Availability analysis of subsea blowout preventer using Markov model considering demand rate

다국어 초록 (Multilingual Abstract)

Availabilities of subsea Blowout Preventers (BOP) in the Gulf of Mexico Outer Continental Shelf (GoM OCS) is investigated using a Markov method. An updated ${\beta}$ factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the ${\beta}$ factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym) method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs) and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.