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.