Year: 2025
Type: article
Abstract: ABSTRACT With the rapid advancement of deepwater oil and gas exploration, subsea operations are facing increasingly complex environments and technical challenges. As water depth increases, the difficulty of installation, operational risks and uncertainties grow significantly, resulting in shorter weather windows, limited real‐time response and higher safety requirements. To address these challenges and enhance operational efficiency and safety, this paper proposes a digital twin‐based support system for deepwater subsea installation. The system integrates heterogeneous data sources to establish dynamic mappings between physical assets and their digital counterparts, enabling real‐time monitoring, predictive analysis and intelligent decision‐making across the entire installation lifecycle. By incorporating environmental sensing, dynamic simulation and virtual‐reality interaction, the digital twin system supports task planning, risk forecasting and remote operations in complex subsea conditions. A case study is presented to demonstrate the system's effectiveness in improving decision efficiency and reducing operational risk. The research provides a theoretical foundation and technical pathway for the intelligent and digital transformation of deepwater offshore engineering.
Source: Digital twins and applications.
DOI: 10.1049/dgt2.70020
Authors: Song Chen, Zhifeng Wang, Shuo Wang, Lizhi Duan, Jianhang Wu, Renhui Wu, Yan Qu
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7117658103