... 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 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 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...

... dgc optimization wellhead compression module Introduction The onshore gas field in Abu Dhabi is made up of six stacked reservoirs. The reservoirs are named A-F as shown in the Figure 1 . The field is formed in the lower cretaceous carbonate with anticline structure measuring 46 × 26 km...

... 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...

... on the operating life of the wells. As a large number of combinations of these parameters are possible, one of the critical decision to make is to identify an optimal set of these parameters. Using the reservoir simulator directly to evaluate the impact of these sets being unrealistic considering the required...

... 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 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...

... Abstract Production optimization is the method for seeking the best possible well control and schedule plans in order to enhance reservoir performance under a given state and economic constraints. Determining the optimal injection and production control strategies through adjoint gradient-based...

.... The solution combines a quasi- Newton gradient based numerical optimization scheme with a stochastic simplex approximate gradient (StoSAG) algorithm. Because the algorithm is non-intrusive with respect to the fluid flow simulator, we can directly apply the solution on any flow optimization problem without...

..., operationalizing a simulation-based workflow 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...

... 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...

... 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...

... 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...

.... This paper presents a genuine approach for field injection optimization using a streamline-based fuzzy logic system. In a previous paper, we presented an adaptive streamline based fuzzy logic system that uses three input parameters namely injection efficiency (IE), water cut (WC), and injection loss...

... wells; data integration for short-term history matching, reservoir characterization and geologic model updating; flow rate allocation, inflow profiling, probabilistic production forecasting and downhole set point optimization in intelligent well completions; matrix acidizing and hydraulic fracturing...

... 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...

... the work from our previous paper to create a new workflow that allows the VOI assessment of a series of future measurements. The method uses elements available in the CLRM framework, such as history matching and robust optimization. First, we identified the opportunity to combine these elements...

... to optimize the running time and accuracy have been investigated (i.e. explicit or implicit modeling of fracs, rate or THP control, black oil versus EOS models, various up-scaling options, sector versus full field models), tested and calibrated with historical data. In addition, history matching of more than...