... learning-based proxy models can be found in Atadeger (2022 ) and Atadeger et al. (2022 ) as the same models are adopted in this study. Table 1 The architecture of the neural network constructed to predict NPV. N u is the total number of well controls. Layer Output size Input...

... neural network as a proxy model of the NPV function, is described. The methodology consists of design an artificial neural network enables to predict the average and standard deviation of NPV for an ensemble of geological realization representing the uncertainties. Global optimizations are performed...

... well History conditioning reservoir model permeability Upstream Oil & Gas Reservoir Management Decision NPV reservoir dynamic data Introduction Increasing uncertainty in the economic profitability of modern hydrocarbon projects leads to an increased focus on reservoir management...

... that can be used for decision support to balance long-term and short-term goals. Artificial Intelligence optimization problem objective function Pareto optimal Upstream Oil & Gas oil production short-term production optimization NPV short-term strategy weighted-sum method optimization...

... be achieved through optimization of technology and processes. artificial intelligence upstream oil & gas training data enhanced recovery steam-assisted gravity drainage simulation thermal method sagd objective function spe 145679 algorithm optimizer npv operational parameter computer...

... fluid optimization npv hydraulic fracture optimization model fracture fracture half-length injection rate fluid viscosity design variable algorithm spe 148205 reservoir lower bound ensure design constraint shear rate treatment parameter Introduction and Review Industry still faces...