... if the pore radius decreases to one nanometer, which indicates the potential of our algorithm for simulating the shale reservoir production process. upstream oil & gas complex reservoir algorithm united states government equation of state calculation derivative pvt measurement optimization...

... and field gas production rate) at each control step need to be honored, solving a large-scale production optimization problem, particularly in geological uncertainty, becomes significantly challenging. This study presents a stochastic gradient-based framework to efficiently solve a nonlinearly constrained...

... the size m and n of a history matching problem before running expensive simulations. united kingdom government optimization problem upstream oil & gas subroutine reservoir simulation united states government europe government machine learning matrix artificial intelligence flop...

... be used as a fast and reliable decision-making tool for reservoir management. fluid dynamics united states government upstream oil & gas reservoir simulation flow in porous media enhanced recovery petroleum engineer optimization problem artificial intelligence machine learning scenario...

.... upstream oil & gas fracture characterization fluid dynamics grid equation of state artificial intelligence waterflooding flow in porous media enhanced recovery cross-section cut-cell grid water saturation cross-section united states government optimization problem modeling...

... understanding of the reservoir in the subsurface. The simultaneous optimization of a large number of well locations is a challenging problem. Conventional gradient-based methods are known to perform efficiently for well-placement optimization problems when such problems are translated into real-valued...

... efficiency maximization case. For the mobile CO 2 minimization case, by contrast, wells are separated and pulsed, which facilitates dissolution and residual trapping. upstream oil & gas subsurface storage fluid dynamics optimization problem constraint-based reasoning reservoir simulation...

... results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO 2 -WAG process, which greatly extends its utility in solving large-scale multi-objective optimization problems in various projects with similar desired outcomes. artificial intelligence...

... posterior distribution. The algorithm to draw from the posterior distribution can be shown to be equivalent to a PDE-constrained optimization problem, which allows for some efficient computational solution techniques. Numerical results demonstrate the efficiency of the proposed methods. In particular, we...

... subsurface storage climate change bayesian inference evolutionary algorithm sequestration wheeler probabilistic surrogate acquisition function optimization problem bayesian optimization optimization application gaussian process upstream oil & gas simulation function evaluation carbon...

... and pressure balance equations. Results for three stand-alone test cases are discussed. well performance reservoir surveillance production control artificial intelligence optimization problem production logging completion installation and operations production monitoring asset and portfolio...

... Abstract Although it is possible to apply traditional optimization algorithms to determine the Pareto front of a multi-objective optimization problem, the computational cost is extremely high, when the objective function evaluation requires solving a complex reservoir simulation problem...

... engineering heuristics, the priority function helps the optimizer focus on exploring scenarios with promising outcomes. The proposed heuristic priority function, combined with the Genetic Algorithm (GA), has been tested through drill sequence optimization problems for the Brugge field and Olympus field...

... computing (HPC). reservoir characterization modeling & simulation optimization problem artificial intelligence upstream oil & gas equation of state waterflooding enhanced recovery flow in porous media reservoir simulation heterogeneity workover convergence criteria realization...

... optimization problem constraint proxy application network model multiple training simulation well performance reservoir simulation ipr database simulation ipr curve training simulation petroleum engineer training case scenario surface network Introduction The surface network model...

... in porous media fluid dynamics streamline artificial intelligence upstream oil & gas flow diagnostic enhanced recovery reservoir simulation gridblock datta-gupta application matrix rate allocation optimization fracture matrix domain fracture domain algorithm probability optimization...

... are easier to work with in our optimization procedure, as these are both within similar orders of magnitude and do not require consideration of the hard constraint associated with the bounds on Poisson's ratio. They also lend themselves more easily to interpretation when the optimization problem in cast...

... techniques e.g., Genetic Algorithm and Machine-Learning sampling method were utilized in an iterative manner. It was quickly realized that due to the number of mixed categorical and continuous control parameters and non-linearity in simulation response, the optimization problem became almost infeasible...

... experiment porous media optimization problem Hajibeygi goal tolerance total number reservoir simulation information adjoint model Indicator society of petroleum engineers Lagrange multiplier equation scaling method Upstream Oil & Gas sensitivity pressure error norm i-msfv method...

... Crosswell EM data Reservoir Characterization history matching localization application conductivity optimization problem Computational Geoscience model parameter production data inversion Standard Deviation EM data assimilation conductivity field ensemble ensemble Kalman filter initial...