Abstract
Assuring the reliability of crude unit pipelines in the downstream oil and gas industry is highly essential since unexpected failures of these pipelines can result in a number of negative impacts to the business, including safety, environmental, and economic impacts. The objective of this work is to understand the degradation behavior of the piping system so we can know in advance when the degraded pipeline will reach the minimum thickness threshold.
The damage mechanisms in atmospheric crude tower overhead piping has been well researched. Hydrochloric Acid (HCL) corrosion is one major type of damage mechanisms seen in the atmospheric crude tower overhead piping. This type of corrosion is time-dependent and also influenced by different operational conditions such as temperature, adequacy of the neutralization of the formed HCL and pipeline interior protection using corrosion inhibitors. To better monitor the degradation of these pipelines and to reduce cost associated with scheduled inspections, a number of refineries are resorting to real time thickness monitoring using Ultrasonic instruments mounted at vantage locations on the pipeline, to provide continuous, non-destructive corrosion and erosion monitoring.
The focus of this paper is to use a stochastic degradation model, which is suitable for characterizing wall thickness degradation data, to estimate the failure probability of the pipeline in the midst of inadequate data. We model the degradation of the crude overhead pipeline using a stationary Gamma process. To capture the substantial heterogeneity among different thickness monitoring locations on the pipe line, random effects are incorporated in our stochastic degradation model. We illustrate the proposed random effect method using the gamma process to model pipe wall thickness degradation data observed over a period.