... keeping the parametrization of uncertainties as practical as possible. reservoir optimization problem history matching neural network upstream oil & gas reservoir simulation artificial intelligence machine learning boundary evolutionary algorithm north kuwait criteria asia government...

... the optimization framework flexible to be customized to any specific optimization problem, e.g., optimization of any type of field development decisions, coupling to any industry-standard reservoir simulators and handling any type of objective and constraint functions. The optimization framework has been used...

... north america government enhanced recovery climate change complex reservoir greenhouse ga emission injection optimization artificial intelligence production monitoring reservoir limited-data depleted gas reservoir injectivity optimization problem reservoir surveillance production control...

... and cross-refer here). gas injection method artificial intelligence cumulative recovery optimization problem enhanced recovery workflow neural network recovery machine learning upstream oil & gas miscible method evolutionary algorithm prediction variation dataset simulation...

... waterflooding reservoir simulation optimization problem asia government netherlands government machine learning concentration complex reservoir foam europe government enhanced recovery permeability reservoir simulator journal malaysia government gas injection method modeling & simulation...

... management framework makes it highly applicable to near real-time reservoir management in EGS as well as other similar system management processes. reservoir simulation upstream oil & gas artificial intelligence neural network australia government united states government optimization problem...

... validation field behavior Modeling & Simulation Upstream Oil & Gas streamline Artificial Intelligence history matching validation process fpcm optimization problem injector Reservoir Management workflow fluid movement aquifer producer well scale society of petroleum engineers...

... stochastic dominance uncertainty realization realization optimisation Artificial Intelligence cumulative density function well control reservoir simulation optimisation realisation response surface optimization problem pragmatic approach development scenario well location society of petroleum...

... in term of return/risk ratio. The problem to solve can be defined as a multi-criterion objective function where the average of NPV is maximized, and the standard deviation of NPV is minimized. The optimization problem consists of identifying X * ∈ U such as: (2) J ( X * ) = X ∈ U...

... History convergence machine learning optimization problem objective function amplitude society of petroleum engineers coefficient history matching multiplier uncertainty quantification permeability model discrete cosine transformation permeability Introduction The most common problem...

... of the fluid flow simulator, which make them difficult to combine with algorithms that attempt to solve general fluid flow optimization problems. This is especially true when combined with commercial software for flow simulation, as we do not have access to the source code. As a result, non-intrusive...

... applications that would not be possible without virtual meter results and uses the results of external applications for validation purpose. production monitoring optimization problem production parameter Reservoir Surveillance Upstream Oil & Gas Wellhead rate transient analysis application...

... to consider a wider range of possible scenarios, for deeper understanding and better risk mitigation. asset and portfolio management optimization problem Artificial Intelligence Upstream Oil & Gas optimization variable ensemble control valve constraint workflow realization Scenario field...

... ) ≥ 0 , n = 1 , … , N (3e) k ( x n , u n ) ≥ 0 , n = 1 , … , N Production Optimization Problem The production optimization problem presented here entails finding the optimal control vectors that maximize the performance measure under a waterflooding...

... Upstream Oil & Gas gas cap flooding optimization problem Surfactant Flooding oil rim reservoir ior eor method machine learning gas flooding Oil Recovery Scenario reservoir water flooding Introduction Reservoir simulation predicts the flow of fluids through porous media. It has been...

... in a given search space. The algorithm was originally developed to simulate social behavior. Subsequently, it was observed that it is suitable for optimization problems. The algorithm works with a certain set of particles called a swarm. Each particle is described by a position in the search space...

... Oil & Gas evolutionary algorithm optimization problem well control saturation distribution fracture History multi-objective optimisation engineering control mwag injection workflow oil production rate proxy model Reservoir Characterization reservoir simulation Scenario permeability...

... and density) from well test pressure responses (e.g., permeability-thickness product, storativity, and interporosity). The optimization problem is addressed using a direct search method. A novel multi-level genetic algorithm is developed to find the optimum solution space of the fracture properties...

... it has been designed to provide multiple and different solutions in a single run. machine learning Upstream Oil & Gas model inversion optimization problem function evaluation evolutionary algorithm optimization multi-start pso mpso algorithm analytic cost function algorithm MPSO...

..., optimization software can be combined with a numerical reservoir simulator. Hence, robust and faster results are imperative to optimization problems. To maximize cumulative recovery and net present value (NPV), the reservoir simulator works on maximizing these predefined objective functions that can be multi...