A Mixed-Integer Nonlinear Programming Model for Solving Integrated Oil and Gas Supply Chain Problem by Considering Enhanced Oil Recovery Methods

Document Type : Research Paper

Authors

Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

10.22070/jqepo.2024.16617.1243

Abstract

 This paper presents a model to solve a multi-objective optimization problem for optimal oil field
development and supply chain management (SCM) of oil and gas, considering Enhanced Oil Recovery (EOR)
methods in both upstream and midstream sectors. Unlike previous studies that primarily investigated EOR in
the upstream sector, this study focuses on integrating EOR methods within a comprehensive supply chain
model. The problem is formulated as a mixed integer nonlinear program (MINLP) to accurately capture the
complexities and interdependencies of oil field development and SCM. To facilitate solution, the multiobjective problem is converted into a single-objective problem using the LP-metric method. The transformed
problem is then solved using the BARON solver within the GAMS software environment. To evaluate the
efficiency and robustness of the proposed solution method, a set of 15 test problems with varying dimensions
was solved. The results demonstrate that the solution method is highly efficient for small-size problems,
achieving a relative gap of 0.01 in less than 100 seconds. However, the computational time increases
significantly as the problem size grows, highlighting the challenges of scaling the model for larger and more
complex scenarios. This study provides a novel approach to incorporating EOR methods into an integrated
supply chain model, offering valuable insights for optimizing oil and gas field development and SCM
strategies. 

Keywords

References

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Journal of Quality Engineering and Production Optimization
Volume 9, Issue 1
May 2024
Pages 1-28

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