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There are many parameters affecting an improved oil recovery (IOR) process like production and injection rates, fault orientation, injection well placement and perforation locations. It is plausible to optimise an IOR process from the beginning of reservoir production to prevent from high changes and further cost during field development. Here a self-code genetic algorithm was coupled with MATLAB and a simulator to optimise IOR process in an oil reservoir model. Thus, 28 parameters have been optimised simultaneously and net present value (NPV) was taken as an objective function. To speed up the optimisation, it has been considered in the GA self-code to avoid simulating reservoir with previously calculated data. Moreover, the effect of the surrounding faults in the reservoir on the applied IOR process has been studied. Based on achieved results, it could be concluded that the presence of the faults in a reservoir may increase the overall displacement efficiency due to prolonging the contact time and the surface area between the flooding front and the target oil.

A study on the effects of surrounding faults on optimisation of improve oil recovery process by using a genetic algorithm self-code