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

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 parameters-temperature, CO2 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.