Optimization in the Oil and Gas Industry: A Review of Techniques, Trends, and Scientific Advances
DOI:
https://doi.org/10.63623/j5jybk62Keywords:
Digitalization, Energy efficiency, Optimization, Process control, SustainabilityAbstract
The oil and gas industry is undergoing a transformative shift driven by the pursuit of operational efficiency, environmental responsibility, and technological innovation. This review critically analyzes optimization strategies deployed across upstream, midstream, and downstream operations. Drawing from recent advances, it explores the integration of feedback control systems, machine learning algorithms, and digitalization tools such as digital twins and edge computing. The review highlights how traditional PID-based control logic has evolved to support real-time optimization, while artificial neural networks (ANNs) have emerged as effective alternatives to physics-based models, particularly in artificial lift and reservoir management. A key finding is the centrality of robust data governance in ensuring the reliability and sustainability of optimization outcomes. Quantitative studies confirm that digital investment, when aligned with organizational restructuring, significantly enhances energy efficiency and production performance. The review also identifies persistent barriers, including corporate resistance to automation and technical misalignment between optimization layers. Emerging trends such as hybrid energy systems and multidimensional optimization frameworks reflect the industry’s growing alignment with environmental and social sustainability goals. This synthesis provides practical insights and a forward-looking perspective on the tools and strategies delivering measurable value in oil and gas optimization under real-world constraints.
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Copyright (c) 2025 Efe Akpotu, Justice Obomejero, Opelopejesu Israel Adeyanju, Ogheneochuko Shadrack Efeni, Emudiaga Fortune Ahwinahwi, Franklin Endurance Igbigbi (Author)
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