Advanced Eddy Current Array Tools for Stress Corrosion Cracking Direct Assessment on Pipelines

2020 ◽  
Author(s):  
Michael Sirois ◽  
Mathieu Bouchard ◽  
Ahmed Sweedy
Keyword(s):  
Stress Corrosion ◽  
Eddy Current ◽  
Stress Corrosion Cracking ◽  
Human Factor ◽  
Corrosion Cracking ◽  
Probability Of Detection ◽  
Ease Of Use ◽  
Process Efficiency ◽  
Screening Process ◽  
Direct Assessment

Abstract Magnetic Particle Inspection (MPI) has been the main reference for Stress Corrosion Cracking (SCC) detection in pipeline integrity for years. Although this technique is relatively economical and easy to deploy — thanks to a large pool of certified technicians — it remains time consuming and highly user dependent. Some of the factors impacting results during SCC Direct Assessment (SCCDA) include the total surface area requiring examination, hard-to-reach positions underneath pipes during inspection, improper surface preparation due to poor sandblast or contrast, condensation on pipes, and operator fatigue. Recent trials have proved that Eddy Current Array (ECA) technology compares favorably against MPI on many aspects in the field, and that ECA has the potential to become the new standard for SCCDA on pipelines. Offering an impressive speed, combined with a particularly high Probability of Detection (PoD), ECA could transform the work of technicians in ditches and above all, offer greater control over the human factor. Besides detection, ECA has also proven its reliability for SCC characterization on real SCC colonies in both lab and field environments. Comparisons to metallography sections, grinding measurements and X-Ray Computed Tomography (XCT) data have greatly contributed to optimized depth sizing algorithms for this new solution, providing accurate SCC depth readings. Although ECA and Phased Array Ultrasonic Testing (PAUT) are often complementary techniques in the field, the main advantage of ECA over PAUT resides in the short amount of time required to locate and size the deepest cracks among colonies containing sometimes thousands of cracks. Within a few minutes, technicians and engineers know where to concentrate and how critical SCC really is so that decisions can be made instantly. Combining ease of use and repeatability (ways to control the human factor) is another key benefit of ECA technology. This paper provides information about a complete ECA solution for SCC detection and depth sizing on pipelines. It reveals results from the field, comparing ECA with MPI, covering several key points and demonstrating how ECA stands out as improving the overall screening process efficiency during examinations in digs. Furthermore, it also exposes and compares ECA data with both destructive and non-destructive testing performed on test pieces containing real SCC.

Validation of EMAT ILI for Management of Stress Corrosion Cracking in Natural Gas Pipelines

2014 ◽  
Author(s):  
Toby Fore ◽  
Stefan Klein ◽  
Chris Yoxall ◽  
Stan Cone
Keyword(s):  
High Resolution ◽  
Natural Gas ◽  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Corrosion Cracking ◽  
Probability Of Detection ◽  
Gas Pipelines ◽  
Line Pipe ◽  
Natural Gas Pipelines ◽  
Electro Magnetic

Managing the threat of Stress Corrosion Cracking (SCC) in natural gas pipelines continues to be an area of focus for many operating companies with potentially susceptible pipelines. This paper describes the validation process of the high-resolution Electro-Magnetic Acoustical Transducer (EMAT) In-Line Inspection (ILI) technology for detection of SCC prior to scheduled pressure tests of inspected line pipe valve sections. The validation of the EMAT technology covered the application of high-resolution EMAT ILI and determining the Probability Of Detection (POD) and Identification (POI). The ILI verification process is in accordance to a API 1163 Level 3 validation. It is described in detail for 30″ and 36″ pipeline segments. Both segments are known to have an SCC history. Correlation of EMAT ILI calls to manual non-destructive measurements and destructively tested SCC samples lead to a comprehensive understanding of the capabilities of the EMAT technology and the associated process for managing the SCC threat. Based on the data gathered, the dimensional tool tolerances in terms of length and depth are derived.

