In-line inspection (ILI) of the Trans Alaska Pipeline System (TAPS) using high resolution metal loss tools indicated 77 locations with suspected minor mechanical damage features (MDF). The tools used are able to detect the presence of a suspected feature, and measure indented dimensions, but are insufficient to detect the presence of cracks or gouges needed to reliably assess feature severity based solely on the ILI data. Excavations of 42 sites deemed most severe provided important field data characterizing residual deformation dimensions, the occurrence of gouges or cracks, and allowing a reliable field assessment of defect severity. Upon completion of the excavations, 35 possible MDF locations remained unexcavated. An engineering evaluation was undertaken to assess whether or not these remaining minor MDF pose a threat that is significant enough to warrant excavation. Multiple assessment methods were utilized including deterministic, probabilistic, and risk assessment methods. The probabilistic assessment of 35 unexcavated MDFs was performed using PCFStat; or Pressure Cycle Fatigue Statistical Assessment, which uses Monte Carlo simulation to estimate remaining fatigue life. PCFStat performs 1,000’s of simulations for each case where the input parameters are randomly selected from expected distributions. Of particular importance is the fatigue environment of the location. The results of the probabilistic assessment were used to estimate the potential for failure of remaining MDFs. The results suggest that 25 of 35 unexpected damage features had a POF of less than 10−4 over the remaining expected pipeline life cycle and thus are unlikely to fail. Alyeska considered a combination of probabilistic, deterministic and risk assessment results to decide on the actual locations to be examined. The results of probabilistic analysis also were found to support the outcome of the operator’s risk-based evaluation process.

Pipeline Operators employ two primary means of external corrosion monitoring on buried steel pipelines, Cathodic Protection (CP) Testing, and Corrosion In-line inspection (Smart Pigs). CP testing has been used to directly assess the level of cathodic protection in accordance with established criteria (NACE RP 0169). In-line inspection results have been traditionally used to determine integrity level by assessing remaining wall thickness and strength. In-line inspection results can also be used to indirectly assess the adequacy of Cathodic Protection by providing evidence that corrosion is active or not. A method has been developed to determine the presence of "Statistically Active Corrosion" based on a comparison of the moving average depth of wall loss features obtained by pig runs made in subsequent years. Evidence of active corrosion is an indicator that CP may not be adequate. This paper describes the statistically active corrosion methodology, and discusses how it can be used in making pipeline corrosion monitoring and maintenance decisions.

Pipeline operators prioritize metal loss features using in-line inspection tools (Smart Pigs). In-line inspection results have traditionally been used to directly assess remaining wall thickness and remaining strength. Pipeline Safety regulations are beginning to require more comprehensive Integrity Management Plans, especially in High Consequence Areas. One method has been developed to address risk factors which the author feels will meet both the Department of Transportation’s requirement for “Prioritizing Risk Factors” and The American Petroleum Institute’s Proposed RP 1160, “Methodology for Evaluation of In-line Inspection Data. This Integrity Management Program has provided the pipeline operator with a high degree of confidence of long-term safety and service.

Pipeline Cathodic Protection (CP) projects are traditionally implemented to provide hot spot protection where needed based on CP monitoring data and to comply with regulatory criteria. In today's competitive environment, operating company management additionally demands that proposed CP projects be justified economically. In-line corrosion inspection (corrosion pig) data can be used to predict potential future corrosion maintenance that would occur under alternative scenarios, both with and without additional CP. An economic analysis can then be used to determine if expected benefits of proposed CP projects outweigh costs. This paper describes methods used on the Trans Alaska Pipeline System (TAPS) for predicting future corrosion maintenance using in-line inspection data, in addition to CP monitoring data, and evaluating the economic impact of proposed CP projects. An example is presented to illustrate the method used.

In-line inspection of underground pipelines for corrosion damage using smart pigs is now quite common. With the advent of high-resolution pigs that can identify large numbers of potential anomalies, more sophisticated methodologies are required for interpreting the results of an in-line inspection. Of particular interest is the probability that the depth of corrosion in a particular location exceeds a critical depth defined by the local pipe characteristics and maximum operating pressure. In this paper, a Bayesian statistical methodology for determining the probability that corrosion exceeds critical magnitude is presented. The estimated probabilities (from the posterior distribution) are based on an assumed pit depth distribution (the prior distribution), the pig call data produced by the in-line inspection (the data), and the detection and depth accuracy performance characteristics of the pig utilized (the data model). The resulting exceedance probabilities can be used with or without corrosion consequences to make inspection/maintenance policy decisions.

Alyeska Pipeline Service Company (APSC) operates the Trans Alaska Pipeline System (TAPS) for transporting crude oil 800 miles from Prudhoe Bay to Valdez. Approximately 420 miles of the pipeline is above ground and 380 miles is below ground. In-line inspection results have indicated external corrosion on portions of the below ground pipe. APSC uses periodic in-line inspections to identify, monitor, and remediate the corrosion. Results of these surveys are used to determine the presence and magnitude of corrosion by sensing a signal (either MFL or UT) produced by the metal loss anomalies. An ideal tool would be able to: detect all corrosion regardless of size, assess the actual corrosion with no measurement errors, and produce no false corrosion indications. Real in-line inspection tools exhibit varying capabilities to detect, measure, and assess corrosion on an operating pipeline. It is essential for the pipeline operator to known how reliable each tool is in order to respond in a manner which prevents a failure from excessive metal loss. Rigorous analysis of three of Alyeska`s more recent inline surveys have provided the essential performance measures to facilitate a satisfactory response plan. These performance measures were evaluated by comparing measurements of the actual corrosion (obtainedmore » from 314 excavations) to results provided by three pig runs selected for presentation in this paper.« less

The ability of a corrosion pig to reliably detect, measure, and assess corrosion that could adversely affect pipeline integrity is its most important performance attribute. Objective knowledge of the performance limitations of in-line inspection tools (commonly referred to as pigs) under real operating conditions is the key to subsequent decision making based on pig results.