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

Abstract

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.

A condition-based dynamic segmentation of large systems using a Changepoints algorithm: A corroding pipeline case

“…Empirical approaches usually cover standards or best practices of Oil & Gas companies; see for instance [13,14]. Numerical approaches usually deal with Finite Elements simulations, and probabilistic approaches evaluate plastic collapse, yielding, or leak failure criteria based on safety margins or limit state functions (see [15][16][17][18]). In either case, these analyses aim to support decisions for integrity management and pipeline risk analysis.…”

“…A burst failure probability was evaluated following the formulation detailed in Section 2.4 for the proposed dynamic segmentation (Section 4.2), a fixed segmentation every kilometer, and segmentation using the soil categories (see Table 2) considering the Netto et al model [51]. This selection was made considering that the case study has a moderate toughness and that previous prediction errors were quite low using FEM and experimental tests, which indicates that the model tends not to be conservative [16]. For this calculation, the failure probability was estimated using 10,000 Monte Carlo simulations for each reported defect, and the failure probability of each segment was bounded using Eq.…”

“…Appendix A. Burst pressure models summary Based on the recent review of Amaya-Gómez et al [16], some models are suggested depending on the material toughness. For a low toughness pipe the models of DNV, CPS, B31G modified, and CUP are recommended; for moderate toughness materials the models of Ma, PCORRC, Netto, and Zhu give adequate predictions; and for high toughness materials, the approaches of Chen, PCORRC, Ma, and Choi provide remarkable results.…”

“…For a low toughness pipe the models of DNV, CPS, B31G modified, and CUP are recommended; for moderate toughness materials the models of Ma, PCORRC, Netto, and Zhu give adequate predictions; and for high toughness materials, the approaches of Chen, PCORRC, Ma, and Choi provide remarkable results. These models will be summarized below; further details for each model, please refer to the review of Amaya-Gómez et al [16] and the references cited therein. .…”

Modeling of pipeline corrosion degradation mechanism with a Lévy Process based on ILI (In-Line) inspections

“…For the moment, this failure represents an ultimate limit state in which the wall thickness is entirely consumed by the corrosion degradation process. This paper does not contemplate other failures such as plastic collapse or deformation, which are reviewed in more detail in [44], but concentrates on the information that can be provided exclusively from the degradation process. Note that the evaluation of the MTTF requires the computation of the failure time distribution, which also provides valuable information on the degradation process and for pipeline reliability.…”