Automatic denoising and detection of microseismic events using the synchrosqueezing
Typical microseismic data recorded by surface arrays are characterized by low signal-to-noise ratios (SNR). A method for SNR improvement and simultaneous detection of microseismic events in time-frequency domain is presented. The proposed method is based upon synchrosqueezed wavelet transform and custom thresholding of single channel data. The synchrosqueezed wavelet transform allows for the adaptive filtering of time and frequency. Simultaneously the algorithm incorporates a detection procedure that utilizes the thresholded wavelet coefficients and detects arrivals as local maxima in a characteristic function. The algorithm was tested using a synthetic signal and field data.
SEG Technical Program Expanded Abstracts
Mousavi, S., Langston, C., & Horton, S. (2016). Automatic denoising and detection of microseismic events using the synchrosqueezing. SEG Technical Program Expanded Abstracts, 35, 825-829. https://doi.org/10.1190/segam2016-13262052.1