System-Reliability Analysis by Use of Gaussian Fuzzy Fault Tree: Application in Arctic Oil and Gas Facilities

Abstract

Summary Reliability analysis has various application in oil- and gas-processing facilities, such as identifying the bottlenecks of the system, quantitative risk assessments, improving system availability and throughput capacity, spare-parts planning, and optimizing maintenance strategies. Reliability performance of a system can be described as a function of operation time and a series of operating conditions. For this purpose, a range of reliability data is required, on the basis of which the reliability function can be modeled. One of the challenges in reliability analysis of Arctic oil and gas facilities is lack of adequate reliability data. The available historical data gathered in normal-climate regions may not be appropriate because they do not include the effects of harsh Arctic operating conditions on equipment performance. In this study, the expert-judgement process is used as a tool to modify the mean time to failure of the equipment to include the adverse impacts of Arctic climate conditions on equipment performance. However, various sources of bias and uncertainties are involved in expert judgements. Fuzzy set theory is used to deal with such uncertainties and their propagation in both the component- and system-level analyses. For this purpose, a methodology is presented to perform a Gaussian fuzzy fault-tree analysis for system-reliability assessments. This methodology is further illustrated by a case study.