Corrosion Metal Loss Interaction From In-Line Inspection and How it Can Affect the Calculated Failure Pressure

In-Line Inspection (ILI) is used to prioritize metal loss conditions based on predicted failure pressure in accordance with methods prescribed in industry standards such as ASME B31G-2009. Corrosion may occur in multiple areas of metal loss that interact and may result in a lower failure pressure than if flaws were analyzed separately. The B31G standard recommends a flaw interaction criterion for ILI metal loss predictions within a longitudinal and circumferential spacing of 3 times wall thickness, but cautions that methods employed for clustering of ILI anomalies should be validated with results from direct measurements in the ditch. Recent advances in non-destructive examination (NDE) and data correlation software have enabled reliable comparisons of ILI burst pressure predictions with the results from in-ditch examination. Data correlation using pattern matching algorithms allows the consideration of detection and reporting thresholds for both ILI and field measurements, and determination of error in the calculated failure pressure prediction attributable to the flaw interaction criterion. This paper presents a case study of magnetic flux leakage ILI failure pressure predictions compared with field results obtained during excavations. The effect of interaction criterion on calculated failure pressure and the probability of an ILI measurement underestimating failure pressure have been studied. We concluded a reason failure pressure specifications do not exist for ILI measurements is because of the variety of possible interaction criteria and data thresholds that can be employed, and demonstrate herein a method for their validation.

A Real-Time AC/DC Measurement Technique for Assessment of AC Corrosion of Buried Pipelines

In this work, a real-time AC/DC signal data acquisition (DAQ) technique was developed, which is capable of separating the DC and AC potential components from the recorded total potential, providing mechanistic information about the steel corrosion in the presence of AC interference. It was found that the corrosion of the steel is enhanced by the applied AC current density from 0 to 400 A/m2. With the further increase to 600 A/m2 and 800 A/m2, the corrosion rate of the steel decreases, which is attributed to passivation of the steel at sufficiently high AC current densities, and a compact film is formed on the steel surface. Moreover, the derived mathematic relationships between AC potential and AC current density provides a potential alternative to determine AC current density on pipelines based on measurements of AC potential in the field.

Pressure Test Planning to Prevent Internal Corrosion by Residual Fluids

Strength and leak testing (AKA ‘hydrotesting’, and ‘pressure testing’) of pipeline projects remains a primary method of providing quality assurance on new pipeline construction, and for validating structural integrity of the as-built pipeline [1][2][3]. A myriad of regulations surround these activities to ensure soundness of the pipeline, security of the environment during and after the pressure testing operation, as well as personnel safety during these activities. CAN/CSA Z662-11 now includes important clauses to ensure that the pipeline designer/builder/operator consider the potential corrosive impacts of the pressure test media [4]. This paper briefly discusses some of the standard approaches used in the pipeline industry to address internal corrosion caused by pressure test mediums — which often vary according to the scope of the pipeline project (small versus large diameter, short versus very long pipelines) — as well as the rationale behind these different approaches. Case studies are presented to highlight the importance of considering pressure test medium corrosiveness. A practical strategy addressing the needs of long-distance transmission pipeline operators, involving a post-hydrotest inhibitor rinse, is presented.

Multiple Data Set ILI for Mechanical Damage Assessment

The purpose of this paper is to present a non-traditional pipeline mechanical damage ranking system using multiple-data-set in-line inspection (ILI) tools. Mechanical damage continues to be a major factor in reportable incidents for hazardous liquid and gas pipelines. While several ongoing programs seek to limit damage incidents through public awareness, encroachment monitoring, and one-call systems, others have focused efforts on the quantification of mechanical damage severity through modeling, the use of ILI tools, and subsequent feature assessment at locations selected for excavation. Current generation ILI tools capable of acquiring multiple-data-sets in a single survey may provide an improved assessment of the severity of damaged zones using methods developed in earlier research programs as well as currently reported information. For magnetic flux leakage (MFL) type tools, using multiple field levels, varied field directions, and high accuracy deformation sensors enables detection and provides the data necessary for enhanced severity assessments. This paper will provide a review of multiple-data-set ILI results from several pipe joints with simulated mechanical damage locations created mimicing right-of-way encroachment events in addition to field results from ILI surveys using multiple-data-set tools.

Predicting the Failure Pressure of SCC Flaws in Gas Transmission Pipelines

An important requirement for the management of stress-corrosion cracking (SCC) in natural gas transmission pipelines is the ability to predict accurately the burst failure pressure of flaws that have been discovered, particularly those found by crack detection in-line inspection (ILI). ASME B31.8S contains guidance for categorization of SCC based on predicted failure pressure for the cracks. Assessment of the segments is based on the severity category of SCC. As part of a Joint Industry Project (JIP) addressing the management of SCC in gas transmission pipelines, eight operators have assembled information relating to 85 in-service failures, hundreds of hydrostatic test failures, and dozens of pipe burst tests in which failure was due to SCC. Within the database are a wide range of pipe grades and sizes. Failures are due to both high pH and near-neutral pH SCC, and the flaws that initiated failure range from simple thumbnails to complex groups of cracks in a three-dimensional cluster. This paper presents some of the results from a comprehensive comparative study of the failure pressure predictions obtained using API 579 Level II, ln-secant, CorLAS® and PAFFC methods for around 40 of the best-characterized datasets within the above database. From the results obtained, the sensitivities of the calculations to the calculation method used and to the input data, such as flaw profile, are examined. The results provide useful guidance to all those involved in predicting failure pressures as part of their threat management activities.

