The ability to accurately determine the rate of corrosion growth along a pipeline is an essential input into a number of key integrity management decisions. For example, corrosion rates are needed to predict pipeline reliability (probability of failure and/or probability of exceedance) as a function of time, to identify the need for and timing of field investigations and/or repairs and to determine optimum re-inspection intervals to name just a few applications. As more and more pipelines are now being inspected using intelligent in-line inspection (ILI) tools for a second or even third or fourth time, pipeline operators require reliable guidelines for comparing repeat ILI data sets to obtain valid corrosion growth rates. Because of the measurement uncertainties associated with corrosion size estimated from a single ILI run, the corrosion growth rate calculated from consecutive ILI runs has a degree of uncertainty that needs to be considered in determining valid and accurate corrosion growth rates. The ratio between the measured corrosion growth and the measurement error is an important parameter in determining a meaningful distribution of the corrosion growth rate either when performing defect to defect comparisons or when comparing the defect populations in pipeline segments. When this ratio is small the associated uncertainty can be too large to make meaningful probabilistic inferences. As the ratio increases, the effect of measurement uncertainty becomes more manageable, allowing growth rate distributions to be calculated with reasonable confidence. This paper describes an approach to define the probability distribution of corrosion growth rates as a function of a simple parameter that characterizes the ratio between the ILI-observed corrosion growth and the ILI measurement error. This approach has been developed as part of an ongoing PRCI-sponsored research project to produce procedures for determining and validating corrosion growth rates from repeat ILI runs. The paper also provides examples using sample data from repeat ILI runs showing the application of these procedures, the treatment of measurement uncertainty, the resulting corrosion growth rate information that can be obtained and the associated level of confidence in the results.
Current risk assessment practice in pipeline integrity management tends to use semi-quantitative index-based or model-based methodologies. This approach has been found to be very flexible and provide useful results for identifying high-risk areas and for prioritizing physical integrity assessments. However, as pipeline operators progressively adopt an operating strategy of continual risk reduction with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels is becoming evident. Whereas reliability-based quantitative risk assessments can be and are routinely carried out on a site-specific basis, they require significant amounts of quantitative data for the results to be meaningful. This need for detailed and reliable data tends to make these methods unwieldy for system-wide risk assessment applications. This paper describes methods for estimating risk quantitatively through the calibration of semi-quantitative estimates to failure rates for peer pipeline systems. By applying point value probabilities to the failure rates, deterministic quantitative risk assessment (QRA) provide greater rigor and objectivity than can usually be achieved through the implementation of semi-quantitative risk assessment results. The method permits a fully quantitative approach to suit the operator’s data availability and quality, and analysis needs. The paper also discusses experiences of implementing this type of risk model in Pipeline Integrity Management System (PIMS) software and the use of and integration of data via existing pipeline geographical information systems (GIS).
Ultrasonic inline inspection (ILI) tools have been used in the oil and gas pipeline industry for the last 14 years to detect and measure cracks. The detection capabilities of these tools have been verified through many field investigations. ILI ultrasonic crack detection has good correlation with the crack layout on the pipe and estimating the maximum crack depth for the crack or colony. Recent analytical developments have improved the ability to locate individual cracks within a colony and to define the crack depth profile. As with the management of corroding pipelines, the ability to accurately discriminate active from non-active cracks and to determine the rate of crack growth is an essential input into a number of key integrity management decisions. For example, in order to identify the need for and timing of field investigations and/or repairs and to optimize re-inspection intervals crack growth rates are a key input. With increasing numbers of cracks and crack colonies being found in pipelines there is a real need for reliable crack growth information to use in prioritizing remediation activities and planning re-inspection intervals. So as more and more pipelines containing cracks are now being inspected for a second time (or even third time in some cases), the industry is starting to look for quantitative crack growth information from the comparison of repeat ultrasonic crack detection ILI runs. This paper describes the processes used to analyze repeat ultrasonic crack detection ILI data and crack growth information that can be obtained. Discussions on how technical improvements made to crack sizing accuracy and how field verification information can benefit integrity plans are also included.
Dent damage in pipelines may result from either impact damage caused by third parties or construction damage. Third party damage generally occurs on the upper half of the pipe (between the 8 o’clock and 4 o’clock positions) and has historically contributed to the highest number of pipeline failures. Dents caused during construction generally occur on the bottom half of the pipe and tend to be constrained by the indenter causing the dent, i.e. a stone or rock in the pipeline bed/backfill. However, all dents have the potential to cause an increase in stress in the pipeline, and consequently increase the pipeline sensitivity to both static and fatigue loading. Although there are extensive recommendations for the ranking and repair of dents, recently, failures of dents that are acceptable to pipeline codes have been reported. Guidance is therefore needed in order that operators can identify dents for which excavation and inspection is uneconomic and could potentially be damaging to pipeline safety and dents for which further action is required. This paper provides a review of the published recommendations for the treatment of pipeline dents and goes on to present a method that is being developed to determine the relative severity of dents in a pipeline using magnetic flux leakage (MFL) signal data. The proposed method involves measuring MFL signal parameters related to the geometry of the dent and relating these to high resolution caliper inspection data. This analysis enables a relationship to be established between the MFL signal data and dent depth and shape measurements. Once the model is verified, this analysis can then be used to provide a severity ranking for dents on pipelines where only MFL data is available.
The performance of older ERW pipelines has raised concerns regarding their ability to reliably transport product to market. Low toughness or “dirty” steels combined with time dependent threats such as surface breaking defects, selective corrosion and hook cracks are especially of concern in hazardous liquid pipelines that are inevitably subject to cyclic loading, increasing both the probability and rate of crack growth. The existing methods of evaluating seam weld flaws by hydrostatically testing the pipeline or In-Line Inspection (ILI) with an appropriate technology are well established. Hydrostatic testing, whilst providing a quantified level of safety is often impracticable due to associated costs, logistics and the possibility of multiple failures during the test. ILI technologies have become more sophisticated and as a result can accurately detect and size both critical and sub-critical flaws within the pipeline. However, the vast amounts of data generated can often be daunting for a pipeline operator especially when tool tolerances and future growth are required to be accounted for. For either method, extensive knowledge of the benefits and disadvantages are required to assess which is the more appropriate for a particular pipeline segment. This paper will describe advances in the interpretation of seam weld flaws detected by ILI and how they can be applied to an Integrity Management Plan. Signal processing improvements, validated by in-field verifications have enabled detailed profiles of surface breaking defects at seam welds for ERW pipelines to be determined. Using these profiles along with established fracture and fatigue analysis methods allows for reductions in the unnecessary conservatism previously associated with the assessment of seam weld flaws detected by ILI. Combining these results with other available data, e.g. dig verifications, previous hydrostatic testing records, enables more realistic and better-informed integrity and maintenance planning decisions to be made. A real case study conducted in association with a pipeline operator is detailed in the paper and quantifies the benefits that can be realised by using these advanced assessment techniques, to safely and economically manage their assets going forward.
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