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An Integrated Production Assurance Framework for Floating Oil Platforms in Harsh Deepwater Environments
Subject area: Science,Engineering and Technology · Area of research: Production Assurance
Abstract
Floating oil platforms operating in harsh deepwater environments face significant challenges that threaten continuous production, operational safety, and environmental compliance. Extreme weather conditions, high pressures, and complex subsea operations contribute to elevated risks of equipment failure, production downtime, and safety incidents. Addressing these challenges requires a comprehensive and adaptive approach to production assurance that integrates risk management, real-time monitoring, predictive maintenance, and safety protocols into a unified framework. This presents an Integrated Production Assurance Framework specifically designed for floating oil platforms in harsh deepwater settings. The framework combines advanced sensor technologies, data analytics, and decision support systems to enable proactive identification and mitigation of production risks. It incorporates predictive maintenance strategies grounded in reliability engineering, facilitating early detection of equipment degradation and optimizing maintenance scheduling to minimize unplanned shutdowns. Safety management is embedded within the framework to ensure rapid response to incidents and compliance with stringent environmental regulations. The proposed framework emphasizes system integration, connecting real-time operational data with predictive models and human-machine interfaces to enhance situational awareness and support informed decision-making. Customization to platform-specific and site-specific conditions is a key feature, recognizing the unique challenges posed by diverse deepwater environments. The implementation methodology includes stakeholder engagement, workforce training, and cybersecurity measures to protect critical operational data. A case study application demonstrates the framework?s effectiveness in improving production continuity, reducing operational risks, and supporting sustainable offshore operations. The study highlights the framework?s capacity to adapt to evolving environmental and technical conditions, underscoring its strategic value for offshore operators. This integrated approach not only advances production assurance but also contributes to the broader goals of operational efficiency, safety enhancement, and environmental stewardship in deepwater oil extraction. Future research directions include the incorporation of artificial intelligence and autonomous systems to further augment predictive capabilities and operational resilience.
Keywords
Integrated, Production assurance, Framework, Floating oil, Platforms, Harsh, Deepwater environments
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How to cite this paper
@article{1709213,
author = {Andrew Tochukwu Ofoedu, Joshua Emeka Ozor, Oludayo Sofoluwe, Dazok Donald Jambol},
title = {An Integrated Production Assurance Framework for Floating Oil Platforms in Harsh Deepwater Environments},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {3},
number = {12},
pages = {319-334},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1709213.pdf},
abstract = {Floating oil platforms operating in harsh deepwater environments face significant challenges that threaten continuous production, operational safety, and environmental compliance. Extreme weather conditions, high pressures, and complex subsea operations contribute to elevated risks of equipment failure, production downtime, and safety incidents. Addressing these challenges requires a comprehensive and adaptive approach to production assurance that integrates risk management, real-time monitoring, predictive maintenance, and safety protocols into a unified framework. This presents an Integrated Production Assurance Framework specifically designed for floating oil platforms in harsh deepwater settings. The framework combines advanced sensor technologies, data analytics, and decision support systems to enable proactive identification and mitigation of production risks. It incorporates predictive maintenance strategies grounded in reliability engineering, facilitating early detection of equipment degradation and optimizing maintenance scheduling to minimize unplanned shutdowns. Safety management is embedded within the framework to ensure rapid response to incidents and compliance with stringent environmental regulations. The proposed framework emphasizes system integration, connecting real-time operational data with predictive models and human-machine interfaces to enhance situational awareness and support informed decision-making. Customization to platform-specific and site-specific conditions is a key feature, recognizing the unique challenges posed by diverse deepwater environments. The implementation methodology includes stakeholder engagement, workforce training, and cybersecurity measures to protect critical operational data. A case study application demonstrates the framework?s effectiveness in improving production continuity, reducing operational risks, and supporting sustainable offshore operations. The study highlights the framework?s capacity to adapt to evolving environmental and technical conditions, underscoring its strategic value for offshore operators. This integrated approach not only advances production assurance but also contributes to the broader goals of operational efficiency, safety enhancement, and environmental stewardship in deepwater oil extraction. Future research directions include the incorporation of artificial intelligence and autonomous systems to further augment predictive capabilities and operational resilience.},
keywords = {Integrated, Production assurance, Framework, Floating oil, Platforms, Harsh, Deepwater environments},
month = {June},
}