A methodology for risk-based inspection planning of oil and gas pipes based on fuzzy logic framework

摘要

In an efficient and effective pipe integrity management programme, maintenance engineers often use the risk-based inspection (RBI) and maintenance strategy. Unfortunately, the calculation of risk is a daunting task because in order to calculate the risk of failure, a maintenance engineer needs to predict the rate of growth of a defect, the effect of the defect on the integrity of the structure and the consequence of failure. Unfortunately precise calculation for either of these parts is quite difficult. Fuzzy logic is a mathematical tool suitable for handling imprecise information in the real world. The benefit of this approach lies in its ability to include personal experiences along with acceptable deterministic models in the calculation. The structure of the model also allows easy calibration of the model to suit a particular plant condition. This approach can thus help to reduce the dependence upon the precise data, allow modelling even when a phenomenon is incompletely understood, and reduce the difficulties arising due to the complex computation required by more traditional methods. This paper presents a proposed methodology, based on fuzzy logic framework, for the establishment of an RBI programme for pipes. The paper also presents in detail a section of the methodology that can be used for calculating the estimated rate of CO_2 corrosion in carbon steel pipes. In this technique the plant operating parameters (temperature, gas and liquid flow rates, total pressure, CO_2 partial pressure and pH) are taken as fuzzy variables and used to calculate the Predicted Rate of Corrosion. The inspected rate of corrosion and the efficiency of inspection are also considered as fuzzy variables and are used to calculate Trust in Inspection Results and Trust in Predicted Results. By combining all the modules an estimated rate of corrosion is calculated. This estimated rate of corrosion can then be used for developing the risk-based inspection programme.