A critical review on intelligent optimization algorithms and surrogate models for conventional and unconventional reservoir production optimization
Aiming to find the most suitable development schemes of conventional and unconventional
reservoirs for maximum energy supply or economic benefits, reservoir production …
reservoirs for maximum energy supply or economic benefits, reservoir production …
Metamodel-based multidisciplinary design optimization methods for aerospace system
The design of complex aerospace systems is a multidisciplinary design optimization (MDO)
problem involving the interaction of multiple disciplines. However, because of the necessity …
problem involving the interaction of multiple disciplines. However, because of the necessity …
Training effective deep reinforcement learning agents for real-time life-cycle production optimization
Life-cycle production optimization aims to obtain the optimal well control scheme at each
time control step to maximize financial profit and hydrocarbon production. However …
time control step to maximize financial profit and hydrocarbon production. However …
A radial basis function surrogate model assisted evolutionary algorithm for high-dimensional expensive optimization problems
Evolutionary algorithms require large number of function evaluations to locate the global
optimum, making it computationally prohibitive on dealing with expensive problems …
optimum, making it computationally prohibitive on dealing with expensive problems …
Multifidelity genetic transfer: an efficient framework for production optimization
Production optimization led by computing intelligence can greatly improve oilfield economic
effectiveness. However, it is confronted with huge computational challenge because of the …
effectiveness. However, it is confronted with huge computational challenge because of the …
Constraint handling techniques for metaheuristics: a state-of-the-art review and new variants
Metaheuristic optimization algorithms (MOAs) are computational randomized search
processes which draw inspiration from physical and biological phenomena, with an …
processes which draw inspiration from physical and biological phenomena, with an …
Deep reinforcement learning and adaptive policy transfer for generalizable well control optimization
Well control optimization is a challenging task but plays a critical role in reservoir
management. Traditional methods independently solve each task from scratch and the …
management. Traditional methods independently solve each task from scratch and the …
Data-driven evolutionary algorithm for oil reservoir well-placement and control optimization
Well placement and control scheme optimization is crucial for hydrocarbon, groundwater
and geothermal development, and generally involves a large number of discrete and …
and geothermal development, and generally involves a large number of discrete and …