High-resolution In-line Inspection Research Articles

Bayesian dynamic linear model for growth of corrosion defects on energy pipelines

This paper describes the use of the second-order polynomial dynamic linear model (DLM) to characterize the growth of the depth of corrosion defects on energy pipelines using data obtained from multiple high-resolution in-line inspections (ILI). The growth model incorporates the measurement error of the ILI tools and captures the temporal variability of the corrosion growth by allowing the artificially-constructed average growth rate between two successive inspections to vary with time. The Markov Chain Monte Carlo simulation is employed to carry out the Bayesian updating of the growth model and evaluate the posterior distributions of the model parameters. An example involving real ILI data collected from an in-service natural gas pipeline is employed to illustrate and validate the growth model. The analysis results show that the defect depths predicted by the proposed model agree well with the actual depths and are more accurate than those predicted by the Gamma process- and Inverse Gaussian process-based growth models reported in the literature.

System reliability of corroding pipelines considering stochastic process-based models for defect growth and internal pressure

A methodology is presented to evaluate the time-dependent system reliability of pressurized pipelines that contain multiple active metal-loss corrosion defects and have been subjected to at least one inline inspection (ILI). The methodology incorporates a homogeneous gamma process-based corrosion growth model and a Poisson square wave process-based internal pressure model, and separates three distinctive failure modes, namely small leak, large leak and rupture. The hierarchical Bayesian method and Markov Chain Monte Carlo (MCMC) simulation are employed to characterize the parameters in the corrosion growth model based on data obtained from high-resolution inline inspections (ILIs). An example involving an in-service gas pipeline is used to validate the developed corrosion growth model and illustrate the proposed methodology for the system reliability analysis. Results of the parametric analysis indicate that both the uncertainties in the parameters of the growth model as well as their correlations must be accounted for in the reliability analysis. The proposed methodology will facilitate the application of reliability-based pipeline corrosion management programs.