Pipeline river crossings are typically managed through a process of flood monitoring, ground inspections, risk assessments, and conducting of remediations.  The assessments conducted within this management approach require simplifications within the data that is collected during monitoring.  For example, the measured depth of cover is a timestamp that may vary with flow conditions; river bed soil type is often estimated based on bank observations; and software default values are often used during allowable span length calculations.  Moreover, assessments are often based on the current observations at the crossing, opposed to the potential conditions during flooding events.  Thus while conservative assumptions are usually applied, there would be benefit in developing a model that considers the potential ranges in crossing assessment inputs. 

A probabilistic model would enable combined consideration of all factors that contribute to the span failure threat, provide site rankings to support discrete mitigation prioritizations, allow for evaluation of whether a crossing is acceptable in regards to a risk target, and provide a ‘check’ to the hydrotechnical engineers visually based assessments.  This paper describes two models for estimating the pipeline probability of failure at river crossings.

The first model is a qualitative scoring-based model that is readily implementable by operators and consultants.  This model employs a weightings factor approach to consider the multiple factors that contribute to pipeline exposures and overstress.  A unique score for each crossing was established, and a relationship between score and probability of failure was determined by using the historical failure rates of similar crossings.

The second model is a more complex quantitative model that required: 1) Generation of a semi-quantitative model that estimates the likelihood of a crossing exposure occurring, 2) Identification of scour depth equations that may be applied to pipeline integrity management, 3) Development of a method for estimating scour lengths,  4) Updating of the Pipeline Research Council International (PRCI) model that assesses the allowable pipeline span length at river crossings, and 5) Development of a model that quantifies the probability that a span length longer than the critical span length could form.

The results from this project demonstrated that the site rankings correlated reasonably with those estimated by program managers, the scour depth and length prediction results were consistent with measured historical scours, and the pipeline probability of failure at the assessed river crossings were within expected ranges.


Model for Estimating the Probability of Failure at River Crossings

Division / Sponsors: 
Pipeline Systems Division

Paper Proceedings: https://asmedigitalcollection.asme.org/IPC/IPC2020/volume/84447

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