A framework for developing leading indicators for offshore drillwell blowout incidents

作者：Tamim Nafiz; Laboureur Delphine M; Mentzer Ray A; Hasan A Rashid; Mannan M Sam^*

来源：Process Safety and Environmental Protection, 2017, 106: 256-262.

DOI：10.1016/j.psep.2017.01.005

• Leading indicators
• Risk metrics
• Offshore blowouts
• Risk assessment
• Kick prediction
• Case study
• Decision support algorithm

Offshore operations have always been very challenging due to technological and operational complexities in combination with harsh environmental conditions. Geological uncertainties, high pressure flammable fluids in the presence of ignition sources, complicated structural layouts, limited response time allowance, difficulty of control and communication are some of the critical factors that pose clear threats toward safe operations and may result in high consequence events, e.g., blowouts. Developing well specified risk indicators is difficult due to such highly correlated factors and multifaceted operations. Leading indicators, which are able to identify critical events that could lead to high consequence events, have proven to be an effective tool that can help the operators in their decision making to react earlier to an event and to reduce the risk of an incident. Most of the research dedicated to leading and lagging indicators are applicable to the petrochemical industry, and there is not yet an agreement on a definition and classification of leading indicators for drilling related blowouts. This paper discusses the approaches of different organizations and institutes on leading indicators characterization and development. The drilling industry is compared with the aviation industry to identify potential elements for developing a comprehensive leading indicators framework. A workable definition of leading indicators is proposed considering the intricacy of offshore operations. Leading indicators are broadly categorized into two classes which are further segmented into different groups. Proposed categorization is analyzed with a blowout case study and simple decision support algorithms are proposed for predicting kick which is a major precursor to blowouts.

• 出版日期2017-2