Graded EMAT Performance Specification Validated in Blind Test

This paper describes the activities and stages completed as part of the Integrity Management Program for SCC in the natural gas system of Transportadora de Gas del Norte (TGN-Argentina) which started in 2000. This document focuses in a pipeline section of the system, which suffered an in-service failure in 2002 due to high pH SCC. This event triggered a series of activities, whose results are detailed in this paper. These activities involved soil analysis to determine the susceptibility to develop SCC along the system pipelines. For susceptible sections, the program included hydrostatic testing to levels of 100% and 110% of SMYS followed by replacement of degraded coating. The paper also details the experience in the use of new internal inspection tools with EMAT technology. The capability of the EMAT tool to detect and size SCC defects and the possibility of discriminating between SCC colonies that have been recoated and those that may still be active due to degraded coating is discussed. Finally, the severity of SCC cracks detected by in-line inspection is assessed using API 579 methodology, and the feasibility of using this assessment results to determine the critical SCC defect sizes for detection by ILI tools is analyzed.

In-line inspection (ILI) is often used to estimate failure pressure from anomalies as part of the integrity management of pipelines. The goal of this project is to improve failure pressure estimates of stress corrosion cracking (SCC) colonies by advancing field measurements and comparing ILI tool data. Electromagnetic acoustic transducer (EMAT) ILI technologies have made significant strides in providing crack depth measurements for SCC colonies, and emerging technologies such as ultrasonic testing (UT) imaging are providing more accurate in-ditch validation data. For new ILI technologies, feeding back accurate field measurements to vendors is an essential part of the process for improving ILI estimates of failure pressure. This project was designed to improve failure pressure estimates with three tasks spanning three years. Year 1 (Task 1) included the development of ultrasonic imaging processes and procedures for gathering accurate in-ditch measurements of depth, length and separation for SCC. Year 2 (Task 2) comprised field trials of the ultrasonic imaging and collection and analysis of EMAT data. Validation was performed and improvements to signal analysis for crack sizing and interaction criteria were made. Year 3 (Task 3) work included validation by means of burst tests to evaluate the performance of the model that predicts failure pressure based on ultrasonic imaging measurements. The main focus of Year 1 was comparing the dimensions of SCC colonies measured by X-ray computed tomography (XCT) to IWEX ultrasound imaging for thirty 4-inch (10 cm) wide plates containing SCC colonies. For truth data, two of these samples were destructively evaluated by breaking open cracks frozen in liquid nitrogen and sectioning through multiple parallel cracks with subsequent polishing of samples. Comparisons of the XCT and IWEX to the freeze break sample results are presented in this report across profiles of cracks in an SCC colony. The details of the work are documented in the first report for this project and summarized in this report. Year 2 focused on collecting data in the field with the IWEX system based on EMAT inspection results. A process was developed to facilitate comparisons between IWEX and EMAT data to allow an in-ditch verification of the axial cracking. Due to the technology differences between ILI and IWEX, the ILI recorded data/signals show less detail and do not allow for discrimination of the individual flaws the same way that IWEX does. Even with the differences in sampling and resolution between the techniques, it is possible to establish parameters for burst pressure calculations. A second goal of Year 2 was to select samples for Year 3 pressure testing. Year 3 focused on pressure testing of four samples to improve and verify failure pressure predictions calculated from field NDE and ILI measurements of SCC crack colony dimensions. Also examined was the potential of the recently developed intelligent interaction criteria (PRCI SIA-1-5) to predict failure pressure using IWEX results. The application of traditional interaction criteria produced mixed results. For the intelligent interaction criteria, the comparison between experimentally determined and predicted failure pressures was excellent, with a 3% average overestimation of predicted values and tight error distribution with a 3% standard deviation. Along with the specific results, this project successfully demonstrated a general approach for improving crack ILI technology using field NDE methods.

