... with the stochastic-gradient-based line-search sequential quadratic programming (LS-SQP) workflow associated with the lexicographic method to handle robust multi-objective optimization in the presence of nonlinear state constraints. Five realizations of the SPE10 sector model consisting of different channelized...

... Abstract Our objective is to seek optimal well placement design for maximizing immobile CO 2 storage capacity within an operating oilfield given a set of realistic input constraints consisting of well placement geometry as well as output constraints consisting of the CO 2 production rate...

... accuracy within reasonable CPU time. Moreover, SAOR ensures that the solutions are not only optimal but also adhere to the underlying physics and technical constraints of the reservoir system. This paper is organized as follows. First, we provide a general description of the SAOR optimization approach...

... and water production, all within the constraints of this thermodynamically complex reservoir. The methodology was developed through a collaborative effort between SLB and Petrobras, integrating reservoir modeling, advanced completions technology, and operational optimization to address the reservoir`s...

... workflows may lead to poor-quality decisions. geologist geology directional drilling optimization problem artificial intelligence risk management machine learning evolutionary algorithm waterflooding flow in porous media optimization objective function fluid dynamics constraint model...

... Another complexity is the multifaceted constraints governing exploration and development decisions. Each prospect operates under specific lease terms with defined expiration dates that necessitate drill/no-drill decisions within prescribed timeframes. Similarly, production facilities have...

... parametrization dataset reconstruction accuracy conditional vae jafarpour variational autoencoder parameterization constraint Introduction Accurate prediction of flow and transport behavior relies on correct description of the subsurface flow properties. In practice, geologic formations tend...

... Summary Life-cycle production optimization is a crucial component of closed-loop reservoir management, referring to optimizing a production-driven objective function via varying well controls during a reservoir's lifetime. When nonlinear-state constraints (e.g., field liquid production rate...

.... Ensemble Smoother with Multiple Data Assimilation (ESMDA) is utilized to reduce the error at each step of the history matching. Next, a best-matched candidate is selected for numerical optimization to maximize oil production rates with constraints satisfying field conditions. Excellent history-matching...

... efficiency, are considered. Appropriate linear and nonlinear constraints, involving the geometry of the well configuration, injection rates, and injected mass (for pressure management), are specified. Two derivative-free algorithms, particle swarm optimization (PSO) and differential evolution (DE...

... n f . The force balance of the internal boundary is implemented with contact and stick constraints. Geomechanics Under dynamic conditions, linear, poroelastic momentum conservation is required allowing resolution of the onset of the rupture and injection-induced seismic events. We solve...

... conditions) and show that with the proper implementation of physical constraints, a robust solution can be trained within a reasonable amount of time and iterations. We revisit some of the limitations presented in previous work [ 1 ] and further the applicability of this method in a forward, pure hyperbolic...

... Abstract When coupling reservoir simulators to surface network solvers, an often used strategy is to perform a rule or priority-driven allocation based on individual well and group constraints, augmented by back-pressure constraints computed periodically by the network solver. The allocation...

... management. In the coupled model the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves which are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the CPU intensive reservoir simulation...

... and robust algorithms to effectively set all local constraints at various measured depths. This paper describes special constructs called "boundary segments" with a similar set of flow rate and pressure control modes to those available for tubinghead or bottomhole well control. In a multisegment well model...

..., with a large historical (70y) and prediction (200y) time periods, 10s of millions of cells and thousands of wells, many injection and production constraints and drilling targets. Each of these giant fields requires a parallel supercomputer to run each individual model in a reasonable time. To couple many...

... multiscale concepts based on the Constraint Energy Minimization (CEM-GMsFEM). CEM-GMsFEM concepts utilize local spectral problems and an energy minimization principle to design multiscale basis functions, which are supported in oversampled regions. A coarse-grid solution defined by these basis functions...

... and constraints, (ii) interact with software to identify, screen, and maximize the opportunity, (iii) interact with reservoir to understand the physics for meaningful solutions, and (iv) interact with candidate solutions for the most rigorous one. Data analytics is used in this interactive workflow, boosting...

... Abstract Solving a large-scale optimization problem with nonlinear state constraints has proven to be challenging when adjoint gradients are not available for computing the derivatives needed in the basic optimization algorithm employed. Here, we present a methodology for the solution...

.... In this context, the modeling workflow has to manage one or several reservoirs, connected to a single FPSO (Floating Production Storage and Offloading) unit through a production and injection networks composed of risers, flowlines, manifolds… In such developments, operation constraints are imposed...