GIS based Spatial Risk Assessment for Natural Gas Pipelines
Proceedings Publication Date
Presenter
Yogin Gajjar
Presenter
Author
Yogin Gajjar
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Abstract

Risk identification and assessment are essential for effective pipeline safety and integrity management. Using risk and/or likelihood of failure evaluation, pipelines are prioritized for physical assessment and for implementation of preventive and mitigative measures. The risk-analysis process is data-intensive. Substantial information is required to describe the pipeline facility, its construction, its operation and the environment through which it is routed. Numerous options exist for the collection, storage, management and maintenance of this data. In this paper, Pipeline risk assessment has been done using GIS-based Spatial Risk Assessment and overlaying the information layers. For this purpose, all effective threat factors were identified and projected. In order to achieve the same risk was calculated at each interval, and substantial calculations are performed for consequences, the total likelihood of failure and total risk. Total likelihood of failure is the sum of all the threat factors, while total risk is the total probability of failure multiplied by the consequence factor. The likelihood is a measure of threats to the pipeline while the Consequence is typically the impact of a failure on public safety, with additional considerations of the environment or the business. Spatial Risk assessment enables to take input of different threat factors such as Structures Unit Counts for generation of Pipeline Risk Radius, Unauthorized encroachments for identifying potential mechanical damage, Habitat Structures Density for indicating risk level along the pipeline and External/Internal Corrosion for indicating corrosion threats to pipeline. Finally, the result of threat factors shall be captured and pipeline risk scores are generated and visualized over pipeline GIS database. In addition, the GIS provides powerful spatial analysis tools that allow risk management specialists to better understand and model the complex spatial relationships and interactions that contribute to individual threats and overall risk.

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