Monitoring corrosion and materials degradation using probes/sensors is a practical means of acquiring in-situ and site-specific data from ‘invisible’ underground structures such as oil & gas pipelines for the early warning of structural failure and the prediction of asset life. A difficulty in corrosion monitoring is the design of suitable corrosion probes for acquiring localized corrosion and materials degradation data from complex buried pipeline conditions. This paper provides an overview of some of recent progresses in this area and a brief discussion on future prospects. Several cases are presented to illustrate our approaches to monitoring and visualizing localized corrosion of buried steel under the effect of dynamic anodic transients; coating disbondment under overprotection potential; and localized corrosion under a simulated pipeline coating.


The lack of visibility of corrosion and material degradation processes occurring on underground pipelines is believed to be a major contributor to corrosion induced oil & gas pipeline accidents including the oil pipeline explosion occurred in the Chinese city of Qingdao, killing 62 people and wounding 136, and a similar explosion in Taiwan caused 32 deaths and 321 injuries 1-3. These incidents clearly indicate the extreme consequences of structural failure and the need to ensure the safety, reliability and durability of these ‘invisible’ assets. A major problem in today’s management of these assets is the lack of sufficient corrosion and materials degradation data required for the effective management of these assets. Traditionally historical field inspection data are used as the main source of knowledge for forecasting the degradation and service lives of underground structures. The most common approach to collecting corrosion and materials degradation data from buried oil and gas pipelines is through excavation and inline inspection using various pipeline inspection techniques such as Direct Current Voltage Gradient (DCVG) survey, ultrasonic scanning and radiography. Based on these techniques, equipment known as a ‘pig’ (structure inspection gauge) has been developed for internal inspection of pipes. The ‘pig’ follows the flowing medium in the structure and records corrosion related data for analysis after it is removed from the pipe. A review of major methods for inspecting and monitoring external corrosion of on-shore transportation pipelines and for measuring coating disbondment has been presented in references 4,5. All these corrosion and coating inspection techniques are useful in pipeline corrosion and coating degradation data acquisition; however they are able to detect corrosion only when sufficient damage has occurred to cause an accumulated change in the bulk material properties. These field inspection techniques are often expensive (e.g. pigging of a pipeline can cost $1million or more). Field corrosion inspections occur relatively infrequently (e.g. pigging of a pipeline is usually done only every 5-15 years), usually coinciding with routine shutdown and maintenance, and therefore peak corrosion rates and materials degradation are often not detected. Traditional methods of visualizing and interpreting corrosion data are usually computer software developed based on historical field inspection data and probabilistic asset management models 6-9. These asset management tools are useful in providing an overall assessment of the aging of a structure; however the success of these tools is heavily dependent upon the availability and reliability of structural condition data. These models are often not suitable for infrastructural systems that are under localized corrosion attack and that are under the effect of dynamically changing environmental conditions. This is because under these circumstances corrosion and materials degradation are significantly affected by local environmental parameters, as well as dynamically changing stray currents, coating disbondment and cathodic shielding phenomena.

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