Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Andrei Erofeev"'
Autor:
Lena Jonson, Andrei Erofeev
This book explores how artistic strategies of resistance have survived under the conservative-authoritarian regime which has been in place in Russia since 2012. It discusses the conditions under which artists work as the state spells out a new state
Publikováno v:
SPE Journal. 26:1812-1823
SummaryWe studied the applicability of a gradient-boosting machine-learning (ML) algorithm for forecasting of oil and total liquid production after hydraulic fracturing (HF). A thorough raw data study with data preprocessing algorithms was provided.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::922493393c541636535525cfb2968ac7
https://doi.org/10.2118/205479-pa
https://doi.org/10.2118/205479-pa
Publikováno v:
Day 3 Tue, November 30, 2021.
We are presenting a new, highly intelligent AI-based ranking system for selecting the most appropriate candidates for well treatment. The system is trained to predict flow rates after hydraulic fracturing (HF) and rank wells by the expected effect of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca7efa24991518550cce4a3ef77f9b1b
https://doi.org/10.2118/204571-ms
https://doi.org/10.2118/204571-ms
Publikováno v:
Transport in Porous Media. 128:677-700
The objective of this work is to study the applicability of various machine learning algorithms for the prediction of some rock properties which geoscientists usually define due to special laboratory analysis. We demonstrate that these special proper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e7b05361d5ff7a387d1def5b8e41993
https://doi.org/10.1007/s11242-019-01265-3
https://doi.org/10.1007/s11242-019-01265-3
Publikováno v:
Progress’19.
Summary The main aim of this work is to study the applicability of Machine Learning (ML) techniques for prediction of rock properties, which are commonly defined via special core analysis (SCAL). The mechanism of SCAL prediction on the basis of routi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f457dce10fae6ce0b6038ca937ba8366
https://doi.org/10.3997/2214-4609.201953059
https://doi.org/10.3997/2214-4609.201953059
Autor:
D. M. Orlov, Vladislav Krutko, Andrei Erofeev, Vladislav Aleksandrovich Balashov, B.V. Belozerov, Dmitry Koroteev, Ivan Yakimchuk, E. A. Muravleva, Denis Volkhonskiy, Mohammad Ebadi, Evgeny Borisovich Savenkov, Nikolay Evseev
Publikováno v:
Journal of Natural Gas Science and Engineering. 87:103750
The development of tight hydrocarbon resources has a significant impact on the future of the energy market. Digital Rock Physics (DRP) is technically recognized as an effective method for characterizing reservoir rock properties. However, there is un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0a6abd64b68b44b6f42b5e2d567e721
https://doi.org/10.1016/j.jngse.2020.103750
https://doi.org/10.1016/j.jngse.2020.103750
Publikováno v:
Russia – Art Resistance and the Conservative-Authoritarian Zeitgeist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e8351d828c29c1bf55b8f53762c256e
https://doi.org/10.4324/9781315186856-17
https://doi.org/10.4324/9781315186856-17
This chapter examines several phenomena in contemporary Russian art that seem to intentionally undermine or betray the very discourses that they claim to voice. It argues that these betrayals are a strategic effort towards a redistribution of the sen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7eb63cd52e346764dd7d948e0801fd6
https://doi.org/10.4324/9781315186856-9
https://doi.org/10.4324/9781315186856-9