A more result-driven, holistic view on the performance of an In-line inspection (ILI) system is desired by pipeline operators, namely an integrated view on the Probabilities of Detection, Identification and Sizing, i.e. POD, POI and POS respectively. It is self-evident to combine the product of the individual probabilities to a single value POX as proposed also by API 1163. The changes in material properties of existing pipelines related to the repurposing to Hydrogen service yields smaller acceptable anomaly dimension. Consequently the dependency of the POX vs. anomaly dimensions need to be considered as function. The current practice to document the performance of an ILI system is typically based only on the specific dimensions of minimum detectable crack-like anomaly. In the case of crack-like anomalies, the contribution of the dimensions (e.g. length, depth, orientation) and interactions of crack-like anomalies can be used to turn POX into a meaningful function/dependency depending on the anomaly dimensions instead of a single value. To establish a POX to anomaly dimension relation successfully for a specific ILI crack detection service, the relevance of field verifications needs to be taken into account as well. Previous publications as well as physics foundations of NDE demonstrate that an increase in anomaly dimensions typically yields a higher sensitivity of the underlying inspection system. This can be immediately linked to the POX function as product of POD, POI and POS. This paper provides access to an in-depth assessment of POX based on the results of recent field verification data. The paper focuses on the interaction between POX and different anomaly dimensions. This is supported by the most commonly applied standard for in-line inspection, API 1163, which implies the validation of inspection performance with use of field verifications based on the reported results. In addition, a performance specification can be derived exclusively based on a field verification campaign, in the absence of other comparable performance information. As an example, as part of a conversion of natural gas transmission pipelines to hydrogen service the sensitivity of inspection systems is frequently discussed. A potentially increased crack growth rate da/dN and a reduction in pipe steel toughness seem to require a reduction of minimum acceptable anomaly dimensions, in the absence of better statistical evidence of the actual ILI performance. The proposed POX assessment will be a credible means to establish optimal re-inspection intervals for existing in-line crack inspection technologies.

The paper describes a new practical method of updating the stochastic remnant life of pipelines with defects using ILI data. The paper describes a comprehensive algorithm for assessing pipeline remnant life taking into account the stochastic results of in-line inspection (ILI). It is assumed that the pipeline segment wall has a longitudinal external crack of semi-elliptical form and is described by the J-integral. The limit state function (LSF) is described as the difference of the critical and current value of the J-integral. The latter is calculated for the current time of pipe performance and is assumed known due to monitoring of the pumping equipment. The critical crack depth is defined using the notion of fracture toughness and the J-integral approach. The algorithm contains solutions of three sequentially interconnected problems. First, the deterministic problem of fatigue crack growth (FCG) is analyzed. Then the stochastic FCG is analyzed. The probability of failure assessment algorithm is designed on the basis of the authors’ version of the adaptive important sampling (AIS) procedure. The main steps of the AIS algorithm are described in detail. The samples are generated in such a way, that at all times a majority of samples belong to the fracture region. Finally, the results of the latest ILI are fused into the algorithm, providing best possible assessment of pipeline remnant life as a random variable. The remnant life update for pipeline segment with crack-like defects using ILI data takes into account three possible outcomes: defect not discovered: defect is discovered but not measured; defect is discovered and measured. This result permits solving most important problems of pipeline maintenance: prioritization of pipeline segments for repair/rehabilitation; optimization of the time between ILI; minimization of pipe operational risk. Two real cases are described of assessing the probability of fracture/leak of a pipeline section with an external crack at different periods of its performance. The described approach currently is being generalized for the case of multiple stress corrosion SC cracks.

The emphasis on pipeline safety through reliability analysis strategies in the pipeline industry has pushed the process of uncertainty quantification towards advanced statistical techniques. Probabilistic modeling of pipeline threats and inline inspection (ILI) validation/tool performance assessment are areas that have all benefited from advances in uncertainty quantification. More recently, the statistical calibration of measurement uncertainty has developed as a promising approach for reducing the effect of measurement errors that exist in both ILI and field non-destructive examination (NDE) measurement readings. Using traditional methods for estimating measurement error quantities in ILI data, calibration provides a robust and simple approach towards incorporating the error information towards obtaining an improved estimate of the true value. Since calibration is performed at the individual feature-level, its combination with probabilistic modeling using statistical distributions at the parameter-level can potentially provide an opportunity to understand its effect on the probabilistic analysis (leak or burst limit state). In this work, the impact of applying statistical calibration towards identifying/utilizing ILI and NDE measurement uncertainty in conjunction with probabilistic modelling is explored through an investigated problem.

A new methodology for incorporating stochastic models in integrity maintenance management for high-pH stress corrosion cracking (SCC) in gas pipelines has been presented. The generation of new crack features along with the growth of existing ones are included in the stochastic modeling, by means of nonhomogeneous Poisson process (NHPP) and nonhomogeneous gamma process (NHGP), respectively. The dependence (correlation) among the growths of individual cracks is considered by employing the Gaussian copula method. Data from multiple in-line inspections (ILI) are used to evaluate the parameters of the stochastic models by means of Bayesian updating. Hence, a hierarchical Bayesian framework is developed that can efficiently account for the ILI associated measurement errors and the probability of detection (PoD) of the crack features. The Bayesian updating is performed through subset simulation, a structural reliability method (SRM) conjointly with the data augmentation (DA) technique. Multiple simulated crack features from different ILI inspections are employed for the implementation and validation of the methodology. At the end, the time-dependent system reliability is evaluated along with a parametric study that examines the impact of correlations among stochastic growths of crack features on the posterior growth model and system reliability.

