Dynamic risk analysis of high-sulfur wellhead gas-liquid separator based on Bayesian method

Key words:  event tree  accident precursor data  Bayesian method  fuzzy loss rate  dynamic risk analysis  separator

Abstract:

Traditional methods of quantitative risk analysis can 't effectively take advantage of operational status data of wellhead separator, and easily make assessment results deviate from the actual situation. The event tree model was established to simulate the progress of abnormal events of wellhead separator, and safety barrier failure probability and abnormal event consequence likelihood of wellhead separator were dynamically analyzed using accident precursor data based on Bayesian method. The fuzzy loss rate method was employed to quantify the consequence of the accident loss. Then dynamic risk analysis of wellhead separator was performed. The results show that the proposed method of dynamic risk analysis for wellhead separator overcomes the disadvantages of traditional risk assessment methods. It can dynamically assess accident probability and dynamically reflect risk change of the separator to provide references for risk analysis and control of high-sulfur wellhead gas-liquid separator and other related equipments.