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 …
Global and local surrogate-model-assisted differential evolution for waterflooding production optimization
Surrogate models, which have become a popular approach to oil‐reservoir production‐
optimization problems, use a computationally inexpensive approximation function to replace …
optimization problems, use a computationally inexpensive approximation function to replace …
Surrogate-assisted evolutionary algorithm with dimensionality reduction method for water flooding production optimization
The objective of oil reservoir production optimization is finding optimal scheme of each well
to maximize the net present value (NPV) or the hydrocarbon production. Various …
to maximize the net present value (NPV) or the hydrocarbon production. Various …
[HTML][HTML] Data-driven production optimization using particle swarm algorithm based on the ensemble-learning proxy model
Production optimization is of significance for carbonate reservoirs, directly affecting the
sustainability and profitability of reservoir development. Traditional physics-based numerical …
sustainability and profitability of reservoir development. Traditional physics-based numerical …
A classification-based surrogate-assisted multiobjective evolutionary algorithm for production optimization under geological uncertainty
Multiobjective optimization (MOO) is a popular procedure for waterflooding optimization
under geological uncertainty that maximizes the expectation of net present value (NPV) over …
under geological uncertainty that maximizes the expectation of net present value (NPV) over …
Hybrid derivative-free technique and effective machine learning surrogate for nonlinear constrained well placement and production optimization
It is imperative that wells in an oil field be located and controlled in an optimal fashion to
maximize asset value while satisfying the optimization constraints which can be in the form …
maximize asset value while satisfying the optimization constraints which can be in the form …
[HTML][HTML] Evolutionary-assisted reinforcement learning for reservoir real-time production optimization under uncertainty
Production optimization has gained increasing attention from the smart oilfield community
because it can increase economic benefits and oil recovery substantially. While existing …
because it can increase economic benefits and oil recovery substantially. While existing …
Development of an adaptive surrogate model for production optimization
Recently production optimization has gained increasing interest in the petroleum industry.
The most computationally expensive part of the production optimization process is the …
The most computationally expensive part of the production optimization process is the …
A surrogate-assisted multi-objective evolutionary algorithm with dimension-reduction for production optimization
Abstract Multi-objective optimization (MOO), which involves more than one conflicting
objective to be optimized simultaneously, is expected to provide efficient and …
objective to be optimized simultaneously, is expected to provide efficient and …
Evolutionary algorithm with individual-distribution search strategy and regression-classification surrogates for expensive optimization
Surrogate-assisted evolutionary algorithms (SAEAs) with prescreening model management
strategies show great potential in handling expensive optimization problems (EOPs) …
strategies show great potential in handling expensive optimization problems (EOPs) …