Comparative Study of Failure Consequence Assessment of Oil Pipelines Based on Quantitative Risk Assessment and Gray Relational Analysis

Large cities have high population density and complex oil pipeline distribution. Failure consequence assessments for each pipeline help optimize maintenance schedules, ensure safe operation, minimize costs, and enhance economic benefits for operators. Based on field surveys, this study processed and filtered the obtained data. A locally developed quantitative risk assessment (QRA) method was used to assess the failure consequences of the pipelines. In addition, linguistic values were converted, some parameters were adjusted, and gray relational analysis (GRA) was applied to assess the failure consequences further. The advantages and disadvantages of these two methods are discussed in terms of their practical applications. The results of the QRA analysis indicated that the leakage rate of the assessed pipeline segments ranged from 47.0 to 223.2 kg/s, and the ignition probability ranged from 2.0% to 5.2%. The probability of occurrence varied between 2.13×10−6 and 10.22×10−6 events/year, and the number of fatalities ranged from 0 to 2.5. The failure probability was classified as Level 1, and the failure consequence severity ranged from A to C. The societal risk is considered to be acceptable. The results of the GRA analysis showed that the gray relational degree of the pipeline before adjustment ranged from 0.54 to 0.83, whereas after adjustment it ranged from 0.44 to 0.86. The failure consequence severity was classified between Levels A and C. Finally, the similarities and differences between the QRA and GRA results were analyzed, and corresponding risk mitigation measures are proposed. The study shows that the QRA method takes into account more variables, and provides precise results; however, it requires a significant amount of time for data collection and processing. In contrast, the GRA method uses fewer data, and offers faster calculation speeds. Companies should combine both risk assessment methods to ensure accuracy, reduce costs, and maximize benefits.