Early Warning Analysis of Oil-Gas Field Equipment Failure Based on Statistical Model of Failure Rate

Abstract

This paper proposed a method used to estimate mechanical equipment failure for oil-gas field enterprises. First, this method established a mixed failure distribution model of mechanical equipment modules. According to the collected statistical data of module defect, this method then applied MLE (Maximum Likelihood Estimation) algorithm and EM algorithm to calculate the mixed failure distribution parameters of mechanical equipment modules, so as to form the mixed distribution function of failure rate. The feasibility of this method was verified through examples. At last, the concept of risk early warning management for mechanical equipment failure was proposed based on the estimated distribution function of mechanical equipment failure rate. As a result, there are scientific grounds for the equipment maintenance & repair cycle regulated by grass-roots staff and the equipment replacement & scrapping strategy set by management-level users.