Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

Corrosion inhibitors for ferrous and non-ferrous metals and alloys in ionic sodium chloride solutions: A review

https://hal.archives-ouvertes.fr/hal-01988082/document

Reliability assessments of corroded pipelines based on internal pressure – A review

https://repository.tudelft.nl/islandora/object/uuid%3A6d5454df-83c6-497a-b6d7-b44d293eb224/datastream/OBJ/download

Safety and security of oil and gas pipeline transportation : A systematic analysis of research trends and future needs using WoS

Corrosion induced failure analysis of subsea pipelines

Failure of Leak Detection System (LDS) to detect pipeline leakages or ruptures may result in drastic consequences that could lead to excessive financial losses. To minimize the occurrence of such failure, the functionality of the LDS and the integrity of the pipeline should be assessed on a priority basis. This paper presents an integrated risk-based assessment scheme to predict the failure and the failure consequences of offshore crude oil pipelines. To estimate risk, two important quantities have to be determined, the joint probability of failure of the pipeline and its LDS and the consequences of failure. Consequences incorporate the financial losses associated with environmental damage, oil spill cleanup and lost production. The assessment provides an estimate of the risk in monetary value and determines whether the estimated risk exceeds a predefined target risk. Moreover, the critical year for the asset can be determined. In essence, the outcome of the assessment facilitates an informed decision-making about the future of the asset.

Risk assessment of offshore crude oil pipeline failure

Purpose – The purpose of this paper is to develop a risk‐based integrity model for the optimal replacement of offshore process components, based on the likelihood and consequence of failure arising from time‐dependent degradation mechanisms.Design/methodology/approach – Risk is a combination of the probability of failure and its likely consequences. Offshore process component degradation mechanisms are modeled using Bayesian prior‐posterior analysis. The failure consequences are developed in terms of the cost incurred as a result of failure, inspection and maintenance. By combining the cumulative posterior probability of failure and the equivalent cost of degradations, the operational life‐risk curve is produced. The optimal replacement strategy is obtained as the global minimum of the operational risk curve.Findings – The offshore process component degradation mechanisms are random processes. The proposed risk‐based integrity model can be used to model these processes effectively to obtain an optimal rep...

Risk based integrity modeling of offshore process components suffering stochastic degradation

The deterioration of the condition of process plants assets has a major negative impact on the safety of its operation. Risk based integrity modeling provides a methodology to quantify the risks posed by an aging asset. This provides a means for the protection of human life, financial investment and the environmental damage from the consequences of its failures. This methodology is based on modeling the uncertainty in material degradations using probability distributions, known as priors. Using Bayes theorem, one may improve the prior distribution to obtain a posterior distribution using actual inspection data. Although the choice of priors is often subjective, a rational consensus can be achieved by judgmental studies and analyzing the generic data from the same or similar installations. The first part of this paper presents a framework for a risk based integrity modeling. This includes a methodology to select the prior distributions for the various types of corrosion degradation mechanisms, namely, the uniform, localized and erosion corrosion. Several statistical tests were conducted based on the data extracted from the literature to check which of the prior distributions follows data the best. Once the underlying distribution has been confirmed, one can estimate the parameters of the distributions. In the second part, the selected priors are tested and validated using actual plant inspection data obtained from existing assets in operation. It is found that uniform corrosion can be best described using 3P-Weibull and 3P-Lognormal distributions. Localized corrosion can be best described using Type1 extreme value and 3P-Weibull, while erosion corrosion can best be described using the 3P-Weibull, Type1 extreme value, or 3P-Lognormal distributions.

Premkumar Thodi

Papers

Corrosion induced failure analysis of subsea pipelines

Risk assessment of offshore crude oil pipeline failure

Risk based integrity modeling of offshore process components suffering stochastic degradation

The selection of corrosion prior distributions for risk based integrity modeling

Revised burst model for pipeline integrity assessment