For many years, pipeline safety regulations in the US have defined prescriptive minimum requirements for integrity management combined with a clear expectation that operators should do more than the minimum where appropriate. The regulations have also provided operators with the flexibility to take a performance based integrity management approach leveraging as much information available to manage threats effectively. One the threats that must be managed is Selective Seam Weld Corrosion (SSWC). SSWC is an environmentally assisted mechanism in which there is increased degree of metal loss in the longitudinal weld in comparison to the surrounding pipe body. An appropriate definition is linear corrosion that is deeper in the longitudinal weld zone than the surrounding pipe body. In some cases, the surrounding pipe body may have limited or no corrosion present, and in other cases the pipe body corrosion may have occurred but at a slower rate than the local corrosion in the longitudinal weld zone. Conventional responses to potential or identified threats focus on in-situ investigations, often resulting in expensive and un-planned repairs for features reported by In-line Inspection (ILI) that when assessed properly demonstrate a remnant life well into the next inspection interval. When ILI identifies metal loss indications co-located with the longitudinal seam weld, the current prescribed response is often a blanket call for remediation. Such a response may not be appropriate if an ILI system is deployed to discriminate feature types and integrity assessment is exercised leveraging a sound understanding of the pipe’s material properties. This paper describes an approach that can be taken to manage the threat of SSWC. The foundation of the approach is deployment of an appropriate ILI system incorporating an effective ILI technology, an optimized evaluation process considering the specific threat morphology, material testing and a structured dig program. The evaluation process uses the ILI data and data from the field in combination material properties data and a susceptibility analysis to classify anomalies as “Likely”, “Possible” and “Unlikely” SSWC. This is aligned with the guidance in API RP 1176 “Assessment and Management of Cracking in Pipelines” for defining an appropriate response to ILI calls. Approaching the management of SSWC in this way allows operators to define a structured response for excavation activities to verify the process and remediate features as required. By using likelihood classification the risk to pipeline integrity can be reduced by acting on the most likely SSWC features as a priority, whilst collecting the data needed to make informed decisions on where to focus resources and efforts on what is a very complicated and difficult to manage threat. The output form this work, including a future plan for managing the remaining metal loss features, can be documented in a procedure and incorporated into an existing Integrity Management Plan.

Gas transmission pipeline operators increasingly rely on Electro-Magnetic Acoustic Transducer (EMAT) technology to reliably detect, identify and size stress corrosion cracking (SCC) anomalies in their pipeline system. However, scheduling EMAT in-line inspection (ILI) on every pipeline in the system is not always practicable or achievable in an expeditious manner. A means of conducting a preliminary assessment of the SCC threat on pipelines without EMAT ILI data in an objective and quantifiable manner is useful for understanding the threat level and for prioritizing or deciding on outstanding EMAT inspections. A wealth of system-specific SCC field data from historical integrity excavations across the pipeline system typically exists in a pipeline operator’s dataset and can be readily leveraged for quantitatively estimating the SCC threat reliability in other, similar (“like-in-kind”) parts of the pipeline system. This system-specific data, based on actual SCC findings from integrity excavations, is an improved and more granular alternative to applying industry-wide SCC statistics to estimates of SCC reliability levels on pipelines without EMAT ILI data. This paper presents a robust and direct limit state approach for estimating the SCC reliability level in pipelines that have not yet had an EMAT ILI completed by leveraging system-wide SCC field findings from historical integrity excavations.

This paper establishes a dynamic Bayesian network to model the growth of corrosion defects on energy pipelines. The integrated model characterizes the growth of defect depth by a homogeneous gamma process and considers the biases and random errors associated with the in-line inspection (ILI) tools. The distributions of the mean value and coefficient of variation of the annual growth of defect depth are learned from multiple ILI data using the parameter learning technique of Bayesian networks. With the same technique, the distributions of the biases and standard deviation of random errors associated with ILI tools are learned from ILI data and their corresponding field measurements. An example with real corrosion management data is used to illustrate the process of developing the model structure, learning model parameters and predicting the corrosion growth and time-dependent failure probability. The results indicate that the model can in general predict the growth of corrosion defects with reasonable accuracy and the ILI-reported and field-measured depth can be used to update the time-dependent failure probability in a near-real-time manner. In comparison with existing growth models, the graphical feature of Bayesian networks makes it more intuitive and transparent to users. The employment of parameter learning provides a semi-automated and convenient approach to elicit the probabilistic information from ILI and field measurement data. The above advantages will facilitate the application of the model in the practice of corrosion management in pipeline industry.