Overcoming Technical Limitations in Identifying and Characterizing Critical Complex Corrosion

In 2009 a pipeline within the TransCanada pipeline system experienced a rupture. As this pipeline was already under a rigorous In Line Inspection (ILI) based corrosion management program this failure led to an extensive root cause analysis. Even though the hazard causing the failure was microbiologically induced corrosion (MIC) under tape coating, the more troubling question was “Why had the severity of this anomaly not been determined by the ILI based corrosion management program?” This led to an investigation of what key characteristics of the ILI signals resulting from areas of “complex corrosion” are more difficult to correctly interpret and size and furthermore where the line condition is such that manual verification is needed. By better understanding the limitations of the technology, processes used, and the critical defect signal characteristics, criteria were developed to ensure that “areas of concern” are consistently identified, manually verified and therefore the sizing is validated at these potentially higher risk locations. These new criteria were applied on ILI data and then validated against in-the-ditch measurements and a hydrotest. This process in conjunction with optimization of ILI sizing algorithms enabled the operator to overcome some of the known challenges in sizing areas of complex corrosion and update its corrosion management process to improve the detection and remediation of critical defects. This paper describes this investigation of the failure location, development of the complex corrosion criteria, and the validation of effectiveness of the criteria. The criteria are focused on external corrosion and have been currently validated on pipelines of concern. Application to other lines should be similarly validated.

Evaluating the Effects of Ovality on the Integrity of Pipe Bends

This paper provides details on a study performed for a liquids pipeline operator to evaluate the effects of ovality on the mechanical integrity of pipe bends in their 16-inch pipe system. Prior to this study, a caliper tool was run that indicated unacceptable ovality was present in the bends relative to the requirements set forth in ASME B31.4. An engineering investigation was performed based on the methodology of API 579 Fitness for Service. This standard provides guidance on evaluating defects using a multi-level assessment approach (Levels 1, 2, and 3) that rewards rigorous evaluation efforts by reducing the required design margins. Therefore, an extensive evaluation was performed that involved making field measurements of the bends in the ditch. Using these ovality measurements, calculations were performed using the closed-form equations in API 579 for Level 2 assessment. The ovality of several of the bends in the field was deemed unacceptable based on in-field measurements. Consequently, a Level 3 assessment was completed using finite element analysis (FEA). The results of this more rigorous analysis, coupled with more favorable design margins, resulted in this particular bend being acceptable. A tool was developed to permit a general assessment of pipe bends having ovality and was validated by performing a full-scale burst test.

Effects of Detector Dynamics on Magnetic Flux Leakage Signals From Dents and Gouges

The current study was designed to model the dynamic effects of detector ride and magnet liftoff on Magnetic Flux Leakage (MFL) signals from dents as well as gouges that have significant denting. The MFL tools have long been used for the detection and sizing of corrosion defects. This is comparatively straightforward for a number of reasons, one of which is that the MFL detector assembly can ride relatively smoothly along the inner pipe wall surface. This is not the case when significant denting is present, since the dent presents a perturbation in the pipe wall that can cause liftoff of the detector or magnet system. Since the tool travels at relatively high speeds down the pipe, the dent itself can cause the detector to lose contact with the trailing half of the dent. In addition, the magnet pole piece may experience partial liftoff as it traverses the dent, thus causing a change in the local flux density. In this study results from ‘static’ measurements are compared with a dynamic case in which detector liftoff is simulated through modeling and experiment. Results are discussed regarding the severity of MFL signal loss at the trailing edge of the defect as a result of detector liftoff. The effect of partial liftoff of the magnet as it passes over the dent is also examined. Magnet liftoff is found to increase the local magnetic flux near the liftoff region, causing the MFL signal from the dent wall to increase rather than decrease in the vicinity of magnet liftoff region.

Useful Trends for Predicting Corrosion Growth

The objective of an effective corrosion management program is to identify and mitigate corrosion anomalies before they reach critical limit states. Often as there are many anomalies on pipelines an optimized program will mitigate the few corrosion anomalies that may grow to a critical size within the next inspection interval, without excavating many of the anomalies that will not grow to a critical size. This optimization of the inspection interval and the selection of anomalies to mitigate depend on understanding of corrosion growth. Prediction of corrosion growth is challenging because growth with time is non linear and highly location specific. These characteristics make simplistic approaches such as using maximum growth rates for all defects impractical. Therefore it is important to understand the salient aspects of corrosion growth so that appropriate decisions on excavation and re-inspection can be made without compromising safety or undertaking undue amounts of mitigative activities. In the pipeline industry corrosion growth between two in line inspections (ILIs) has been measured by comparing one ILI run to the next. However many types of ILI comparison methodologies have been used in the past. Within the last decade or two comparison techniques have evolved from box matching of defect samples to signal matching of the total defect populations. Multiple comparison analyses have been performed on the TransCanada system to establish corrosion growth rates. Comparison of the results from these various analyses gives insight into the accuracy and uncertainty of each type of estimate. In an effective integrity management process the best available corrosion growth data should be used. To do so it is important to understand the conservatism and the uncertainty involved in each type of estimate. When using a run-comparison to predict future growth it is assumed that the growth within the last ILI interval will continue (with associated uncertainty) during the next inspection interval. The validity of these assumptions is examined in this study. In the context of this paper these assumptions are validated for external corrosion on onshore pipelines. Characteristics of internal and offshore corrosion are very different in space and time variation. Correlations of external corrosion growth in onshore pipelines with defect size and location are also examined. Learning from multiple corrosion growth studies gives insight into the actual corrosion rate variation along a pipeline as well as general growth characteristics. Different types of corrosion growth modeling for use in probabilistic or deterministic integrity management programs are also discussed.