Subsea Blowout Preventer (BOP): Design, Reliability, Testing, Deployment, and Operation and Maintenance Challenges

Subsea blowout preventer (BOP) is a safety-related instrumented system that is used in underwater oil drilling to prevent the well to blowout. As oil and gas exploration moves into deeper waters and harsher environments, the setbacks related to reliable functioning of the BOP system and its subsystems remain a major concern for researchers and practitioners. This study aims to systematically review the current state-of-the-art and present a detailed description about some of the recently developed methodologies for through-life management of the BOP system. Challenges associated with the system design, reliability analysis, testing, deployment as well as operability and maintainability are explored, and then the areas requiring further research and development will be identified. A total of 82 documents published since 1980's are critically reviewed and classified according to two proposed frameworks. The first framework categorises the literature based on the depth of water in which the BOP systems operate, with a sub-categorization based on the Macondo disaster. The second framework categorises the literature based on the techniques applied for the reliability analysis of BOP systems, including Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Reliability Block Diagram (RBD), Petri Net (PN), Markov modelling, Bayesian Network (BN), Monte Carlo Simulation (MCS), etc. Our review analysis reveals that the reliability analysis and testing of BOP has received the most attention in the literature, whereas the design, deployment, and operation and maintenance (O&M) of BOPs received the least

Availability analysis of safety critical systems using advanced fault tree and stochastic Petri net formalisms

Failure scenarios analysis constitutes one of the cornerstones of risk assessment and availability analysis. After a detailed review of available methods, this paper identified two distinct formalisms to analyze failure scenarios and systems availability: generalized stochastic Petri nets (GSPN) and Fault tree driven Markov processes (FTDMP). The FTDMP formalism is a combination of the Markov process and the fault tree. This aims to overcome fault tree limitations while maintaining the use of deductive logic. The GSPN is a Petri net with probabilistic analysis using Monte Carlo simulation. The effectiveness of both methods is studied through an emergency flare system including a knockout drum. It is observed that GSPN provides a robust and reliable mechanism for accident scenario analysis. It provides additional information such as events frequencies at operating and failing modes and expected occurrence timing and durations resulting from different complex sequences. Even for multi-state variables which could be used to design a safety management system. Although FTDMP is a powerful formalism, it provides limited information