Application of DOE and metaheuristic bat algorithm for well placement and individual well controls optimization

Abstract The design of an optimal gas field development and production management is a complicating task because of influencing various factors on decision-making process. Typical factors include number and type of wells, well locations, and production constraints, economic factors of capital expenditure, operating costs, gas sale price, and different engineering and geological parameters. The situation is further complicated due to uncertainty associated with the nonlinear problem of field development optimization. In this study, first, design of experiment (DOE) techniques including uniform design (UD) and Box-Behnken design (BBD) are used for performance prediction of water drive gas reservoirs. Next, a new metaheuristic bat inspired algorithm (BA) will be applied in optimization process of objective function. Undiscounted net present value (UNPV) is used as an objective function for the determination of optimal number of wells (N), individual well locations (I and J), production rate (Q g ), perforation thickness (H p ) and the limit of tubing head pressure (THP) for different average reservoir permeability (K G ) and permeability anisotropy (K v /K h ). In this regard, part of gas reservoir with an active bottom aquifer based on actual data is simulated in order to predict gas recovery factor and cumulative water production data that are necessary for performing production optimization. The results show that reducing gas production rate increases the UNPV. Reducing production rate increases ultimate recovery factor and decreases cumulative water production. However, considering time value of money, it is favorable to produce with high rates and consequently deplete the reservoir over short time scales in order to compensate the reduction of profit.

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