Subsea blowout preventer (BOP) is safety critical equipment used in the drilling, completion and workover stages of offshore oil and gas wells. The BOP is the last line of defense against a blowout for the safety of the personnel, environment and rig while it also supports the nominal rig operations. Each component of the BOP fluid power system is a dynamic pathway from one to another; thus, a complete and thorough analysis of a BOP fluid power system component require an integrated system level approach for design, optimization, forensic analysis and condition monitoring.
In this dissertation, a physics-based system level modeling approach is presented for modeling the BOP fluid power system to assist design, testing, requirement validation and condition and performance monitoring (CPM). The process starts with the division of the BOP fluid power system into subsystems. Governing mathematical relationships based on physics and subsystem functionality are developed. The subsystem models are integrated to obtain system level models that are calibrated and validated using field data, and then they are called Virtual System. Presented is the use of the Virtual System for analyzing sealing performance of elastomer piston seals within an annular preventer in subsea conditions during nominal operation and for determining effects of boundary conditions over pipe ram preventer operation. The Virtual System for the pipe ram preventer is further simplified to obtain a CPM model, whose structure can employ signals measured on a subsea BOP by adapting its parameters with real time data. This adaptive CPM model is used for detection, isolation and quantification of the degradations within a pipe ram preventer fluid power circuit, and it is validated with field and Virtual System data. Based on the same approach, a CPM model for quantifying steady state fluid power system leakage methodology is presented.
A major benefit of the proposed approach over component-based analysis is that the developed Virtual Systems reflect performance under actual operating conditions with dynamic interactions, which might not be captured under static boundary conditions. Additionally, developed models are easily modified for additional purposes including CPM.Mechanical Engineering, Department o