A novel engineering framework for risk assessment of Mobile Offshore Drilling Units

Abstract

Natural oil and gas has become one of mankind’s most fundamental resources. Hence, the performance of mobile offshore drilling units (MODUs) under various conditions has received considerable attention. MODUs are designed, constructed, operated, and managed for harsh geographical environments, thus they are unavoidably exposed to a wide range of uncertain threats and hazards. Ensuring the operational safety of an MODU’s system is often a complex problem. The system faces hazards from many different sources which dynamically threaten its integrity and can cause catastrophic consequences at time of failure. The main purpose of this thesis is to propose a methodology to improve the current procedures used in the risk assessment of MODUs. The aim is to prevent a critical event from occurring during drilling rather than on measures that mitigate the consequences once the undesirable event has occurred. A conceptual framework has been developed in this thesis to identify a range of hazards associated with normal operational activities and rank them in order to reduce the risks of the MODU. The proposed methodology provides a rational and systematic approach to an MODU’s risk assessment; a comprehensive model is suggested to take into consideration different influences of each hazard group (HG) of an offshore system. The Fuzzy- analytic hierarchy process (AHP) is used to determine the weights of each HG. Fault tree analysis (FTA) is used to identify basic causes and their logical relationships leading to the undesired events and to calculate the probability of occurrence of each undesirable event in an MODU system. The BBN technique is used to express the causal relationships between variables in order to predict and update the occurrence probability of each undesirable event when any new evidence becomes available. Finally, an integrated Fuzzy multiple criteria decision making (MCDM) model based on the Fuzzy-AHP and a Fuzzy techniques for order preference by similarity to an ideal solution (TOPSIS) is developed to offer decision support that can help the Decision maker to set priorities for controlling the risk and improving the MODU’s safety level. All the developed models have been tested and demonstrated with case studies. An MODU’s drilling failure due to its operational scenario has been investigated and focus has been on the mud circulation system including the blowout preventer (BOP).