Comparison of design optimization algorithms of a multiply fractured horizontal well

E. A. Kavunnikova, B. N. Starovoitova, S. V. Golovin, A. M. Krivtsov

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


The paper is devoted to comparison of multiple-objectives optimization algorithms in application to the problem of design optimization of a multiply fractured horizontal well (MFHW). The problem is stated either as a single-objective one, where only the income based on Net Present Value (NPV) is maximized, or as a multi-objective problem, where it is necessary to simultaneously find extremes of NPV, the post-fracture oil production and fracturing costs. Three popular stochastic optimization methods are considered: genetic algorithms (GA), simulated annealing (SA) and particle swarm optimization (PSO). Since PSO, SA and GA techniques employ different strategies and computational efforts, the comparison of their efficiency was carried out by testing on synthetic problems and then applied to the example of a MFHW in a low-permeable oil reservoir.

Original languageEnglish
Article number012029
Number of pages8
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 16 Jul 2019
EventAll-Russian Conference and School for Young Scientists, devoted to 100th Anniversary of Academician L.V. Ovsiannikov on Mathematical Problems of Continuum Mechanics, MPCM 2019 - Novosibirsk, Russian Federation
Duration: 13 May 201917 May 2019


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