Яндекс.Метрика

S. Grubas, S. Yaskevich, A. Duchkov

Том: EAGE. 82nd EAGE Annual Conference and Exhibition (Amsterdam, Netherlands, 18 - 21 October 2021)
Том: 7 , Год издания: 2021
Многотомное издание: EAGE. 82nd EAGE Annual Conference and Exhibition (Amsterdam, Netherlands, 18 - 21 October 2021)
Место издания: Amsterdam
Страницы: 5228-5232

Аннотация

The paper demonstrates an algorithm for using physics-informed neural networks in the workflow of microseismic data processing and more specifically the problem of localization of microseismic events. The proposed algorithm involves the use of a physics-informed neural network solution to the eikonal equation to calculate the traveltimes of the first arrivals. As a result, the network solution is compared with the observed arrival times to solve the inverse kinematic problem to determine the coordinates of the event locations. Using a synthetic 3D example, it was shown that the average absolute error of the arrival time misfit was less than 0.25 ms, and the average localization error did not exceed 4.5 meters.
индекс в базе ИАЦ: 035790