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.
|Number of pages||8|
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 16 Jul 2019|
|Event||All-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 2019 → 17 May 2019