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Comparison of design optimization algorithms of a multiply fractured horizontal well. / Kavunnikova, E. A.; Starovoitova, B. N.; Golovin, S. V. et al.

In: Journal of Physics: Conference Series, Vol. 1268, No. 1, 012029, 16.07.2019.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Kavunnikova, EA, Starovoitova, BN, Golovin, SV & Krivtsov, AM 2019, 'Comparison of design optimization algorithms of a multiply fractured horizontal well', Journal of Physics: Conference Series, vol. 1268, no. 1, 012029. https://doi.org/10.1088/1742-6596/1268/1/012029

APA

Kavunnikova, E. A., Starovoitova, B. N., Golovin, S. V., & Krivtsov, A. M. (2019). Comparison of design optimization algorithms of a multiply fractured horizontal well. Journal of Physics: Conference Series, 1268(1), [012029]. https://doi.org/10.1088/1742-6596/1268/1/012029

Vancouver

Kavunnikova EA, Starovoitova BN, Golovin SV, Krivtsov AM. Comparison of design optimization algorithms of a multiply fractured horizontal well. Journal of Physics: Conference Series. 2019 Jul 16;1268(1):012029. doi: 10.1088/1742-6596/1268/1/012029

Author

Kavunnikova, E. A. ; Starovoitova, B. N. ; Golovin, S. V. et al. / Comparison of design optimization algorithms of a multiply fractured horizontal well. In: Journal of Physics: Conference Series. 2019 ; Vol. 1268, No. 1.

BibTeX

@article{761bd2f582c94f75b774f7ae9375ae59,
title = "Comparison of design optimization algorithms of a multiply fractured horizontal well",
abstract = "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.",
author = "Kavunnikova, {E. A.} and Starovoitova, {B. N.} and Golovin, {S. V.} and Krivtsov, {A. M.}",
year = "2019",
month = jul,
day = "16",
doi = "10.1088/1742-6596/1268/1/012029",
language = "English",
volume = "1268",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",
note = "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 ; Conference date: 13-05-2019 Through 17-05-2019",

}

RIS

TY - JOUR

T1 - Comparison of design optimization algorithms of a multiply fractured horizontal well

AU - Kavunnikova, E. A.

AU - Starovoitova, B. N.

AU - Golovin, S. V.

AU - Krivtsov, A. M.

PY - 2019/7/16

Y1 - 2019/7/16

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85073910182&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1268/1/012029

DO - 10.1088/1742-6596/1268/1/012029

M3 - Conference article

AN - SCOPUS:85073910182

VL - 1268

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012029

T2 - 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

Y2 - 13 May 2019 through 17 May 2019

ER -

ID: 21995177