The paper presents a probabilistic-based methodology for the assessment of a pipeline containing internal corrosion defects. Two different models have been used to predict the future CO2 corrosion rates namely a linear growth and the deWaard-Milliams models. A probabilistic approach is used to analyse the behaviour of corrosion data obtained from in-line intelligent (ILI) pigging inspections. The outcomes are parameters represented by their corresponding statistical distribution. Due to the availability of these statistical parameters, a Monte Carlo simulation is used to calculate the probability of failure of the pipeline due to bursting failure. The existence of corrosion may reduce the maximum capacity of the pipe, as such causing leakage and bursting when the operational pressure supersedes its threshold. From the analysis of the result, failure probability based on theoretical linear growth model exhibit slightly longer lifetime of the pipeline with three years interval compared to deWaard-Milliams model. This is due to higher mean value of corrosion growth rate estimated using the empirical deWaard-Milliams model. Both results are very useful in prolonging the lifetime of pipelines by having knowledge of the past to schedule the future maintenance work.

Prediction of co2 corrosion growth in submarine pipelines

Statistical and probabilistic methods are now recognized as a proper method to address the degree of randomness and complexity of the corrosion process. Nevertheless, the inclusion of this approach within corrosion model development is still rarely practiced in the structure assessment. This has led to the tendency by engineers and inspection personnel to use much simpler approaches in the assessment of corrosion progress. For example, the use of the linear model to predict the future growth of corrosion defects is widely practised despite its questionable accuracy. This work develops several corrosionrelated models based on actual metal loss data with objectives to improve the data interpretation as well as prediction of future defect growth. Although this work deals specifically with data from oil pipelines and vesselâ€™s ballast tanks, the models has been designed to be generic, with no restriction on the types of structure or inspection tool. The procedure consists of three stages: data sampling, data analysis and probabilistic-based prediction. A statistical approach has been applied to model the corrosion parameters as a probability distribution. The issues raised by the presence of negative growth rate and unknown corrosion initiation time have been addressed by the development of new correction methods and a new data sampling technique. The research also demonstrates how the simple linear model can be modified to account for errors arising from the randomness of corrosion growth data and the variation in measured growth for severe defects. A proposed development of the linear-based model has been extensively used in the simulation programme. New data sampling techniques, data correction approaches, and alternative linear models have been developed to improve the assessment work on corrosion data. To conclude, this research was able to demonstrate how inspection data can be more fully utilised to optimise the application of information of corrosion progress to structural analysis.

Statistical modelling of corrosion growth in marine environment

In this paper, the development of a novel omni-directional inspection robot is presented, which is capable of delivering NDT sensors to surfaces on straight pipe, pipe bends and branch connections, overcoming the limitation that a test area over a pipe bend or past a branch or other obstruction raise. The lightweight crawler is attached on the outside of the pipe to the thin metal strip that holds the insulation in place without deforming the insulation through the application of a force controlled clamping mechanism while performing longitudinal, circumferential and arbitrary movements. In order to be able to cope with a range of pipe, materials and coverings, to allow for future modifications and to be able to incorporate a wide range of NDT inspection equipment, a modular approach was considered for the design of the mobile robot. Either two different inspection sensors may be mechanically incorporated into the chassis of the crawler and deployed at the same time or just a double-sided acting sensor (e.g. X-Ray).

On the Development of a Modular External-pipe Crawling Omni-directional Mobile Robot.

On the development of a modular external‐pipe crawling omni‐directional mobile robot

Risk Assessment is an extremely useful tool in providing a framework in which to identify the possible hazards and evaluate the risks associated with all crude oil pipelines By using index method and multivariable analysis, a methodology of the threat and risk of crude oil pipelines to environment are presented General concepts are introduced and explained in detail Principles of the methodology, the specific equations, and data required to prepare a risk analysis for environmental risk and failure analysis are discussed and explained, and an example is presented to illustrate the method

/pdf/quantitative-risk-assessment-for-crude-oil-pipelines-53e0x6uipt.pdf

Quantitative Risk Assessment for Crude Oil Pipelines

This report is the latest in a series of annual reports issued by CONCAWE reviewing the performance of cross-country oil pipeline network of 30,860 km and the reported spillage incidents are analyzed by cause and the effectiveness of clean-up is recorded.

Performance of cross-country oil pipelines in western europe: statistical summary of reported spillages, 1995

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Performance of cross-country oil pipelines in western europe: statistical summary of reported spillages, 1995