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research-article

SAFETY OF PIPELINES SUBJECTED TO DETERIORATION PROCESSES MODELLED THROUGH DYNAMIC BAYESIAN NETWORKS

[+] Author and Article Information
Oscar Palencia

Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, nº 1, 1049-001 Lisboa, Portugal
oscar.palencia@centec.tecnico.ulisboa.pt

Angelo Teixeira

Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, nº 1, 1049-001 Lisboa, Portugal
teixeira@centec.tecnico.ulisboa.pt

Carlos Guedes Soares

Fellow ASME, Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, nº 1, 1049-001 Lisboa, Portugal, Also, Subsea Technology Laboratory, Ocean Engineering Department, COPPE, Federal University of Rio de Janeiro, Brazil
c.guedes.soares@centec.tecnico.ulisboa.pt

1Corresponding author.

ASME doi:10.1115/1.4040573 History: Received July 22, 2017; Revised June 16, 2018

Abstract

The paper studies the application of Dynamic Bayesian Networks for modelling degradation processes in oil and gas pipelines. A Dynamic Bayesian Network tool consisting of a MATLAB code has been developed for performing inference on models. The tool is then applied for probabilistic modelling of the burst pressure of a pipe subjected to corrosion degradation and for safety assessment. The burst pressure is evaluated using the ASME B31G design method and other empirical formulas. A model for corrosion prediction in pipelines and its governing parameters are explicitly included into the probabilistic framework. Different sets of simulated corrosion measurements are used to increase the accuracy of the model predictions. Several parametric studies are conducted to investigate how changes in the observed corrosion (depth and length) and in the frequency of inspections affect the pipe reliability.

Copyright (c) 2018 by ASME
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