Corrosion is one of the most significant threats for onshore pipelines that may lead to a Loss of Containment (LOC). A LOC poses significant consequences over the surrounding people and environment because of the hazardousness of the transporting fluids, so different efforts have been raised to predict pipe failures, which are commonly based on reliability assessments with limit state functions. These functions are gathered in serviceability, leakage, and ultimate conditions, out of which the last two approaches contemplate a LOC. This paper reviews recognized limit state functions for corroded pipelines, and it discusses their assumptions and applicability. Specifically, this paper focuses on burst limit pressures considering the relevance in the academic literature and Oil & Gas standards. Therefore, a thorough comparison is presented based on failure criteria, acceptable defect dimensions, failure probability, and error prediction based on experimental and numerical burst tests. The objective is to evaluate the level of conservatism of each simplified model depending on the material toughness and the corrosion rate. This review aims to support a reliability model selection in corroded pipelines for future intervention strategies.

Onshore pipeline failure caused by corrosion represents about 16% of the overall number of incidents during the period from 2004 to 2011 according to databases such as CONCAWE and PHMSA. In-Line Inspection (ILI) is one of the available inspection techniques used to determine overall pipeline status, highlighted because it establishes a clear perspective of inner and outer condition of the pipe against the failure modes and wall thickness. Furthermore, it supports measures to prevent risk based on standards such as ASMEB31G or API579-1/ASME FFS-1. However, this approximation could represent a conservative assessment of the pipeline status, taking into account the uncertainty associated with ILI inspection tools such as MFL and UT. Several researches have been conducted to analyze available inspection techniques attempting to reduce noise generated by their inspection tools, and determine procedures in order to establish correct metal loss detection, excelling pattern recognition analysis and reliability concepts. Therefore this work seeks to transform a set of data obtained from two ILI runs, into useful information to support decision making in risk analysis based on pattern recognition techniques and reliability concepts, in order to obtain base failure frequencies for prior analysis from individual and grouped flaws. Moreover, growth corrosion and remaining life models supported on the standards mentioned above were evaluated using a pressure failure criteria. As a result it was obtained that the failure probability of the grouped flaws increases 10% in comparison with the corresponding flaws evaluated individually.

Parallel pipelines are frequently installed over long distances, due to the difficulty in creating or maintaining the required corridor. This implies that a release in one pipeline can seriously affect another one. The main risks associated with this domino effect are the erosive action of fluid-sand jets and the thermal action of jet fires. In this paper a survey has been performed on the accidents that have occurred, and the diverse possibilities and the associated domino sequences are analysed. The probability of occurrence of this domino effect is a function of the location of the hole, the direction of the jet, the solid angle that the jet is outlining, the diameter of both pipelines, and the distance between them. A mathematical model has been developed to estimate this probability. The model shows how the probability of domino effect decreases with the distance and diameter of the source pipe, and increases with the diameter of the target pipe. The frequency of the domino effect can be estimated from this probability and from the frequency of the initiating pipe failure plus, in the case of jet fire impingement, the probability of ignition. The frequency of the secondary pipe failure thus calculated, always higher than the individual frequency of this pipe, allows obtaining more realistic risk analysis results. HIGHLIGHTS In parallel pipelines domino effect can have a significant influence.  Domino effect will be originated by jet erosion or jet fire impingement.  The domino effect probability depends on the geometric arrangement of the system.  A mathematical model has been developed to estimate domino effect probability.  This probability allows a more realistic estimation of failure frequencies. ABSTRACTParallel pipelines are frequently installed over long distances, due to the difficulty in creating or maintaining the required corridor. This implies that a release in one pipeline can seriously affect another one. The main risks associated with this domino effect are erosion by fluid-sand jets and the thermal action of jet fires. In this paper a survey has been performed on the accidents that have occurred, and the diverse associated domino sequences are analyzed. The probability of occurrence of domino effect is a function of the location of the hole, the jet direction and solid angle, the diameter of both pipelines and the distance between them. A mathematical model has been developed to estimate this probability. The model shows how the probability of domino effect decreases with the distance and diameter of the source pipe, and increases with the diameter of the target pipe. Its frequency can be estimated from this probability and from the frequency of the initiating pipe failure plus, in the case of jet fire impingement, the probability of ignition. The frequency of the target pipe failure thus calculated, always higher than its individual frequency, allows a more realistic risk analysis.

A way to predict two-phase liquid-gas flow patterns is presented for horizontal, vertical and inclined pipes. A set of experimental data (7702 points, distributed among 22 authors) and a set of synthetic data generated using OLGA Multiphase Toolkit v.7.3.3 (59 674 points) were gathered. A filtering process based on the experimental void fraction was proposed. Moreover, a classification of the pattern flows based on a supervised classification and a probabilistic flow pattern map is proposed based on a Bayesian approach using four pattern flows: Segregated Flow, Annular Flow, Intermittent Flow, and Bubble Flow. A new visualization technique for flow pattern maps is proposed to understand the transition zones among flow patterns and provide further information than the flow pattern map boundaries reported in the literature. Following the methodology proposed in this approach, probabilistic flow pattern maps are obtained for oil–water pipes. These maps were determined using an experimental dataset of 11 071 records distributed among 53 authors and a numerical filter with the water cut reported by OLGA Multiphase Toolkit v7.3.3.

Underground pipelines have a space-dependent condition that arises from various soil properties surrounding the pipeline (e.g., moisture content, pH, aeration) and the efficiency of protection measures. Corrosion is one of the main threats for pipelines and is commonly monitored with in-line inspections (ILI) every 2 to 6 years. Preliminary characterizations of the surrounding soil allow pipeline operators to propose adequate protective measures to prevent any loss of containment (LOC) of the fluid being transported. This characterization usually requires detailed soil measurements, which could be unavailable or very costly. This paper implements categorical measurements of soil properties and defect depth measurements obtained from ILI to characterize the soil in the surroundings of a pipeline. This approach implements an independence test, a multiple correspondence analysis, and a clustering method with K-modes. The approach was applied to a real case study, showing that more severe defects are likely located in poorly drained soils with high acidity.

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In pipelines, one of the primary testing procedures used to identify the e↵ects and evolution of corrosion over time is through In-Line Inspections (ILI). ILI inspections provide detailed information regarding the inner and outer pipeline condition based on the remaining wall thickness. Based on this information, di↵erent approaches have been proposed to predict the degradation extent of the defects detected. However, these predictions are subject of uncertainties due to the inspection tool and the degradation process that poses some challenges for assessing an entire pipeline within the timespan between two inspections. To address this problem, ILI data was used to formulate a degradation model for steel-pipe degradation based on a Mixed Lévy Process. The model combines a Gamma and Compound Poisson Processes aimed for a better description of the degradation reported by the ILI data. The model seeks to estimate corrosion lifetime distribution and the mean time to failure (MTTF) more accurately. The model was tested on an actual segment of an oil pipeline, and the results have been used to support a preventive maintenance program.

A model to predict crater dimensions given a LOC in underground pipelines is proposed • The model implements 57 real accidents of natural gas underground pipelines • The approach proposes worst, mean and less severe scenarios to support decision-making • Some applications in Domino effect scenarios and Right-of-Way distances were discussed