Department of Petroleum Engineering, Eqbal University of Mashhad, University lecturer
Abstract
In this study, in roder to investigate the optimal location of a production well, the fast forward method (FMM) was implemented as a proxy to calculate the bottom hole pressure of wells instead of a comprehensive numerical simulation. Two reservoirs, the standard SPE10 reservoir and the Shadegan reservoir were studied. Also, for optimization, the metaheuristic particle swarm algorithm (PSO) has been used which the combination of two methods called PSO-FMM. This method is a fast forecasting method and is highly capable so that it enhances the objective function up to 20% , compared to the conventional well drilling methods. Also, this method has a considerable speed so that it reduced the simulation time 10% of direct stimulation (PSO). This study also proved that the fast forward FMM method is very compatible with numerical simulation-based methods for multi-well location optimization problems (SPE 10 standard model) and a single well optimization (one-sector of Shadegan reservoir).
rostami, S. (2021). Optimizing well placement via metaheuristic algorithms (case study: Shadegan fields). Construction science and technology, 2(1), 55-69.
MLA
Sadra rostami. "Optimizing well placement via metaheuristic algorithms (case study: Shadegan fields)", Construction science and technology, 2, 1, 2021, 55-69.
HARVARD
rostami, S. (2021). 'Optimizing well placement via metaheuristic algorithms (case study: Shadegan fields)', Construction science and technology, 2(1), pp. 55-69.
VANCOUVER
rostami, S. Optimizing well placement via metaheuristic algorithms (case study: Shadegan fields). Construction science and technology, 2021; 2(1): 55-69.
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