An Integrated RBI Risk Evaluation Methodology Combining Cloud Algorithm with Structural Entropy Weighting Method

Abstract In recent years, static equipment accidents occur frequently in shallow shale gas station, and the risk status of many static equipment is unknown, so it brings great potential danger to the safe operation and property safety of the station. Therefore, this paper constructs a special risk assessment index system and scoring guidelines for shallow shale gas stations based on historical failure data and actual hazard sources. Aiming at the uncertainty and error problems in the assessment process, an integrated RBI risk assessment methodology based on the cloud algorithm and the structural entropy weighting method is proposed, in which the cloud algorithm can describe the uncertainty in the RBI risk assessment. The structural entropy weighting method fully considers the error in the index importance ranking. Finally, combining the economic losses caused by different static equipment shutdowns, the corresponding risk matrix levels are formed, and the detection strategies under different risk levels are proposed. The proposed RBI risk assessment model is applied to Sun Shale gas station, and its assessment results are in line with the actual situation on site.