Energy transition

[ET-01] Extension of low-SNR coherent signal detection method based on spectral matrix analysis by using wavelet transformation and time delay coordinate

*Takayuki Nagata¹, Yusuke Mukuhira², Taku Nonomura¹ (1. Department of Aerospace Engineering, Tohoku University (Japan), 2. Institute of Fluid Science, Tohoku University (Japan))

The detection and analysis of low signal-to-noise-ratio (SNR) events are valuable for source positions mapping of microseismicity and understanding of underground reservoirs. In the previous study, we applied the spectral matrix (SPM) analysis to characterize the motion of 3D particles in the time-frequency domain by eigenvector of SPM and detected the P-wave arrivals of low SNR microseismic events. In the present study, we further extended low-SNR event detection based on the spectral matrix analysis with the wavelet analysis and time delay coordinate. By using wavelet analysis, the optimum length of the time window for frequency analysis is automatically applied for each frequency band. In addition, the introduction of time-delay coordinates increases the dimension of the SPM matrix and improves the SNR in SPM analysis. Particularly, the time delay is beneficial when event signals are coherent. The characteristics of the proposed method were evaluated by applying the method to synthetic signals. Synthetic signals include sinusoidal event signals and colored noise, and the SNR sensitivity test was conducted by changing the intensity of the noise component. The proposed method is robust to noise and shows the potential to detect low SNR coherent signals efficiently.