... Abstract Field development planning activities involve decisions that entail multi-billion-dollar investments. Making right design choices is crucial to the techno-economic success of the project. In this paper we demonstrate how state-of-the-art numerical model-based optimization techniques...

... Abstract In giant reservoirs, production sustainability strongly depends on the identification of opportunities for infill drilling. This paper presents the use of Machine Learning to speed-up and improve the efficiency of the evaluation of future infill wells, in an effort to optimize field...

... and portfolio management production control azer abdullayev ihab nabil mohamed reservoir simulation reservoir surveillance upstream oil & gas artificial lift system gas well deliquification uae government ahmed mohamed al bairaq compressor study dgc optimization integrated asset model...

... Abstract In this study, we investigate the use of deep learning-based and kernel-based proxy models in nonlinearly constrained production optimization and compare their performances with directly using the high-fidelity simulators (HFS) for such optimization in terms of computational cost...

... Abstract In this work we discuss the successful application of our previously developed automated scenario reduction approach applied to life-cycle optimization of a real field case. The inherent uncertainty present in the description of reservoir properties motivates the use of an ensemble...

... Abstract The topic of the paper is an approach to find optimal regimes of miscible gas injection into the reservoir to maximize cumulative oil production using a surrogate model. The sector simulation model of the real reservoir with a gas cap, which is in the first stage of development...

... is the cumulative time. We take place in the framework of an optimization of the production strategy under uncertainty. Uncertainty is represented by a set of geological models for which the calibration of the history of production data has been made. The objective is to propose an optimal production strategy...

... Drainage strategy optimization under geological uncertainty, was first addressed by Van Essen ( Van Essen, et al., 2009 ) using an adjoint technique to evaluate the gradient in the optimization algorithm. A practical challenge with adjoint methods, however, is that they are intrusive in terms...

... Abstract Standard approaches to optimization under uncertainty in reservoir simulation require use of multiple realizations, with variable parameters representing operational constraints and actions as well as uncertain scenarios. We will show how appropriate use of local optimization within...

... ) ≥ 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...

... to optimize design to keep up with the field operation schedule remains the biggest challenge owing to the slow model-to-design turnaround cycle. The objective of this project is to apply the ensemble learning-based model concept to this issue and, for the purpose of completion design, we summarize...

... Abstract In this paper we present an enhanced and new optimization algorithm based on Particle Swarm Optimization (PSO) that can be used in reservoir characterization applications to determine multiple solutions that reproduce measurements within satisfactory accuracy. The method is illustrated...

... process but it generated severely uneven distributions of temperature, pressure, and saturation around wells due to the high reservoir heterogeneity. An improved steam circulation start-up methods instead of cycle steam stimulation is needed to overcome the problems. We developed an optimization method...

... Abstract In field development and management, optimization has turned out to be an integral component for decision-making. Optimization involves computationally intensive complex formulations but simplifies making decisions. For reaching the optimal solution to a defined objective function...

... Full-field injection optimization is a complex task requiring continuous injection rate adjustments of many injectors simultaneously. Therefore, an intelligent method is needed to assist with this endeavor. Fuzzy logic has been employed in the oil and gas industry for a number of years...

... to provide the operator information on past and future events to give engineer insights into the current state of the well and reservoir systems, and to provide information helpful for set point optimization of downhole inflow control valves or active flow control devices? – How can the considered...

... Abstract Various studies have been conducted to optimize oil production in unconventional reservoirs using gas injection processes. Some studies determined the optimal design of hydraulic fractures through horizontal wells while others optimized the placement of horizontal wells to maximize oil...

... Gradient-based optimization methods use the information provided by the objective function derivatives to update the control variables. The gradient can be evaluated using methods based on finite difference approximation ( Yeten et al., 2004 ; Wang et al., 2009 ), although the computational cost...

... cases. reservoir simulation information production data procedure Artificial Intelligence leeuwenburgh observation time history matching optimization time-lapse seismic survey water front workflow Upstream Oil & Gas barros multiple production measurement production measurement...

... Abstract Developing an efficient and optimized field development plan is a crucial and vital task that aims to increase the productivities as well as the recovery factors of oil and gas fields and hence increase the profitability in the most effective manner. In this paper, a novel algorithm...