Safety Analysis of Offshore Wells Plugging and Abandonment Process with Riserless Well Intervention System Using a DBN based Comprehensive Method

Abstract

The Riserless Well Intervention (RLWI) system that performs complex offshore oil well Plugging and Abandonment (P&A) operations is a typical Multi-Mission Phased-Mission System (MM-PMS), which requires multiple missions to be completed within a phase. P&A processes involve complex operations and equipment that can contaminate local marine ecosystems if they fail. Therefore, it is necessary to evaluate the reliability of the RLWI system. This paper proposes a dynamic reliability evaluation model for analyzing the RLWI MM-PMS. The GO model of the phase operation process and the Fault Tree (FT) model used to analyze the failure of each mission were established, and a Dynamic Bayesian Network (DBN) model based on the GO model and the FT model was developed for reliability evaluation. The established model can analyze the changes in the reliability of the RLWI MM-PMS more comprehensively, and can also clarify the importance of different missions and different system components. In addition, considering the impact of the marine environment on operators, the Standardized Plant Analysis Risk-Human (SPAR-H) reliability analysis is used for quantification. These findings can guide the improvement of the reliability of the RLWI system and the success rate of P&A operations.