Risk Assessment and Control of Deepwater Umbilical Cable–Laying Process Based on a Complex Network

During the installation of deepwater umbilical cables, multiple risk factors exhibit coupled interactions, rendering conventional static risk assessment methods inadequate for capturing dynamic risk evolution and secondary disaster chain effects. To address the limitations of existing research in dynamically analyzing risk propagation pathways and modeling interactions within man–machine-environment-management (MMEM) systems, this study proposes a risk assessment framework grounded in complex network theory. Focusing on the entire laying process of deepwater umbilical cables, the research integrates cloud modeling and an enhanced decision-making trial and evaluation laboratory algorithm to construct a multiphase weighted directed risk network. This approach systematically quantifies the fuzziness and stochasticity inherent in expert evaluations while identifying critical risk nodes and their propagation pathways. A case study of a gas field development in the South China Sea demonstrates the establishment of a dynamic risk mitigation mechanism that coordinates core driving factors, chain propagation, intraphase containment, and cross-phase interdiction. The model provides a quantifiable framework for dynamic risk management in deepwater engineering, effectively enhancing safety decision-making capabilities for complex marine systems and achieving system risk reduction.