... reservoir simulation reservoir surveillance artificial intelligence production control optimization tr-sqp robust optimization procedure optimization problem enhanced recovery machine learning gradient realization reynolds reservoir characterization algorithm nonlinear constraint subproblem...

... 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...

... Abstract Commercial reservoir simulators have traditionally been optimized for distributed parallel execution on Central Processing Units (CPUs). Recent advances in Graphics Processing Units (GPUs) have led to the development of GPU-native simulators and triggered a shift towards a hardware...

... not been extensively tested in different settings for ensemble-based history matching of reservoir simulation models. This work proposes a general workflow to guide localization implementation and evaluation. The workflow is developed in five sections: i) the initial ensemble generation; ii) history...

... 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...

... reservoir geomechanics permeability displacement table united states government equation of state enhanced recovery reactivation mole fraction vector upstream oil & gas reservoir simulation tendency canada government transmissibility multiplier storage unit vector wellbore design flow...

.... For the unconventional test problem, the samples are compared with the ones obtained using a Gauss Newton or iterative Ensemble Smoother methods. reservoir simulation history matching artificial intelligence machine learning united states government particle upstream oil & gas bayesian inference stein...

... Abstract In composition reservoir simulation, fluid phase behavior is determined by vapor-liquid equilibrium (VLE) calculations. VLE calculations can consume more than half of the CPU time of compositional reservoir simulations. To accelerate the VLE calculations, machine learning (ML...

.... united states government complex reservoir upstream oil & gas reservoir simulation scaling method grid refinement fracture grid modeling & simulation equation discrete fracture fracture china government grid pedfm fractured reservoir discrete fracture model matrix grid adaptive...

.... upstream oil & gas reservoir simulation asia government structural geology china government reservoir geomechanics equation modeling & simulation preconditioner janna ferronato geomechanical simulator gpu-accelerated simulator reservoir characterization journal website challenging...

... fluid dynamics flow in porous media upstream oil & gas artificial intelligence convergence iteration nldd runtime subdomain nonlinear elimination aspen equation simulator reservoir simulation enhanced recovery solver preconditioner comput decay nonlinear iteration preconditioned...

... slope is related with drawdown pressure. upstream oil & gas drillstem testing drillstem/well testing reservoir simulation wellbore design completion installation and operations perforation tunnel history wellbore integrity fines migration perforation efficiency united states...

... Abstract Routine well-wise injection/production data contain significant information which can be used for closed-loop reservoir management and rapid field decisions. Traditional physics-based numerical reservoir simulation can be computationally prohibitive for short-term decision cycles...

... Abstract Integrated reservoir studies for performance prediction and decision-making processes are computationally expensive. In this paper, we develop a novel linearization approach to reduce the computational burden of intensive reservoir simulation execution. We achieve this by introducing...

... Abstract Commercial reservoir simulators have traditionally been optimized for parallel computations on central processing units (CPUs). The recent advances in general-purpose graphics processing units (GPUs) have provided a powerful alternative to CPU, presenting an opportunity...

.... The results show that the stabilization is effective at smoothing the pressure field without adversely affecting the prediction quality of other quantities of interest. fluid dynamics reservoir simulation climate change stabilization subsurface storage injection stabilization flux equation...

... pressure change on mixing accelerates the CO 2 diffusion into the reservoir through the sorbed region and also the counter-current transport of oil components through the central region. reservoir simulation enhanced recovery united states government co 2 injection okuno upstream oil & gas...

... the number of components used in compositional models. pvt measurement artificial intelligence united states government composition upstream oil & gas equation of state characterization partition algorithm component reservoir simulation machine learning regression lump clustering...

... ). Despite these developments, intrusive changes are required for its implementation within a fully-implicit cell-centered general compositional reservoir simulator ( Raynaud et al. 2021 ), which disqualified the MFD method from our investigations. In this work, we develop and test consistent...

... . Algorithm 2 Calculation of restricted smoothed basis functions. Abstract The key idea with multiscale methods for reservoir simulation is to construct a set of prolongation operators that interpolate solutions from a coarse spatial resolution to the grid resolution. Efficient multiscale methods...