Production strategy from a hydrocarbon reservoir plays an important role in optimal field development in the sense of maximizing oil recovery and economic profits. To this end, self-adapting optimization algorithms are necessary due to the great number of variables and the excessive time required for exhaustive simulation runs. Thus, this paper utilizes genetic algorithm (GA), and the objective...

Abstract In this study, we propose the use of a first-order gradient framework, adaptive moment estimation (Adam), in conjunction with stochastic approximation, to well location and trajectory optimization problems. The Adam framework allows incorporation additional information from previous gradients calculate variable-specific progression steps. As result, assists search be adjusted further f...

the most costly operation in the oil exploration is the well network drilling. one of the most effectiveways to reduce the cost of drilling networks is decreasing the number of the required wells byselecting the optimum situation of the rig placement. in this paper, balas algorithm is used as a modelfor optimizing the cost function in oil well network, where the vertical and directional drillin...

Abstract Model-based optimization of placement and trajectories wells in petroleum reservoirs by the means reservoir simulation forecasts is computationally demanding due to high number simulations typically required achieve a local optimum. In this work, we develop an efficient flow-diagnostics proxy for net-present-value (NPV) with adjoint capabilities computation well control gradients appro...

Well placement optimization is considered a non-convex and highly multimodal problem. In this article, modified crow search algorithm proposed to tackle the well This article proposes modifications based on local niching techniques in (CSA). At first, suggested approach verified by experimenting with benchmark functions. For test functions, results of demonstrated higher convergence rate better...