Generally, trial and error approach is applied in reservoir simulation to collect some amount of data that will be compared in finding the optimal solution of the
development scenario. In this study, genetic algorithm as a directed random search techniques is applied to select the optimum development scenario for X gas field
production. One important parameter to be optimized in a gas field is the plateau time production. X gas field will be developed using one horizontal well. GA has
a role to replace trial and error procedure in finding the best horizontal well length to obtain the optimal plateau time production in X gas field.
The objective function for GA is derived using curve fitting function of the plateau time towards the horizontal well length obtained from some trial cases run in the reservoir simulator. GA also will be executed for the different objective function formulated from smaller amount of simulation data. Smaller amount of
data represent less reservoir simulation cases run in forecasting future reservoir performance.
It may be concluded at the end of this study that GA, with the appropriate objective function, can give conformable result compared with validation result
using reservoir simulator. Moreover, the role of GA in reservoir simulation with derivation of the objective function from smaller amount of data still can obtain
accepted accuracy in finding the optimal solution for field production optimization. This would reduce sufficient amount of time in running reservoir
simulation works.