Zobrazeno 1 - 10
of 60
pro vyhledávání: '"N. Bukhanov"'
Publikováno v:
ECMOR 2022.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce8704a30081569087e3c71f86ef0b0c
https://doi.org/10.3997/2214-4609.202244040
https://doi.org/10.3997/2214-4609.202244040
Publikováno v:
83rd EAGE Annual Conference & Exhibition.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e4a0fe5ccc47f56ffe01c8d46a3ea29
https://doi.org/10.3997/2214-4609.202210139
https://doi.org/10.3997/2214-4609.202210139
Publikováno v:
Second EAGE Subsurface Intelligence Workshop.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49ee29942d4952e6f17d3f45ed86bcbd
https://doi.org/10.3997/2214-4609.2022616002
https://doi.org/10.3997/2214-4609.2022616002
Publikováno v:
Sixth EAGE Rock Physics Workshop.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d529946ee42b5cf32dc74c2d987f4251
https://doi.org/10.3997/2214-4609.2022617002
https://doi.org/10.3997/2214-4609.2022617002
Autor:
Anna V. Kalyuzhnaya, Anton Voskresenskiy, Anna V. Bubnova, Irina Deeva, N. Bukhanov, Petr Andriushchenko, Nikolay O. Nikitin
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779603
ICCS (1)
ICCS (1)
In this paper, a multipurpose Bayesian-based method for data analysis, causal inference and prediction in the sphere of oil and gas reservoir development is considered. This allows analysing parameters of a reservoir, discovery dependencies among par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70aefe1963dd367487323e63303a5128
https://doi.org/10.1007/978-3-030-77961-0_33
https://doi.org/10.1007/978-3-030-77961-0_33
Publikováno v:
EAGE/AAPG Digital Subsurface for Asia Pacific Conference.
Summary We propose a method for well placement inspired by recent achievements in machine learning and data science which is able to offer options for well positions based on variational forecast with existing data perturbations. To benchmark our app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfbeea99aefaa8f387746a1b26337470
https://doi.org/10.3997/2214-4609.202075010
https://doi.org/10.3997/2214-4609.202075010
Autor:
Rafael Brandão, Anton Voskresenskiy, N. Bukhanov, O. Popova, M. Butorina, E. Vital Brazil, Z. Filippova, Vinícius C. V. B. Segura
Publikováno v:
Scopus-Elsevier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19dda4cd2626c33a9b356a3a25591ae8
https://doi.org/10.3997/2214-4609.202053163
https://doi.org/10.3997/2214-4609.202053163
Publikováno v:
Saint Petersburg 2020.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57ac9fe53f922ccfde78d3451702dcf0
https://doi.org/10.3997/2214-4609.202053177
https://doi.org/10.3997/2214-4609.202053177
Autor:
Petr Andriushchenko, N. Bukhanov, Anton Voskresenskiy, Anna V. Bubnova, Anna V. Kalyuzhnaya, Irina Deeva
Publikováno v:
Data Science in Oil & Gas.
Summary In this paper, the authors investigated the approach of Bayesian networks to the analysis of parameters of oil and gas fields. The study of existing approaches and methods of probabilistic modeling in relation to the problems of analyzing the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::696d86978ba17f2ccae7ae68ca166c3d
https://doi.org/10.3997/2214-4609.202054026
https://doi.org/10.3997/2214-4609.202054026
Autor:
N. Bukhanov, Ilya V. Derevitskii, Anastasia A. Funkner, Ksenia Balabaeva, Vladimir Fonin, Sergey V. Kovalchuk
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030503703
ICCS (1)
ICCS (1)
The paper presents an ongoing research project aimed towards the development of an approach to modeling of information spreading in complex organizations during providing service to customers and performing domain-specific business processes (BP). Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71be1e991281212df5342026f6d8494c
https://doi.org/10.1007/978-3-030-50371-0_49
https://doi.org/10.1007/978-3-030-50371-0_49