A Review of Intelligent Optimization Algorithms for Oilfield Development - Lu, Nian; Hong, Mengli (International Journal of Global Economics and Management, 2026)
To identify the most suitable oilfield development strategy for maximizing energy supply or economic returns, optimization of oilfield development remains one of the most critical challenges in closed-loop reservoir management. In recent decades, with the advancement of artificial intelligence technologies, intelligent optimization algorithms have been increasingly applied to improve the efficiency and accuracy of optimization outcomes in oilfield development. This paper provides a comprehensive review of intelligent optimization algorithms applied to oilfield development optimization problems. It covers several key topics within this domain, ranging from the fundamental components of such problems—decision variables, objective functions, and constraints—to various algorithmic approaches developed from different perspectives and for different types of optimization problems.