Corrosion growth rate (CGR) is one of the key elements in corrosion threat management. It is used to determine metal loss In-Line Inspection (ILI) re-assessment interval, identify high growth features that require excavation before the next ILI and predict probability of failure of an unmitigated feature. Overestimated CGR may result in unnecessary expenditures for excavations and remediation, while underestimated CGR could result in pipeline failure. Although there are many methods to derive CGR from successive ILIs, there is no particular approach widely accepted by industry. In this paper, several CGR methodologies used by Enbridge to manage corrosion threats on pipelines including CGR based on feature matching and signal matching are discussed and validated. CGR based on feature matching refers to the rate that is calculated based on ILI reported depths of two back-to-back ILIs. CGR based on signal matching refers to the rate that is determined based on ILI raw data review provided from the ILI vendor. Both feature level and joint level CGR have been used in corrosion threat management. A probabilistic CGR methodology based on Pipeline Research Council International (PRCI)(1) EC-1-2 project (Development of detailed procedures for comparing successive ILI runs to establish corrosion growth rate) that accounts for uncertainty of measurement tools is also included in this study. The ILI data and field non-destructive evaluation (NDE) results of six onshore pipelines are used for this study. Each of the six pipelines has at least three high resolution Magnetic Flux Leakage (MFL) inspections. The various CGRs are established based on the 1st and 2nd inspections. The CGR methodologies are validated based on comparing the predicted depth using CGR with the field measured depth as well as the depth reported by the 3rd ILI. Over 700 field measured feature depths are used in this study and over 60,000 ILI features are used to validate the estimated depth at the time of field measurements and at the time of the 3rd ILI. This paper demonstrates the validation results of feature level and joint level CGR based on both feature matching and signal matching. The probabilistic CGR methods are also validated using the same method. The CGR validation study enables pipeline operators to establish defect repair schedules and re-inspection intervals with increased confidence.

Stress-corrosion cracking (SCC) occurs occasionally in line-pipe steels. Reviews of this cracking indicate that the environment is carbonate-bicarbonate and that the cracking is primarily intergranular. Research sponsored by the PRCI Line Pipe Research Supervisory Committee (LPRSC) has over the years identified metallurgical and electrochemical parameters as playing a role in the process. This work has also argued the significance of strain rate and its relationship to the service loading, given that dissolution is indicated as the controlling mechanism. While much has been learned about the mechanism of cracking, very little has been learned about how to directly relate the nucleation and growth of cracks to the loading, the metallurgy, and the environmental parameters. The continual development of new line-pipe steels, the probable development of reliable in-line inspection (ILI) tools to detect SCC, and the occasional discovery of cracking colonies during field surveys have recently centered attention on methods to rank line-pipe resistance to SCC and characterize crack-growth rates. Ranking line-pipe resistance to SCC may be done in terms of a threshold stress for nucleation of SCC or the rate of crack growth at some crack depth beyond nucleation. Estimating remaining life of cracks located by an ILI tool or confirmed in a field survey involves only crack growth rate data or data that define a threshold stress for continued growth. Recent attention of the SCC subgroup of the LPRSC, therefore, has focussed on experimental protocols to assess susceptibility, determine thresholds, and establish growth rate behavior. The tapered-tension test (TTT) has been developed to determine stress thresholds for crack nucleation, whereas several different prenotched or precracked geometries have been or are now being used to assess crack growth. Attention has also focussed on modelling SCC thresholds and crack growth behavior so that data developed under laboratory conditions can be adapted to assess field cracking situations. Models are being explored for both threshold and crack-growth conditions. This report presents the development and validation for a model that is being adapted to line-pipe problems for the SCC subgroup. This model deals with the threshold for and the growth of SCC cracks up to about 0.020-inch deep.

