A new Optimization Approach for Solving Well Placement Problem under Uncertainty Assessment, M.Sc. Thesis Sharif University of Technology ; Massihi, Mohsen (Supervisor) ; Roosta Azad, Reza (Supervisor)
Abstract
Determining the best location for new wells is a complex problem that depends on reservoir and fluid properties, well and surface equipment specifications, and economic criteria. Various approaches have been proposed for this problem. Among those, direct optimization using the simulator as the evaluation function, although accurate, is in most cases infeasible due to the number of simulations required. This study proposes a hybrid optimization technique (HGA) based on the genetic algorithm (GA) with helper functions based on the polytope algorithm and the neural network. Hybridization of the GA with these helper methods introduces hill-climbing into the stochastic search and also makes use...
Cataloging briefA new Optimization Approach for Solving Well Placement Problem under Uncertainty Assessment, M.Sc. Thesis Sharif University of Technology ; Massihi, Mohsen (Supervisor) ; Roosta Azad, Reza (Supervisor)
Abstract
Determining the best location for new wells is a complex problem that depends on reservoir and fluid properties, well and surface equipment specifications, and economic criteria. Various approaches have been proposed for this problem. Among those, direct optimization using the simulator as the evaluation function, although accurate, is in most cases infeasible due to the number of simulations required. This study proposes a hybrid optimization technique (HGA) based on the genetic algorithm (GA) with helper functions based on the polytope algorithm and the neural network. Hybridization of the GA with these helper methods introduces hill-climbing into the stochastic search and also makes use...
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