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  • Evolutionary algorithms deliver promising results to gas lift optimization problems


    T. Ray and R. Sarker

    Evolutionary algorithms are a class of stochastic optimization algorithms inspired by the process of natural evolution. They are suitable for complex, real-life optimization problems that have so far been considered intractable. Gas lift is known to be one of the most economic methods for artificially lifting oil.1 This article reports the application of an evolutionary algorithm to find optimal gas injection volumes for oil extraction subject to constraints on gas availability, oil extraction targets and well characteristics. This article also provides insights on the benefits offered by our multi-objective optimization approach, which simultaneously minimizes gas injection while maximizing oil extraction. Results show significant improvement over existing practices for two standard benchmarks of six-well and 56-well problems. For the six-well problem, the algorithm delivered a solution with 35 bopd more-12,775 bbl improvement on a yearly basis-and for the 56-well problem our solution was better off by 243 bopd-88,695 bbl improvement on a yearly basis...

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