Performance analysis of subsea wellhead system considering thermodynamic coupling defects

• Published in: Ocean engineering 2024-11, Vol.312, p.119074, Article 119074
• Main Authors: Wu, Shengnan, Li, Bin, Zhang, Laibin, Zhang, Qiao, Liu, Yiliu
• Format: Article
• Language: English
• Subjects: Fatigue damage; Probabilistic-based models; Reliability analysis; Subsea wellhead system; Temperature-pressure coupling effects
• ISSN: 0029-8018
• DOI: 10.1016/j.oceaneng.2024.119074

The Subsea wellhead (SW) system plays a crucial role in offshore oil and gas drilling and production. Specifically, the high-pressure wellhead (HPW), as a critical pressure-bearing part, operates in a challenging environment characterized by complex temperature-pressure loads and corrosion after extended service, posing a risk of fatigue damage. This paper presents a performance analysis method that integrates stress states and probabilistic-based models for intricate SW systems, incorporating fatigue tests. An advanced finite element model accounts for thermodynamic coupling and corrosion defects, predicting the impact of thermal distribution on SW mechanical behavior. This model can effectively capture environmental and operational loadings, enabling the identification of fatigue hot spots. The relationship between stress and fatigue damage is established, facilitating the prediction of the fatigue life of key components using tested S-N curve. The reliability of the SW system under multiple loads is estimated through Monte Carlo simulation combined with the response surface method. The effects of structural, operational, and thermodynamic parameters on reliability are considered, thereby enhancing SW performance. To validate the effectiveness and feasibility of the models, the method is applied to a case study involving an HPW system, with simulation results compared to actual testing outcomes. •Develop an advanced FEM-based approach for fatigue damage and reliability analysis of complicated SW system.•Subsea environmental loads, operating loads and material properties are considered to identify the fatigue hotspots.•Establish the relationship between stress and fatigue damage to predict fatigue life by imbedding tested S-N curve.•An improved RSM-MCS method is proposed for SW reliability and sensitivity analysis.