Affiliation:
1. Trofimuk Institute of Petroleum Geology and Geophysics SB RAS; Novosibirsk State University
2. IEC SB RAS; Novosibirsk State University
Abstract
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.
Publisher
Siberian State University of Geosystems and Technologies
Subject
Industrial and Manufacturing Engineering