Том: 22nd International Conference on Computational Science and Its Applications, ICCSA 2022. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Malaga, Spain, July 4-7, 2022)
Том: 13375 LNCS
, Год издания: 2022
Многотомное издание: 22nd International Conference on Computational Science and Its Applications, ICCSA 2022. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Malaga, Spain, July 4-7, 2022)
Страницы: 173-183
Аннотация
Seismic inversion is used in practice as a tool for predicting reservoir properties. It allows one to extract a model with a high level of detail from seismic data, i.e. high-frequency component of the model. In this case, the input data are the time processing results, and the issues related to the low-frequency component of the model are not considered usually. This work describes the implementation of a model-based seismic inversion algorithm. The input data for the inversion are the depth image results in true amplitudes and the depth migration velocity model. The possibilities of seismic inversion are numerically investigated to refine the low-frequency component of the model. Experiments were carried out using synthetic seismic data got for realistic Sigsbee model.
