Luc Huyse

EFFECTS OF INLINE INSPECTION SIZING UNCERTAINTIES ON THE ACCURACY OF THE LARGEST FEATURES AND CORROSION RATE STATISTICS

With the increased acceptance of the use of probabilistic fitness-for-service methods, considerable effort has been dedicated to the estimation of the corrosion rate distribution parameters. The corrosion rate is typically computed from the difference in anomaly size over a specific time interval. The anomaly sizes are measured through either in-line inspection or direct assessment. Sizing accuracies for inline inspection methods are reasonably well established and in many cases the sizing uncertainty is non-negligible. In many approaches that are proposed in the literature the time-averaged corrosion rates are computed without explicitly considering the effect of the sizing uncertainties and as a result considerable interpretation and engineering judgment is required when estimating corrosion rates. This paper highlights some of the effects of the sizing uncertainties and the resulting biases that occur in the subsequent reliability calculations. These assessments are used to determine the most appropriate course of action: repair, replacement, or time of next inspection. The cost for repair or replacement of subsea pipelines is much higher than for onshore pipelines. For subsea applications, it is therefore paramount that the risk calculations, and therefore the corrosion rate estimates, be as accurate as possible. In subsea applications, the opportunity to repair individual defects is often limited due to practical constraints and there is merit in an approach that focuses on entire spools or pipeline segments. The proposed statistical analysis method is ideally suited to this application although the principles behind the analysis apply equally well to onshore lines subject to either internal or external corrosion threats.Copyright

WHY RELIABILITY-BASED APPROACHES NEED MORE REALISTIC CORROSION GROWTH MODELING

Deterministic design and assessment methods are by definition conservative. Although no claim is made regarding the actual reliability level that is achieved using deterministic, i.e. safety-factor based approaches, the safety factors have been selected such that generally sufficient conservatism is maintained. Reliability-based methods aim to explicitly quantify the aggregated conservatism in terms of probabilities or risk. Accurate reliability estimates are not possible without accurate computational prediction models for the limit states and adequate quantification of the uncertainties in both the inputs and model assumptions. Although this statement may seem self-evident, it should not be made light-heartedly. In fact, just about every analysis step in the pipeline integrity assessment procedures contains an inherent, yet unquantified, level of conservatism. One such example is the application of a “maximum” corrosion growth rate that is constant in time. A reliability-based framework holds the promise of a more consistent and explicitly quantified safety level. This ultimately leads to higher safety efficiency for an entire pipeline system than under safety factor based approaches. An accurate prediction of the true likelihood of an adverse event is impossible without significant research into determining and understanding the, usually conservative, bias in the engineering models that are currently employed in the pipeline integrity state-of-the-practice. This paper highlights some of the challenges that are associated when porting the “maximum corrosion rate” approach used in a deterministic approach to a reliability-based paradigm. Issues associated with both defect and segment matching approaches will be highlighted and a better corrosion growth model form will be proposed.

Improvements in the Accurate Estimation of Top of the Line Internal Corrosion of Subsea Pipelines on the Basis of In-Line Inspection Data

The cost for repair or replacement of subsea pipelines is much higher than for onshore pipelines. To a large extent, the repair or replacement decision hinges on the outcome of fitness-for-service analyses that are in turn based on the results of in-line inspections. It is therefore of utmost importance to obtain in-line inspection data that are as accurate as possible. It has been reported in the literature that MFL tools may significantly exaggerate the localized wall loss for wet gas lines subject to top of the line corrosion. This paper reports the results of a study on a Chevron asset that was initiated to compare the performance of various inspection methods. Upon completion of the in-line inspections, a section of the pipeline was recovered off the ocean floor and subsequently replaced. The defect population of the recovered pipeline section together with the high-definition automated ultrasonic testing (AUT) results built the reference of the performance test of several inline inspection techniques like magnetic flux leakage (MFL), ultrasonic (UT) and a recently developed technology for accurate measurement of shallow internal corrosion (SIC) that is based on eddy current (EC) technology. The improvements in defect sizing that resulted from this investigation are reported.Copyright

Pragmatic Approach to Estimate Corrosion Rates for Pipelines Subject to Complex Corrosion

Corrosion is a common degradation process for most oil and gas pipelines in operation that can lead to leak and rupture failures. To avoid failures due to corrosion, integrity management plans for pipelines require fitness-for-service (FFS) assessments and remaining life analysis of the corrosion features that are detected by in-line inspections (ILIs). The objective of the present paper is to support the deterministic integrity and remaining life assessment of pipelines by introducing a pragmatic approach for the determination of corrosion rates from two inspections. The proposed approach is primarily tailored towards upstream and subsea pipelines that are subject to very high density internal corrosion rather than transmission pipelines with low to moderate densities of external features.ILI data may be subject to significant measurement errors and feature matching for two ILIs can become highly unreliable if high-density corrosion is present. To address these uncertainties, the backbone of the proposed approach is to focus on corrosion clusters rather than individual corrosion pits and a filtering process is utilized to identify true corrosion growth. The introduced approach is supported by theoretical knowledge and practical experience. The approach can be easily executed in spreadsheet software tools without the application of advanced statistical and probabilistic methods for the deterministic remaining life assessment in practice.Copyright

