Journal V.22.No.3.2020

Date of publication: 30 Sep 2020

Pages: 2-96

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Section types and oil prospects of the Bazhenov Formation in the Nadym-Ob interfluve

M.A. Fomin, R.M. Saitov

Original article

DOI https://doi.org/10.18599/grs.2020.3.2-11

Petroleum source rocks of the Silurian deposits on the Chernov swell (Timan‑Pechora basin)

I.S. Kotik, T.V. Maydl, O.S. Kotik, N.V. Pronina

Original article

DOI https://doi.org/10.18599/grs.2020.3.12-20

Geochemical features of the organic matter from Jurassic sediments of the Nadym‑Taz interfluve

L.S. Borisova, А.N. Fomin, Е.S. Yaroslavtseva

Original article

DOI https://doi.org/10.18599/grs.2020.3.21-27

A new method of «geochemical logging» for studying Domanic deposits

S.B. Ostroukhov, N.V. Pronin, I.N. Plotnikova, R.K. Khairtdinov

Original article

DOI https://doi.org/10.18599/grs.2020.3.28-37

Quantitative methods for quantification of montmorillonite content in bentonite clays

P.E. Belousov, B.V. Pokidko, S.V. Zakusin, V.V. Krupskaya

Original article

DOI https://doi.org/10.18599/grs.2020.3.38-47

Vosnesensky Cu-porphyry deposit (Southern Urals): formation conditions, trace elements, sulfur isotopes and fluid sources

S.E. Znamensky, N.N. Ankusheva, D.A. Artemiev

Original article

DOI https://doi.org/10.18599/grs.2020.3.48-54

Facies models of the Achimov Formation of East-Urengoiskoe license as the basis for optimizing exploration and field development patterns

A.V. Khramtsova, S.I. Pakhomov, N.Yu. Natchuk, M.P. Kalashnikova, S.V. Romashkin, A.D. Musikhin, N.G. Semenova

Original article

DOI https://doi.org/10.18599/grs.2020.3.55-61

Petro-elastic modeling deliverables for the Kharyaga Permian carbonate deposits

S.I. Gusev

Original article

DOI https://doi.org/10.18599/grs.2020.3.62-68

Junction zone stability in coaxial wells of different diameters (on the example of the Khanty-Mansi Autonomous District oil field)

A.V. Seryakov, M.Yu. Podberezhny, O.B. Bocharov, M.A. Azamatov

Original article

DOI https://doi.org/10.18599/grs.2020.3.69-78

Development of a comprehensive methodology for the forecast of effectiveness of geological and technical measures based on machine learning algorithms

A.A. Kochnev, N.D. Kozyrev, O.E. Kochneva, S.V. Galkin

Original article

DOI https://doi.org/10.18599/grs.2020.3.79-86

Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions

A.D. Chernikov, N.A. Eremin, V.E. Stolyarov, A.G. Sboev, O.K. Semenova-Chaschina, L.K. Fitsner

Original article

DOI https://doi.org/10.18599/grs.2020.3.87-96