario was necessitated by the increasing corrosion defect depth, which generally results in increased stress concentration on pipelines [18][19][20]. For a given L/D and L/ √ Dt (Figures 9 and 10), the retention ratios were fairly steady at each d/t as the L/D and L/ √ Dt values increased.…”

“…between 0.21 mm/year to 0.38 mm/year, it is said to be undergoing a high corrosion rate, while a growth rate that is above 0.38 mm/year is classified as severe corrosion [21]. If the corrosion defect depth d(t) at time t of a corroded pipeline follows a power model [16][17][18] according to Equation [13], the time of initiation of the corrosion defects (tini) for different corrosion categories are low corrosion (tini = 1.56 years), mild corrosion (tini = 0.58 years), high corrosion (tini = 1.03 years) and severe corrosion (tini = 1.89 years) [22]. In this case, the burst pressure at different lifecycle durations and various corrosion categories can be computed with Equations (12a,b).…”

Stochastic modelling of perfect inspection and repair actions for leak–failure prone internal corroded pipelines

“…This is the trend expected from ageing assets, which have the survivability rates reduced with increasing age. Imperatively, the more a pipeline is exposed to corrosion, the more the probability of failure, despite the fact that the corrosion rates may be higher at initial exposure times and slower towards the terminal end of the corrosion wastage cycle of the pipeline [52,55]. Figure 7 shows the failure probabilities of the pipeline with time lapse of exposure to the corrosive environment.…”

A failure prediction model for corrosion in gas transmission pipelines

“…Similarly, Kucheryavyi and Mil’kov 22 performed reliability assessment towards corrosion failure in a defective gas pipeline based on mechanical equations on pipeline strength. Through application of a Monte Carlo simulation and principals of reliability analysis, Teixeira et al 23 and Ossai et al 24 proposed two methodologies to assess reliability of oil and gas pipelines. Teixeira et al 23 performed a first-order reliability analysis on burst pressure results from numerical and experimental analysis.…”