A digital operations model for aligning subsea surveillance workflows with floating storage vessel schedules and offshore logistics
DOI:
https://doi.org/10.64171/JAES.1.1.62-69Keywords:
Subsea surveillance, Offshore logistics, Floating storage and offloading (FSO), Digital operations model, Predictive maintenance, Data-driven coordinationAbstract
Offshore oil and gas operations rely heavily on two critical yet often disconnected domains: subsea surveillance and offshore logistics, particularly involving Floating Storage and Offloading (FSO/FPSO) vessels. These domains operate in silos, leading to delayed interventions, misaligned schedules, and significant inefficiencies. This paper proposes a digital operations model designed to align subsea surveillance workflows with floating vessel schedules and offshore logistics through real-time data integration, automated decision support, and intelligent orchestration. The model features a centralized digital platform that ingests data from ROVs, AUVs, and fixed sensors, integrates it with marine scheduling systems, and enables predictive planning through rule-based decision nodes. It emphasizes interoperability with legacy systems, hybrid automation with human-in-the-loop oversight, and robust cybersecurity to ensure operational integrity. By synchronizing maintenance needs with vessel movements, the model reduces downtime, improves resource utilization, and enhances the responsiveness of offshore operations. The proposed framework offers a scalable foundation for digital transformation in offshore environments and lays the groundwork for future integration with AI, digital twins, and industry-wide standardization initiatives.
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