A Statistical Predictive Model to Prioritize Site Selection for Stress Corrosion Cracking Direct Assessment

2006 ◽  
Author(s):  
Anthony Merle ◽  
P. F. Ehlers
Keyword(s):  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Environmental Parameters ◽  
Predictive Modelling ◽  
Corrosion Cracking ◽  
Direct Assessment ◽  
Degree Of Certainty ◽  
Regression Techniques ◽  
Selection For ◽  
High Degree

Pipeline stress-corrosion cracking (SCC) is an ongoing integrity concern for pipeline operators. A number of different strategies are currently employed to locate and mitigate SCC. Ultrasonic in-line inspection tools have proven capable of locating SCC, but reliability of these tools in gas pipelines remains in question. Rotating hydrotest programs are effectively employed by some companies but may not provide useful information as to the location of SCC along the pipeline. NACE Standard RP0204-2004 (SCC Direct Assessment Methodology) outlines factors to consider and methodologies to employ to predict where SCC is likely to occur, but even this document acknowledges that there are no well-established methods for predicting the presence of SCC with a high degree of certainty. Predictive modelling attempts to date have focused on establishing quantitative relationships between environmental factors and SCC formation and growth; these models have achieved varying degrees of success. A statistical approach to SCC predictive modelling has been developed. In contrast to previous models that attempted to determine direct correlations between environmental parameters and SCC, the new model statistically analyzed data from dig sites where SCC was and was not found. Regression techniques were used to create a multi-variable logistic regression model. The model was applied to the entire pipeline and verification digs were performed. The dig results indicated that the model was able to predict locations of SCC along the pipeline.

Caution when applying eddy current inversion to stress corrosion cracking

2006 ◽  
Vol 236 (2) ◽  
pp. 211-221 ◽  
Author(s):  
Noritaka Yusa ◽  
Ladislav Janousek ◽  
Mihai Rebican ◽  
Zhenmao Chen ◽  
Kenzo Miya ◽  
...  
Keyword(s):  
Stress Corrosion ◽  
Eddy Current ◽  
Stress Corrosion Cracking ◽  
Corrosion Cracking ◽  
Eddy Current Inversion ◽  
Current Inversion

Statistical Predictive Modelling: A Methodology to Prioritize Site Selection for Near-Neutral pH Stress Corrosion Cracking

2010 ◽  
Author(s):  
Edgar I. Cote ◽  
James Ferguson ◽  
Nauman Tehsin
Keyword(s):  
Tensile Stress ◽  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Corrosion Cracking ◽  
Probability Of Detection ◽  
Predictor Variables ◽  
Neutral Ph ◽  
Proactive Management ◽  
Ph Stress ◽  
Axial Defects

Pipelines are subjected to both residual and applied tensile stresses, and can form near-neutral pH SCC (transgranular stress corrosion cracking) if the pipeline is exposed to a conducive environment and is made from a material that is susceptible to SCC. This transgranular SCC is an ongoing integrity concern for pipeline operators. As part of an SCC Integrity Management Program (IMP), it is necessary to perform integrity assessments and prioritize segments of the pipelines to manage the SCC threat. Ultrasonic crack detection in-line inspection tools have proven capable of locating SCC, but reliability of these tools is not absolute and the reduced probability of detection of subcritical flaws limits options for proactive management. Hydrostatic retesting is a very effective program for removing near-critical axial defects, such as SCC, but does not provide useful information as to the location of SCC along the pipeline. NACE Standard RP0204-2004 (SCC Direct Assessment Methodology or SCCDA) outlines factors to consider and methodologies to employ to predict where the SCC is likely to occur, but the standard acknowledges that there are no well-established methods for predicting the presence of SCC with a high degree of certainty. The trend in probabilistic modelling has been to focus on establishing deterministic relationships between environmental factors, tensile stress and SCC formation, and growth; these models have achieved varying degrees of success. The Statistical Predictive Model (SPM) was previously developed to predict the likelihood of occurrence of near-neutral pH Stress Corrosion Cracking (SCC) for the NPS 10 Alberta Products Pipeline (APPL). SPM Phase 5 uses selected predictor variables representing tensile stress, environmental, pipe-related, corrosion control and operational relevant factors to determine the Probability of Occurrence of SCC. Regression techniques were used to create multi-variable logistic regression models. The results for each model are checked at locations where SCC is known to be present or absent to assess predictive accuracy, then used to prioritize susceptible segments for field excavation. The relative strength of individual predictor variables provides insight into the mechanism of near-neutral pH SCC crack initiation.

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