Performing the discrimination of natural and artifical quakes based on the earthquake stations and adapting on AFAD system

Sertçelik F. (Executive) , Irmak T. S. , Yavuz E. , Kafadar Ö. , Livaoğlu H. , Şentürk E. , et al.

Project Supported by Other Official Institutions, 2019 - 2021

  • Project Type: Project Supported by Other Official Institutions
  • Begin Date: September 2019
  • End Date: March 2021

Project Abstract

In this project, it is aimed to classify the blast and the earthquakes occurred in Turkey using velocity based seismometers operated by AFAD by carrying out different methods. It is also one of the essential purpose of this project to obtain linear and quadratic equations discriminating the two different dataset integrated with Turkey’s Seismological Network within a Ui software that will be created by the project team. The seismic networks are generally induced by undetectable events due to artificial blast like explosions especially in mine and tunnel-road construction sites causing the events classified as earthquakes which are not. Approximately 2023 blast sites (stone quarry) and 15000 quakes with less than 2.5 magnitudes (M≤2.5) in the AFAD catalogues were inspired us to reveal the investigation of discrimination analysis. Within the scope of this proposed project (1); acquiring the earthquake records with less than magnitude 2.5 for per station with average 100 events (in the case of at least %20 of events being blast or earthquake record) from AFAD seismological data management, (2) Classifying the events according to their time and location information (day-night, marine-land etc.), (3) detecting first arrival P waves’s direction, (4) determining max. Amplitude of P and S wave and implemetation amplitude ratio method, (5) performing complexity analysis based on integration of P and S wave’s amplitudes at two different time window, (6) applying short-time Fourier and wavelet transforms, (7) calculating the power spectra, (8), Deriving linear and quadratic discrimination equations representing the results for per analyised station, (9), verifying weights coefficients for the methods, (10), making a software using MATLAB program to perform the methods, (11), and It will be set out of Integrating this program to AFAD’s seismic network and provide trains for the software. As a result of the proposed project, a PhD and MSc thesis are planned to be carried out. This project will be a pioneer study for decimation analysis of artificial and naturel source events within the context of AFAD and it could be a promising case study for other seismic networks. The software to develop for the proposed project will be the comprehensive program.