Integrity Maintenance of Petroleum Pipelines

Summary In this paper, a data-driven model is applied to derive optimum maintenance strategy for a petroleum pipeline. The model incorpo- rates structured expert judgment (classical model) to calculate the frequency of failure, considering various failure mechanisms. Opti- mization models are applied to derive optimum maintenance inter- vals for petroleum pipelines on the basis of the frequency of failure estimated. Two separate maintenance-optimization models are pro- posed. The first is a use-based optimization model that minimizes the expected total cost from a petroleum pipeline. The second is a benefit/cost (B/C) -ratio model that seeks to maximize the benefit derived from the pipeline, while minimizing operation and failure costs. The B/C-ratio model is less data intensive, and it has been used to optimize failure data obtained in the classical model. In this approach, the maintenance optimization is a further attempt at re- ducing the influence of subjectivity in maintenance decisions. the benefits of the approach is that the level of subjectivity in ex- pert judgment is reduced reasonably. This is because of the perfor- mance-based calibration of the experts used in the model. In other words, the inputs from the experts are used on the basis of the con- sistency of the experts during the elicitation process. In this paper, the frequency of failure because of rupture for an existing petroleum-pipeline system is determined. The pipe- line system is divided into three different segments on the basis of the uniqueness of physical and process parameters, and the prob- ability of failure for each segment is determined. Five failure mech- anisms are considered: external interference, corrosion, structural defects, operational errors, and minor failures. On the basis of the frequency of failure obtained using structured expert judgment, the expected cost of failure and maintenance cost for each of the pipeline segments can be determined. Furthermore, maintenance- optimization models are presented and applied to derive optimum maintenance intervals for the pipeline segments. The frequency of failure obtained in the classical model serves as an input to the op- timization model. The approach presented in this paper can be used both under limited data and when failure data are available. The findings of this research are very beneficial both academically and in the in- dustry. The expert-judgment study, for example, is capable of re- ducing the level of subjectivity inherent in expert-judgment-based decision making. In addition, the maintenance-optimization study will be very beneficial in maintenance planning, both to the pipe- line operator and the society at large. Moreover, the maintenance framework can be applied to existing pipelines and can provide an adequate benchmark for new pipeline installations. It is also hoped that the study can be extended to other production facilities. Study Data The case study is a petroleum pipeline that was commissioned in 1989, supplying petroleum products nationally. Some figures in the failure data of the pipeline have been modified slightly for con- fidentiality reasons. The pipeline has a diameter of 24 in., a total length of 340 km, with a design pressure and an operating tem- perature of 100 bar and 26.8°C, respectively. The material of the pipeline is fabricated from API5LX42 carbon steel, with a con- crete-type coating. The pipeline is basically located onshore, but connects to a compressor station located offshore. In the analysis, the entire pipeline is classified into three seg- ments (X1, X2, and X3), in line with its natural stretch. The clas- sical model is used to assess the frequency of failure for each pipeline segment. The failure parameters also can be used to ar- range the segments of pipeline into a hierarchical ranking of risk. The aim of the analysis is to obtain the frequency of failure for the pipeline, which could serve as input to integrity-maintenance initiatives. The analysis takes into consideration various failure mechanisms that may occur in any segment of a typical, onshore petroleum pipeline. To begin the classical model, six pipeline experts from the com- pany were invited and trained on the application of the model. A failure-data sheet for each pipeline segment was made available to