Abstract

A parallel genetic algorithm has been applied successfully to design a production plan that is substantially superior to that obtained using a conventional engineering approach. The reservoir, a dipping structure, was expected to yield optimum production using a rolling line drive from downdip to updip positions. The simulation allowed for 3800 positions for each of 11 wells, giving a total of 1.3×1031 options. The genetic algorithm sampled 1650 of these and was able to identify seven solutions that would increase production by over 30% compared with the rolling line drive. In contrast, a random search using 850 samples managed to find only two plans that improved production; in each of these cases the improvement was less than 1%.

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