首页|A barrier risk-based evaluation model for drilling blowouts
A barrier risk-based evaluation model for drilling blowouts
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
Blowout is one of the most serious accidents in the drilling operation as it can lead to catastrophic consequences. The findings of blowout investigations indicate a chain of failures in Well Barriers (WBs) leading to a blowout. There is an urgent need to address the measuring of the performance of WBs and improve their safety to prevent blowouts. This study proposes a quantitative barrier risk-based evaluation model for drilling blowout using a set of WB performance indicators. The methodology of the proposed model is outlined in two sections. In the first section, policymaking, operational, personal, and mechanical factors are identified and described as WB performance indicators using a bow-tie approach. In the second section, the process safety performance indexing system in the chemical industries is developed for the management of maintaining integrity in WB indicators. In this section, a set of leading indicators are identified and proposed for the evaluation of WB performance. Finally, the safety benchmark of WB performance indicators is calculated comprehensively using a weighted aggregation approach based on the DEMATEL-based ANP (DANP) method. A blowout accident is used as a case study to show how this model can evaluate the level of drilling safety. The result of this study shows:(i) how DANP can be applied to determine the relative weight of WB performance indicators for the proposed model based on analyzing the interdependency among their indicators; (ii) how DANP is able to assist decision makers in selecting an influential strategy for the risk mitigation of a blowout; (iii) how the proposed approach can quantitatively model the performance of WBs from the well planning process to the drilling operation using leading indicators and (iv) how policymaking, as one of the main risk controlling factors described in this model, can be applied in improving the performance of process safety.
NSTL
Elsevier