Bayesian approach to estimate corrosion growth from a limited set of matched features

Corrosion is a time-dependent hazard for pipelines that gradually decreases the resistance of pressure containment. The corrosion growth can be inferred from a set of matched corrosion features observed in two successive in-line inspections. Experience shows that the measured corrosion growth between two inspections has often a mean value around zero and, usually, nearly half of the matched features have negative measured growth. Negative growth values are physically impossible as the underlying true corrosion process has strictly non-negative corrosion growth increments. In this paper, a Bayesian probability model is presented to estimate the actual corrosion growth conditional on the observed growth from a set of matched corrosion anomalies. The model assumes independence between sizing error and true feature depth and produces a strictly non-negative corrosion growth process that explicitly accounts for non-growing features. An Empirical Bayes approach is used to determine the prior distribution of the corrosion growth. The key findings in this paper are (1) the variance of the actual corrosion growth process is less than the observed variance of the direct measurements, (2) the upper percentiles of the posterior corrosion growth distribution may be lower than the direct measurements, and (3) the posterior distribution of the corrosion growth is non-negative. A numerical example is provided.

PROVIDING SAFETY - USING PROBABILISTIC OR DETERMINISTIC METHODS

The primary objective of a good engineering design or maintenance process is to provide safety with optimized resources. Most parameters and models used in engineering have uncertainty — some more so than others. Probabilistic assessments strive to account for these uncertainties explicitly while the deterministic methods account for uncertainties implicitly by using conservative inputs and safety factors. Deterministic methods are preferred by many due to their simplicity. However if inputs and safety factors are not defined prudently with explicit consideration for uncertainties and consequences they can lead to unsafe or unduly conservative solutions.The main objective in using reliability based methodologies is to provide consistent safety by explicitly accounting for uncertainties in a probabilistically quantified manner. Reliability methods also allow the articulation of the level of safety. This level of consistency in safety cannot be achieved in a deterministic analysis using safety factors because uncertainties are not accounted for explicitly and consequently the uncertainties lead to variable solutions. However safety factors can be calibrated using reliability methods so that more consistent safety levels can be assured when using deterministic methods.There is a relationship between the reliability level and the deterministic safety factors. This relationship between reliability levels and deterministic safety factors is examined both from a mathematical and practical perspective. Consequently it is shown that reliability based methods can be used to calibrate deterministic methods to improve the consistency of the safety level with due consideration to underlying uncertainties and consequences. This kind of calibration is used in other industries such as structural design and nuclear facilities. Providing more consistent safety enables optimization of maintenance activities which enables the safest system to be provided with available resources.Currently the pipeline industry uses deterministic methods with conservative inputs that are not based on risk or safety principles. Consequently there is a large variation in the inputs and safety factors used in the industry. Some examples of these are safety factors used in response to inline inspection that vary from the reciprocal of the design factor to 1.1 for all location classes.This paper shows that the maximum safety factor achievable for a given design is defined by the original design factor and the ratio between flow stress and yield strength. It also shows the inadequacy of using safety factors that are not risk based. The paper focuses on the importance of using a sound risk based rationale for appropriate safety factors in deterministic methods.A glossary of terms is provided at the end of the introduction.Copyright

Types of Uncertainty and Their Impact on Target Risk or Reliability

The main objective in using reliability based methodologies is to provide consistent safety by explicitly accounting for uncertainties in a probabilistically quantified manner. Reliability methods also allow the articulation of the level of safety. This level of consistency in safety cannot be achieved in a deterministic analysis using safety factors. However, reliability based methods can be used to calibrate and improve deterministic methods to improve the consistency of the safety level. Providing consistent safety enables optimization of maintenance activities which enables the safest system to be provided using the available resources. Currently used deterministic and reliability based methods are both examined and discussed. Gaps and areas of improvement are identified with the objective of improving safety and explicitly articulating and communicating the level of safety.Effective use of quantitative risk and reliability methodologies requires quantitative data that describes the current state of the pipeline, the anticipated future state as well as the failure limit state. In maintaining oil and gas pipelines this level of quantitative data of the pipeline is available when pipelines are in-line inspected. Although reliability-based assessments are by no means restricted to corrosion management, the reliability based maintenance program at Pipeline Research Council International (PRCI) has been foremost applied to corrosion management because in-line inspection (ILI) data is adequately accurate to perform reliability based assessments. Guidelines for a reliability based maintenance program have been developed and projects executed to validate and demonstrate the implementation of these methodologies. The main learning from these guidelines and subsequent validation projects has been useful in identifying the process for improving integrity related decision making, the sensitivities of these methodologies, the impact of physical uncertainty and knowledge uncertainty, and the challenges in defining and applying target criteria. These identified areas are explored and discussed.Copyright