V.A. Sudakov, A.A. Leontyev, M.F. Validov, T.A. Murtazin, K.D. Shumatbaev, R.M. Habipov, O.G. Gibadullina, R.R. Abusalimova, A.F. Iksanova
DOI: https://doi.org/10.25689/NP.2022.4.252-266
Abstract
A novel domestic software product Gisneiro 2.0 is a complex of machine well logging interpretation algorithms to improve interpreting of a bulk of well logging data that have been gathered during life cycles of a huge number of wells.
Automated interpretation of well logs accelerates the process of well data analysis by orders of magnitude utilizing the geological information available to the fullest extent at that, thus, significantly improving the efficiency of well logging interpretation.
The machine learning and statistical methods employed by the Giseiro 2.0 software allow automated stratigraphic breakdown and lithology differentiation, calculation of reservoir properties, determination of net thicknesses and types of saturation.
The software designer and the TATNEFT Company have tested the Gisneiro 2.0 program package withing the framework of a pilot project involving creation of a database, interpretation of well logs, analysis and statistical interpretation of well logging and core data. The results of well logging interpretation in the semi-automatic mode were obtained, in that number, stratigraphic breakdown, boundaries of net thicknesses, reservoir characteristics, and core analysis.
References
Authors
V.A. Sudakov, Deputy Director for Innovation Technologies, Institute of Geology and Petroleum Technologies, Kazan Federal University
18, Kremlevskaya st., Kazan, 420000, Russian Federation
E-mail: VlASudakov@kpfu.ru, sudakovav@gmail.com
https://orcid.org/0000-0002-68...
A.A. Leontyev, Leading Engineer, Institute of Geology and Petroleum Technologies, Kazan Federal University
18, Kremlevskaya st., Kazan, 420000, Russian Federation
E-mail: Leontiev94@gmail.com
https://orcid.org/0000-0002-69...
M.F. Validov, Leading Engineer, Institute of Geology and Petroleum Technologies, Kazan Federal University
18, Kremlevskaya st., Kazan, 420000, Russian Federation
E-mail: marat.validov@gmail.com
T.A. Murtazin, Leading Engineer, Institute of Geology and Petroleum Technologies, Kazan Federal University
18, Kremlevskaya st., Kazan, 420000, Russian Federation
E-mail: aleksandrovich313@yandex.ru
K.D. Shumatbaev, Chief Expert in Petrophysical Studies, Reservoir Engineering Directorate, PJSC TATNEFT
75, Lenin st., Almetyevsk, 423230, Russian Federation
E-mail: Shumatbaevkd@tatneft.ru
R.M. Habipov, Head of Reservoir Development and Subsoil Use Monitoring Department, Reservoir Engineering Directorate, PJSC TATNEFT
75, Lenin st., Almetyevsk, 423230, Russian Federation
E-mail: HabipovRM@tatneft.ru
O.G. Gibadullina, Head of Geological Data Automation and Unconventional Reserves On-Line Estimate Laboratory, Geological Exploration Department, TatNIPIneft–PJSC TATNEFT
32, Musy Jalil st., Bugulma, 423230, Russian Federation
E-mail: domanik@tatnipi.ru
R.R. Abusalimova, Chief of Unconventional Reserves Oil Potential Estimate Sector, Geological Exploration Department, TatNIPIneft–PJSC TATNEFT
32, Musy Jalil st., Bugulma, 423230, Russian Federation
E-mail: Abusalimova-RR@tatnipi.ru
A.F. Iksanova, Leading Engineer, Geological Data Automation Sector, Geological Exploration Department, TatNIPIneft–PJSC TATNEFT
32, Musy Jalil st., Bugulma, 423230, Russian Federation
E-mail: IksanovaAlsuF@tatnipi.ru
For citation:
V.A. Sudakov, A.A. Leontyev, M.F. Validov, T.A. Murtazin, K.D. Shumatbaev, R.M. Habipov, O.G. Gibadullina, R.R. Abusalimova, A.F. Iksanova Vozmozhnosti mnogoskvazhinnyh tehnologij v PK «Gisnejro 2.0» pri interpretacii dannyh GIS [Gisneiro 2.0 program package’s well logging interpretation capabilities allow involving huge number of wells]. Neftyanaya Provintsiya, No. 4(32), 2022. pp. 252-266. DOI https://doi.org/10.25689/NP.2022.4.252-266. EDN GNEHKM (in Russian)