Manuscript Number : SHISRRJ2472143

A Multivariable Optimization Model for Stabilizing Crude Oil Separation in Multi-Phase FPSO Process Streams

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

Floating Production Storage and Offloading (FPSO) systems have emerged as a critical infrastructure in deepwater oil exploration and production, especially in remote offshore environments where subsea production systems demand compact, flexible, and autonomous solutions. Within these systems, the separation of crude oil, water, and gas is a foundational process that directly impacts production efficiency, hydrocarbon quality, and downstream operability. However, the complexity of multiphase flow behavior, variable well conditions, and fluctuating reservoir characteristics presents persistent challenges to the stability of separation units. Traditional control strategies, often based on single-variable or heuristic feedback mechanisms, lack the sensitivity and adaptability required for dynamic and non-linear separation processes. This limitation frequently results in suboptimal operating points, high energy consumption, and compromised product quality. To address these challenges, this study proposes a multivariable optimization model designed to stabilize the crude oil separation process under varying conditions aboard FPSO platforms. The model integrates thermodynamic principles, dynamic process modeling, and advanced optimization algorithms to monitor and control key variables such as pressure, temperature, flow rates, and compositional interfaces in real-time. By considering the interdependencies between separation stages and leveraging real-time data from process instrumentation, the model enhances operational robustness and reduces the frequency of manual interventions. Furthermore, the optimization framework is designed for adaptability, allowing it to reconfigure control actions in response to disturbances such as slugging, water breakthrough, and gas influx from the reservoir. Simulation-based validation using a calibrated dynamic process environment demonstrates the model's capacity to maintain separation efficiency across a range of operating scenarios. The results show measurable improvements in energy efficiency, product recovery rates, and system stability, highlighting the model's potential for deployment in modern digitalized FPSO control architectures. Overall, this study contributes a scalable and intelligent solution for improving operational resilience in offshore oil production systems, supporting the broader industry transition toward automated and optimized hydrocarbon processing.

Authors and Affiliations

Andrew Tochukwu Ofoedu
Shell Nigeria Exploration and Production Company, Nigeria
Joshua Emeka Ozor
First Hydrocarbon, Nigeria
Oludayo Sofoluwe
TotalEnergies Nigeria, IFP School, France, and BI Norwegian Business School
Dazok Donald Jambol
Aramco, Kingdom of Saudi Arabia

FPSO, Crude Oil Separation, Multivariable Optimization, Process Stability, Dynamic Modeling, Offshore Oil Production

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Publication Details

Published in : Volume 7 | Issue 2 | March-April 2024
Date of Publication : 2024-04-05
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 76-113
Manuscript Number : SHISRRJ2472143
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Andrew Tochukwu Ofoedu, Joshua Emeka Ozor, Oludayo Sofoluwe, Dazok Donald Jambol, "A Multivariable Optimization Model for Stabilizing Crude Oil Separation in Multi-Phase FPSO Process Streams", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 2, pp.76-113, March-April.2024
URL : https://shisrrj.com/SHISRRJ2472143

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