The United Kingdom Onshore Pipeline Operators Association (UKOPA) was formed by UK pipeline operators to provide a common forum for representing operators interests in the safe management of pipelines. This includes providing historical failure statistics for use in pipeline quantitative risk assessment and UKOPA maintain a database to record this data.
The UKOPA database holds data on product loss failures of UK major accident hazard pipelines from 1962 onwards and currently has a total length of 22,370 km of pipelines reporting. Overall exposure from 1952 to 2010 is of over 785,000 km years of operating experience with a total of 184 product loss incidents during this period. The low number of failures means that the historical failure rate for pipelines of some specific diameters, wall thicknesses and material grades is zero or statistically insignificant. It is unreasonable to assume that the failure rate for these pipelines is actually zero.
However, unlike the European Gas Incident data Group (EGIG) database, which also includes the UK gas transmission pipeline data, the UKOPA database contains extensive data on measured part wall damage that did not cause product loss. The data on damage to pipelines caused by external interference can be assessed to derive statistical distribution parameters describing the expected gouge length, gouge depth and dent depth resulting from an incident. Overall 3rd party interference incident rates for different class locations can also be determined. These distributions and incident rates can be used in structural reliability based techniques to predict the failure frequency due to 3rd party damage for a given set of pipeline parameters.
The UKOPA recommended methodology for the assessment of pipeline failure frequency due to 3rd party damage is implemented in the FFREQ software. The distributions of 3rd party damage currently used in FFREQ date from the mid-1990s. This paper describes the work involved in updating the analysis of the damage database and presents the updated distribution parameters. A comparison of predictions using the old and new distributions is also presented.