EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Minimising the computational time of a waveform based location algorithm

Emmanouil Parastatidis1, Stella Pytharouli1, Lina Stankovic1, Vladimir Stankovic1, and Peidong Shi2
Emmanouil Parastatidis et al.
  • 1University of Strathclyde, Civil and Environmental Engineering, United Kingdom of Great Britain – England, Scotland, Wales (
  • 2University of Grenoble

Accurate and fast localisation of microseismic events is a requirement for a number of applications, e.g. mining, enhanced geothermal systems. New methods for event localisation have been proposed over the last decades. The waveform-based methods are of the most recent developed ones and their main advantage is the ability to locate weak seismic events. Despite this, these methods are demanding in terms of computational time, making real-time seismic event localisation very difficult. In this work, we further develop a waveform-based method, the Multichannel coherency migration method (MCM), to improve the computational time. The computational time for the MCM algorithm has been reported to linearly depend on several parameters, such as the number of stations, the length of the waveform time window, the computer architecture, and the volume of the area we are searching for the hypocentre. To minimise the computational time we need to decrease one or more of the above parameters without compromising the accuracy of the result. We break the localisation procedure into several steps: (1) we locate the event with a relatively large spatial grid interval which will give less potential hypocentral locations and less calculations as a result. (2) Based on the results of step (1) and the locations of maximum coherencies we decrease the grid volume to a quarter of the original volume and the spatial interval to half the original, focusing only around the area identified in step (1). Step (2) is repeated several times for decreased grid volumes and spatial intervals until the hypocentral location does not significantly change any more. We tested this approach on both synthetic and real data. We find that while the accuracy of the hypocentre is not compromised, the computational time is up to  125,000 times shorter.    

How to cite: Parastatidis, E., Pytharouli, S., Stankovic, L., Stankovic, V., and Shi, P.: Minimising the computational time of a waveform based location algorithm, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15664,, 2021.


Display file

Comments on the display

to access the discussion