Real Time Rainfall Monitoring for Pipeline Geohazards

Abstract

Oil and gas pipelines are subjected to multiple types of geohazards which cause pipeline failures (loss of containment); two of the most common types occur at watercourse crossings and at landslides. At watercourse crossings, the most common geohazard which causes pipeline failures is flooding during which excessive scour may result in the exposure of the buried pipeline and if the exposure results in a free spanning pipeline, then this may fail due to fatigue caused by cyclic loading from vortex-induced vibration. Fortunately the free span length and water velocity combinations that lead to failure can be defined and can be used to identify the flood discharge that should be monitored for in order to trigger actions to manage the hazard and avoid failure. Most watercourse crossings in a pipeline network are on ungauged watercourses and necessitate the use of a proxy gauged watercourse. The “proxy” gauged watercourse is used to infer whether flooding is occurring on the ungauged crossing, and the owner can take appropriate actions. Often the proxy gauged watercourse is too far away or the watercourse may not be representative of the crossing of concern (e.g. large difference in the drainage areas). Real-time rainfall data can be used in conjunction with streamflow monitoring to determine when extreme precipitation has occurred within the ungauged watercourses catchment which may result in flooding. Where pipelines cross landslide prone areas, large scale movements can be initiated, or slow on-going movement rates increased when extreme rainfall occurs. The definition of the extreme rainfall event for slope sites is the key component of providing a suitable warning of potentially dangerous conditions; shallow slides can be caused by short term events from sub-hourly to 3 day duration precipitation events whereas large deep seated (creeping) landslides can be driven by annual and intra-annual rainfall amounts. Monitoring of real time rainfall can be used to determine when extreme rainfall occurs at a landslide site. The density of in-situ weather stations collecting real-time rainfall data prevents the application along remote sections of pipeline routes and within large sections of Canada. Gridded real time rainfall from quantitative precipitation estimations which integrate a multiple data sources including in-situ, numerical weather prediction, satellite and weather radar, can be used to overcome this problem and provide warnings when pre-determined rainfall thresholds are exceeded on a site-specific basis.