As the global pipeline network ages, the threat of cracks and crack growth (particularly stress corrosion cracking (SCC) and/or fatigue) becomes more prominent. Cracking mechanisms are often complex and can be challenging to both inspect and manage. The pipelines in India are relatively new compared to several other countries, this leaves the operators in a good position to take a pro-active approach to the management of cracking threats, by learning from the experience of their counterparts across the world. Such an approach would enable operators to reduce the risk of failures relating to cracking on their systems. Effective management of the cracking threats requires appropriate technical expertise supported by robust management controls. This paper will describe the Pipeline Integrity Framework for Cracking (PIF-Crack) as implemented for various operators around the world and its constituent parts. PIF-Crack is intended to ensure a structured decision-making process where the cracking threat is understood prior to the selection of in-line inspection (ILI) technologies through key activities such as failure investigations and susceptibility analysis. This paper will help wrap up various key concepts to support operators with crack management, including ILI validation, challenges/pitfalls regarding accurate field verification data for cracking and integrity management planning for cracking (aligning with the concepts from API 1163, API 1176 and ISO 19345). Leveraging the systematic process of PIF-Crack allows predictive maintenance, and monitoring of cracking threats, ultimately enhancing pipeline operations’ safety, efficiency and profitability.

The current finite element (FE) assessment methods of dented pipes are based on specific dent profiles, which are generally created based on the shape of indenters. However, the actual dent profile in real case scenarios is mostly irregular in shape, depending on the cause of damage. In this paper, FE analyses of dented pipes using inline inspection (ILI) data are presented. Based on the ILI data, the dent profile is generated by applying the nodal displacements to all the pipe nodes. The validation of this nodal displacement approach is discussed in this paper. Besides, a parametric study is carried out to study the behavior of dent for different dent depth, pipe geometry, and pipe grades. The significance of residual stresses generated during the dent formation on the behavior of dented pipe during the service life is also discussed. Finally, the remaining life estimation of dented pipes according to the API 579-1 is presented using FE analysis results.

Underground coated structures such as pipelines, transmission towers & poles, galvanized guy anchors, tanks and coated galvanized anchors are aging and are at risk of corrosion failure due to coating shielding cathodic protection, localized corrosion and stress corrosion cracking. Those tasked with maintaining these structures require an in-depth understanding of the locations where these aging pipelines are at risk of localized corrosion due to cathodic protection shielding. Corrosion failures in aging pipelines are either sudden catastrophic ruptures or gradual leaks due to localized corrosion. Corrosion failures in transmission structures or galvanized anchors are also at risk of loss in thickness and catastrophic ruptures. Major factors associated with these corrosion areas are coating dis-bondment, blistering/delamination, the presence of moisture, corrosive soils, inadequate cathodic protection and cathodic protection shielding. These areas have a much higher statistical probability of catastrophic failure and rupture. In pipelines, most of the time initiation of stress corrosion cracking (SCC) and pitting corrosion are detected by coincidence in excavation and digs and is not targeted or predicted by analysis of corrosion performance parameters. Internal or In-line inspection (ILI) tools have limited capability for detecting or identifying stress corrosion cracking and pitting corrosion initiation. Here we would like to elaborate on corrosion risk associated with coatings that shield cathodic protection.

Wednesday, October 2, 2019 11:00 a.m. ET PRESENTER: Smitha Koduru, PhD, C-FER Technologies HOST: Steven Bott, Enbridge MODERATOR: John Lynk, PRCI CLICK THE DOWNLOAD/BUY BUTTON TO ACCESS TO THE WEBINAR REGISTRATION LINK Join the PRCI Integrity and Inspection Technical Committee as they present an expansion of previous PRCI research related to ILI performance data. The new research has been expanded to include experience with UT and EMAT in-line inspection data aligned with in-the-ditch NDE results. Also included are improved statistical characterization of crack inline inspection performance; increasing the reliable application of crack ILI to manage cracking and SCC recommendations for in-the-ditch NDE; and information collected to maximize the ability of operators to measure crack ILI performance. Learning outcomes/benefits of attending this webinar: - Learn about the data sets featured in the industry-wide database for crack features identified with in-line inspection tools (ILI) and/or field non-destructive examination (NDE). - Know the influence of pipe attributes, such as seam weld type, and NDE performance on the crack detection and sizing performance assessment of ILI tools - Understand the methods required to use data from multiple ILI runs and field measurements for increased confidence in crack detection and sizing - Recognize the value of collecting full crack profile data for integrity management Who should attend? - Integrity personnel, analyst, engineers and management - Inline inspection vendor personnel Recommended pre-reading: PR-244-173856-R01 In-line Inspection Crack Tool Reliability and Performance Evaluation Not able to attend? Register anyway to automatically receive a link to the webinar recording to view on-demand at your convenience. Attendance is limited to the first 500 registrants to join the webinar. All remaining registrants will receive a link to view the webinar recording. After registering, you will receive a confirmation email containing information about joining the webinar. Please click here to view more webinars that may be of interest to you!