Risk assessment of oil and gas drilling operation: An empirical case using a hybrid GROC-VIMUN-modified FMEA method

Abstract

The failures of drilling operation in oil and gas fields may cause big economic losses owing to several technical consequences such as safety incidents, machinery damages, environmental impacts, etc. To prevent unwelcome events in drilling activities, it is necessary to assess and reduce the potential related risk factors. Hence, the present paper offers a framework to diagnose and analyze drilling operation risk factors in one of the Iranian gas field, located in the south area of the country. The proposed methodology consists of four main stages: providing knowledge sources, risk identification, general risk analysis, and estimation of wellbores overall risks. This framework helps to ensure the successfully performance of drilling companies, and to access safety standards. An improved version of the FMEA method (Failure Mode and Effects Analysis), named as modified FMEA, is suggested by adding risk controllability criterion. Further, a generalized version of the ROC method (Rank Order Centroid) is developed. This method is used to estimate the weights of any ranked entities. Moreover, a new idea called VIMUN (Vital, Important, Medium, Unimportant, and Negligible) is proposed to deal with weighting problems when there are many number of entities to be weighted. A hybrid of the modified FMEA, GROC, and VIMUN methods is used for evaluating the risk factors in the field, and for determining the level of overall risk of each wellbore. The results show that the lost circulation of drilling fluid caused by high density of natural fractures in formation, and lack of advanced technology has the highest priority, and is the most serious failure in drilling operation in the field under study. The failures at the next ranks are drilling rig fire & explosion, well blowout, and wellbore instability. Using the proposed methodology, 36 wellbores in the field are grouped into five classes according to their levels of risk. The robustness of the results was confirmed by carrying out a sensitivity analysis.