Science activity

Articles (11) More info

1	Bratchikov D. , Cheverda V. , Gadylshin K. Born approximation and transfer learning to accelerate the training stage in data-driven end-to-end approach for seismic monitoring in viscoelastic media In compilation Cуперкомпьютерные дни в России: труды международной конференции, 23–24 сентября 2024 г., Москва. – Москва., 2025. – C.3-17. – ISBN 978-5-317-07287-2. DOI: 10.1007/978-3-031-78459-0_1 Scopus OpenAlex
2	Gondyul E. , Lisitsa V. , Gadylshin K. , Vishnevsky D. Numerical dispersion mitigation neural network with velocity model correction Computers and Geosciences. 2025. V.196. 105806 :1-12. DOI: 10.1016/j.cageo.2024.105806 РИНЦ
3	Gadylshin K. , Gondyul E. , Lisitsa V. , Gadylshina K. , Vishnevsky D. Mitigation of numerical dispersion in seismic data in spectral domain with neural networks Soil Dynamics and Earthquake Engineering. 2024. V.187. 109028 :1-15. DOI: 10.1016/j.soildyn.2024.109028 WOS Scopus РИНЦ OpenAlex
4	Gondyul E. , Lisitsa V. , Gadylshin K. , Vishnevsky D. Numerical Dispersion Mitigation Neural Network with the Model-Based Training Dataset Optimization In compilation Computational Science and Its Applications – ICCSA 2023 Workshops Athens, Greece, July 3–6, 2023, Proceedings. – Springer., 2023. – Т.Part III. – C.19-30. – ISBN 9783031371103. DOI: 10.1007/978-3-031-37111-0_2 Scopus OpenAlex
5	Gadylshin K. , Lisitsa V. , Vishnevsky D. , Gadylshina K. Hausdorff-distance-based training dataset construction for numerical dispersion mitigation neural network Computers and Geosciences. 2023. V.180. 105438 :1-9. DOI: 10.1016/j.cageo.2023.105438 WOS Scopus РИНЦ OpenAlex
6	Bratchikov D. , Gadylshin K. Seismic Monitoring of Hydrocarbon Deposits Using a Viscoelastic Medium Model Based on Deep Learning In compilation Computational Science and Its Applications – ICCSA 2023 Workshops Athens, Greece, July 3–6, 2023, Proceedings. – Springer., 2023. – Т.Part III. – C.59-75. – ISBN 9783031371103. DOI: 10.1007/978-3-031-37111-0_5 Scopus OpenAlex
7	Protasov M. , Gadylshin K. , Neklyudov D. , Klimes L. Full Waveform Inversion Based on an Asymptotic Solution of Helmholtz Equation Geosciences. 2023. V.13. N1. 19 :1-13. DOI: 10.3390/geosciences13010019 РИНЦ
8	Gadylshin K. , Silvestrov I. , Bakulin A. Deep-learning-based local wavefront attributes and their application to 3D prestack data enhancement Geophysics. 2023. V.88. N3. P.V277-V289. DOI: 10.1190/geo2022-0226.1 РИНЦ
9	Gadylshin K. , Vishnevsky D. , Gadylshina K. , Lisitsa V. Numerical dispersion mitigation neural network for seismic modeling Geophysics. 2022. V.87. N3. P.1-49. DOI: 10.1190/geo2021-0242.1 WOS Scopus РИНЦ OpenAlex
10	Cheverda V. , Bratchikov D. , Gadylshin K. , Golubeva E. , Malakhova V. , Reshetova G. Subsea Methane Hydrates: Origin and Monitoring the Impacts of Global Warming Applied Sciences. 2022. V.23. N12. 11929 :1-17. DOI: 10.3390/app122311929 WOS Scopus РИНЦ OpenAlex
11	Cheverda V.A. , Bratchikov D.S. , Gadylshin K.G. , Golubeva E.N. , Malakhova V.V. , Reshetova G.V. Development of a Methodology for Monitoring the State of Methane Hydrate Deposits of the East-Siberian Shelf Geophysics. 2022. V.507. NSUPPL 3. P.S424-S430. DOI: 10.1134/S1028334X22601419 WOS Scopus РИНЦ OpenAlex

Conference theses (1) More info

1	Bakulin A. , Silvestrov I. , Dmitriev M. , Neklyudov D. , Protasov M. , Gadylshin K. Data-domain reflection tomography for initial velocity model building using challenging 3d seismic data SEG Technical Program Expanded Abstracts. 2019. P.5120-5124. DOI: 10.1190/segam2019-3214902.1

Conference attendances (2) More info

1	Чеверда В.А. , Гадыльшин К.Г. , Решетова Г.В. Multiparameter inverse problems of seismic wave propagation in geological media Евразийская научная конференция “Обратные и некорректные задачи в естествознании и искусственный интеллект” 16-20 Apr 2024
2	Bratchikov D. , Gadylshin K. Seismic Monitoring of Hydrocarbon Deposits Using a Viscoelastic Medium Model Based on Deep Learning The International Conference on Computational Sciences and its Applications 03-06 Jul 2023