A SCADA-Integrated Framework for Real-Time Production Monitoring and Operational Intelligence in FPSO Units

The evolution of offshore oil and gas operations has brought forward increasing demands for precision, responsiveness, and operational efficiency. Floating Production Storage and Offloading (FPSO) units, as pivotal assets in deepwater field development, face considerable challenges related to real-time data acquisition, operational transparency, and system integration. Amidst growing complexities, Supervisory Control and Data Acquisition (SCADA) systems have emerged as critical enablers of automation and process visibility. This study introduces a SCADA-integrated framework specifically designed to enhance real-time production monitoring and operational intelligence in FPSO environments. By bridging legacy control systems with cutting-edge data analytics, the framework supports proactive decision-making, improved asset reliability, and optimized process control. The proposed approach leverages multi-tiered architecture to integrate sensor data, control modules, visualization dashboards, and operational intelligence engines. It facilitates the continuous flow of actionable insights from subsea operations to central control units, ensuring a more synchronized and adaptive production environment. Emphasis is placed on enabling dynamic feedback loops between physical operations and digital monitoring tools, thereby transforming static control schemes into agile, learning-driven systems. Key innovations include the incorporation of predictive analytics for anomaly detection, real-time KPI tracking, and the development of fault-tolerant mechanisms that ensure data integrity and system resilience. This framework is not only geared toward technical efficiency but also aligns with industry-wide shifts toward digital transformation, remote operability, and sustainability. It presents a scalable model adaptable to varying FPSO configurations and geographies, offering strategic advantages in cost reduction, risk mitigation, and productivity gains. Furthermore, the study outlines a comprehensive methodology for system implementation, validation, and continuous improvement—positioning it as a roadmap for engineers, policymakers, and offshore operators seeking to future-proof FPSO operations.

Authors

Publication Details

Journal
International Journal of Advanced Multidisciplinary Research and Studies
Published
2024-12-31
DOI
https://doi.org/10.62225/2583049x.2024.4.6.4450
Citations
3
Primary Topic
Oil and Gas Production Techniques
Type
article
Field-Weighted Citation Impact
1.01
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article

A SCADA-Integrated Framework for Real-Time Production Monitoring and Operational Intelligence in FPSO Units

Oludayo Olatoye Sofoluwe, Dazok Donald Jambol, Andrew Tochukwu Ofoedu, Joshua Emeka Ozor
3 citations
International Journal of Advanced Multidisciplinary Research and Studies
Oil and Gas Production Techniques
1.01
article

A SCADA-Integrated Framework for Real-Time Production Monitoring and Operational Intelligence in FPSO Units

Oludayo Olatoye Sofoluwe, Dazok Donald Jambol, Andrew Tochukwu Ofoedu, Joshua Emeka Ozor
article en
3 citations

Abstract

The evolution of offshore oil and gas operations has brought forward increasing demands for precision, responsiveness, and operational efficiency. Floating Production Storage and Offloading (FPSO) units, as pivotal assets in deepwater field development, face considerable challenges related to real-time data acquisition, operational transparency, and system integration. Amidst growing complexities, Supervisory Control and Data Acquisition (SCADA) systems have emerged as critical enablers of automation and process visibility. This study introduces a SCADA-integrated framework specifically designed to enhance real-time production monitoring and operational intelligence in FPSO environments. By bridging legacy control systems with cutting-edge data analytics, the framework supports proactive decision-making, improved asset reliability, and optimized process control. The proposed approach leverages multi-tiered architecture to integrate sensor data, control modules, visualization dashboards, and operational intelligence engines. It facilitates the continuous flow of actionable insights from subsea operations to central control units, ensuring a more synchronized and adaptive production environment. Emphasis is placed on enabling dynamic feedback loops between physical operations and digital monitoring tools, thereby transforming static control schemes into agile, learning-driven systems. Key innovations include the incorporation of predictive analytics for anomaly detection, real-time KPI tracking, and the development of fault-tolerant mechanisms that ensure data integrity and system resilience. This framework is not only geared toward technical efficiency but also aligns with industry-wide shifts toward digital transformation, remote operability, and sustainability. It presents a scalable model adaptable to varying FPSO configurations and geographies, offering strategic advantages in cost reduction, risk mitigation, and productivity gains. Furthermore, the study outlines a comprehensive methodology for system implementation, validation, and continuous improvement—positioning it as a roadmap for engineers, policymakers, and offshore operators seeking to future-proof FPSO operations.

International Journal of Advanced Multidisciplinary Research and StudiesVol. 4(6)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Oil and Gas Production Techniques
1.01
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