Holistic Systems Analysis: A Case Study Demonstrating Simple Models Improving the Reliability of the BOP Control Equipment Ecosystem

Abstract

Abstract Owing to their complexity and lack of system level data, subsea BOP control system design has historically focused on the component level design and analysis. When system level design and analysis is considered, it is often performed at assumed steady state conditions and without a detailed knowledge of end-user operating conditions. The interaction of multi-domain dynamically coupled systems can result in unintended system level behavior, including field performance issues and system failure. The timely resolution of these field performance issues is of critical concern as rig non-productive time (NPT) can cost operators of floating rigs in excess of USD 15 thousand per hour [1]. The current approach to resolving field performance issues typically involves replacement of the failed component or over-engineering to improve robustness at the expense of cost, weight, and efficiency. However, as the industry pushes for cost reduction and increased reliability, solutions must meet more than fit, form, and function; a holistic approach to solving field performance issues must be developed to ensure original equipment manufacturers (OEMs) and operators collaborate together to treat not only the "symptoms" of equipment failure, but also address the underlying system "disease". In this work, a case study is presented of a low-order mathematical model of a hydraulic control circuit and its utility as a heuristic for rapidly testing and optimizing solutions to address field performance failures resulting from pressure transients in a real world hydraulic control circuit. A low-order model of hydraulic control circuit was created using a multi-domain lumped parameter approach and replicated the pressure transients detailed in field performance reports, which caused repeated catastrophic failures, e.g. burst inlet/outlet piping, cracked fittings, etc., of the pressure reducing valve. The model was then subjected to a sensitivity analysis to determine dominating input variables, and through repeated iterations of potential solutions, converged to a high-confidence solution. The high-confidence solution and technical justification from the model were presented to operators for feedback and implementation, and the field verification results are detailed in this paper. The deep system level understanding provided by the model aided in consensus building between OEM and operator. Additionally, the results of the model yielded insight to system level communication failures at the organizational level between operator and OEM. Currently, there is a dearth of techniques for analyzing and troubleshooting field performance issues. The case study described here demonstrates the value of new technological tools for understanding system failures and developing solutions to minimize rig NPT.