Numerical dispersion mitigation neural network for seismic modeling | Sciact - Система учета научной деятельности ИМ СО РАН

Numerical dispersion mitigation neural network for seismic modeling Научная публикация

Журнал

Geophysics
ISSN: 0016-8033 , E-ISSN: 1942-2156

Вых. Данные

Год: 2022, Том: 87, Номер: 3, Страницы: 1-49 Страниц : 49 DOI: 10.1190/geo2021-0242.1

Авторы

Gadylshin K. ¹ , Vishnevsky D. ² , Gadylshina K. ² , Lisitsa V. ¹

Организации

1	Institute of Mathematics SB RAS, Novosibirsk, Russian Federation
2	Institute of Petroleum Geology and Geophysics SB RAS, Novosibirsk, Russian Federation

Информация о финансировании (2)

1	Российский научный фонд	22-21-00738
2	Министерство науки и высшего образования РФ Математический центр в Академгородке	075-15-2019-1613, 075-15-2022-281

In this study, we present a novel approach for seismic modeling combining conventional finite differences with deep neural networks. The method includes the following steps: First, a training dataset composed of a small number of common-shot gathers is generated. The dataset is computed using a finite-difference scheme with fine spatial and temporal discretization. Second, the entire set of common-shot seismograms is generated using an inaccurate numerical method, such as a finite difference scheme on a coarse mesh. Third, the numerical dispersion mitigation neural network is trained and applied to the entire dataset to suppress the numerical dispersion. We tested the approach on two 2D models, illustrating a significant acceleration of seismic modeling. © 2022 Society of Exploration Geophysicists.

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

Web of science:	WOS:000793484400005
Scopus:	2-s2.0-85127127342
РИНЦ:	48420721
OpenAlex:	W4221029989

БД	Цитирований
Scopus	17
Web of science	12
OpenAlex	20
РИНЦ	21