Implementation of Integrity Management Programs (IMP) for pipelines has motivated the design of Fitness-For-Service methodologies to assess Stress Corrosion Cracking (SCC) and fatigue-dependent features reported by Ultrasonic Crack Detection (UTCD) In-Line Inspections. The philosophical approach defined by the API 579 [1] “Fitness-For-Service” from the petrochemical industry in conjunction with Risk-based standards and regulations (i.e. CSA-Z662-2003 [2] and US DOT 49 Parts 192 [3] and 195 [4]) and in-line inspection validation (i.e. API 1163 [5]) approaches from the pipeline industry have provided the engineering basis for ensuring the safety, reliability and continued service of the in-line inspected pipelines. This paper provides a methodology to develop short and long-term excavation and re-inspection programs through a four (4) phase-process: Pre-Assessment, Integrity Criticality Assessment, Remediation and Repair, Remaining Life Extension and In-Service Monitoring. In the first phase, Pre-assessment, areas susceptible to Stress Corrosion Cracking (SCC) and fatigue-dependent features are correlated to in-line inspection data, soil modeling, pipeline and operating conditions, and associated consequences in order to provide a risk-based prioritization of pipeline segments and technical understanding for performing the assessment. The second phase, Integrity Criticality Assessment, will develop a short-term maintenance program based on the remaining strength of the in-line inspection reported features previously correlated, overlaid and risk-ranked. In addition, sites may be identified in Phase 1 for further investigation. In the third phase, a Remediation and Repair program will undertake the field investigation in order to repair and mitigate the potential threats as well as validating the in-line inspection results and characterization made during the Pre-assessment and Integrity Criticality Assessment (Phases 1 & 2). With the acquired knowledge from the previous three (3) phases, a Remaining Life Extension and In-Service Monitoring program will be developed to outline the long-term excavation and re-inspection program through the use of SCC and Fatigue crack growth probabilistic modeling and cost benefit analysis. The support of multiple Canadian and US pipeline operating companies in the development, validation and implementation of this methodology made this contribution possible.
Safety culture is a concept which has garnered increasing interest within the pipeline industry in recent years. Made up of the attributes and values of a company as well as the perceptions and values of the individuals within it, safety culture reflects the organization’s commitment to safety. Improvement of an organization’s safety culture can result in a reduction in the frequency of undesired events. The assessment of safety culture presents a number of challenges, including the appropriate selection of models and data gathering methodologies that provide measurable and repeatable results and address both personal and process safety; the development of action plans which drive change within the appropriate levels of an organization; and the measurement of improvement efforts and outcomes. The objective of this paper is to share lessons learned and guidance based on experience conducting semi-quantitative safety culture assessments. This paper will describe: researching and selecting a safety culture assessment model; selecting, developing, and customizing the assessment methods (e.g. document review, surveys, interviews, and observations); undertaking the assessment itself; quantifying and analyzing the findings of the assessment; developing recommendations that improve safety culture; and considerations for the implementation of action plans to ensure continual improvement. The guidance provided in this paper is intended to help organizations improve the safety culture at all levels of the business in order to advance both personal and process safety performance.
The importance of comparing in-line inspection (ILI) calls to excavation data should not be underestimated. Neither should it be undertaken without a solid understanding of the methodologies being employed. Such a comparison is not only a key part of assessing how well the tool performed, but also for an API 1163 evaluation and any subsequent use of the ILI data. The development of unity (1-1) plots and the associated regression analysis are commonly used to provide the basis for predicting the likelihood of leaks or failures from unexcavated ILI calls. Combining such analysis with statistically active corrosion methods into perhaps a probability of exceedance (POE) study helps develop an integrity maintenance plan for the years ahead. The theoretical underpinnings of standard regression analysis are based on the assumption that the independent variable (often thought of as x) is measured without error as a design variable. The dependent variable (often labeled y) is modeled as having uncertainty or error. Pipeline companies may run their regressions differently, but ILI to field excavation regressions often use the ILI depth as the x variable and field depth as the y variable. This is especially the case in which a probability of exceedance analysis is desired involving transforming ILI calls to predicted depths for a comparison to a threshold of interest such as 80% wall thickness. However, in ILI to field depth regressions, both the measured depths can have error. Thus, the underlying least squares regression assumptions are violated. Often one common result is a regression line that has a slope much less than the ideal 1-1 relationship. Reduced Major Axis (RMA) Regression is specifically formulated to handle errors in both the x and y variables. It is not commonly found in the standard literature but has a long pedigree including the 1995 text book Biometry by Sokal and Rohlf in which it appears under the title of Model II regression. In this paper we demonstrate the potential improvements brought about by RMA regression. Building on a solid comparison between ILI data and excavations provides the foundation for more accurate predictions and management plans that reliably provide longer range planning. This may also result in cost savings as the time between ILI runs might be lengthened due to a better analysis of such important data.
When it comes to managing the integrity of corroded pipelines, operators are confronted with many difficult decisions — one of which is the level of conservatism that is used in pipeline integrity assessments. The financial implications associated with excavation, repair, rehabilitation, and inspection programs typically balance the level of conservatism that is adopted. More conservative approaches translate into more spending, so it is important that repair strategies developed based on the integrity assessment results are effective. As integrity assessment methodologies continue to evolve, so does the ability to account for local conditions. One development in recent years has been the ability to evaluate multiple MFL in-line inspections to determine areas of active corrosion growth, through the combined use of statistics, inspection signal comparisons, and engineering analysis. The authors have previously outlined one approach (commonly known as Statistically Active Corrosion (SAC)) that has been successfully used to identify areas of probable corrosion growth, predict local corrosion growth rates, and maximize the effectiveness of integrity assessments.[1] Validation of the SAC-predicted corrosion growth rates is important for establishing confidence in the process. This is achieved through inspection signal comparisons, integrating close interval survey (CIS) results, and (when possible) field verification. The means by which these methods are used for validating the SAC method are described in this paper.
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