Open AccessLOCALIZATION OF MICROSEISMIC EVENTS USING PHYSICS-INFORMED NEURAL NETWORK SOLUTION TO THE EIKONAL EQUATION
Author(s) -
Serafim I. Grubas,
Sergey Yaskevich,
Anton A. Duchkov
Publication year - 2021
Publication title -
interèkspo geo-sibirʹ
Language(s) - English
Resource type - Journals
ISSN - 2618-981X
DOI - 10.33764/2618-981x-2021-2-2-32-38
Subject(s) - eikonal equation , microseism , workflow , artificial neural network , event (particle physics) , eikonal approximation , computer science , mathematics , algorithm , physics , mathematical analysis , artificial intelligence , geology , seismology , quantum mechanics , database
The paper demonstrates an algorithm for using physics-informed neural networks in workflow of processing microseismic data regarding 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.