Manuscript Number : SHISRRJ247155

An Alarm Management and Decision Support Framework for Control Room Operations in Deepwater Production Vessels

Authors(4) :-Andrew Tochukwu Ofoedu, Joshua Emeka Ozor, Oludayo Sofoluwe, Dazok Donald Jambol

Deepwater production vessels (DPVs), such as Floating Production Storage and Offloading units (FPSOs), operate under complex, high-risk conditions where effective control room operations are critical to safety and production continuity. A significant challenge in these environments is managing the overwhelming volume of alarms generated by distributed control systems (DCS), particularly during process upsets. Excessive alarm rates, poor prioritization, and nuisance alarms often lead to cognitive overload, alarm fatigue, and delayed or incorrect operator response. This presents a comprehensive Alarm Management and Decision Support Framework tailored to the operational realities of deepwater production environments. The proposed framework integrates best practices from ISA-18.2 and EEMUA 191 with intelligent technologies to enhance situational awareness and support real-time decision-making. Key components include an advanced alarm rationalization engine, dynamic thresholding based on process context, flood suppression strategies, and a decision support layer powered by machine learning. The framework interfaces directly with existing DCS and SCADA systems, leveraging real-time data, historical patterns, and operator inputs to improve alarm fidelity and reduce cognitive burden. A simulation case study involving a high-pressure riser failure scenario demonstrates the framework's effectiveness in reducing alarm volume, enhancing response time, and improving operator confidence. Performance metrics indicate substantial improvements in alarm relevance, system stability, and decision accuracy compared to traditional alarm handling methods. This work underscores the strategic importance of integrating intelligent alarm management with operator support tools in complex offshore systems. By aligning human factors engineering with real-time analytics and adaptive learning, the proposed framework contributes to safer and more resilient deepwater production operations. Future research will explore deeper integration with digital twin environments, adaptive alarm configurations, and advanced human-in-the-loop systems to further optimize offshore control room performance.

Authors and Affiliations

Andrew Tochukwu Ofoedu
Shell Nigeria Exploration and Production Company, Nigeria
Joshua Emeka Ozor
First Hydrocarbon, Nigeria
Oludayo Sofoluwe
TotalEnergies Nigeria
Dazok Donald Jambol
D-Well Engineering Nig. Ltd. (Shell Petroleum Development Company of Nigeria), Nigeria

Alarm management, Decision support framework, Control room operations, Deepwater production vessels

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Publication Details

Published in : Volume 7 | Issue 4 | July-August 2024
Date of Publication : 2024-08-16
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 107-126
Manuscript Number : SHISRRJ247155
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Andrew Tochukwu Ofoedu, Joshua Emeka Ozor, Oludayo Sofoluwe, Dazok Donald Jambol, "An Alarm Management and Decision Support Framework for Control Room Operations in Deepwater Production Vessels", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 4, pp.107-126, July-August.2024
URL : https://shisrrj.com/SHISRRJ247155

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