Novel Wavelet Threshold Denoising Method to Highlight the First Break of Noisy Microseismic Recordings
Huailiang Li, Jiahao Shi, Linjia Li, Xianguo Tuo, Kai Qu, Wenzheng Rong
Abstract
We proposed a novel wavelet threshold denoising method based on the discrete wavelet transform for noisy microseismic recordings. This algorithm can simultaneously suppress both the high- and low-frequency noises of the microseismic recordings and further highlight the first break of the noisy microseismic recordings. First, we design an adaptive threshold calculation method based on all the wavelet coefficients in different decomposition levels. Then, a continuous and derivable thresholding function is constructed. By adjusting the preset shape adjustment parameters, a more reasonable thresholding function is determined to achieve the denoising processing for highlighting the first break of the microseismic recordings. Finally, different comparison tests are performed to evaluate the performance of the developed method, and the results indicate that the new method can achieve a more effective denoising result. Application on the real microseismic recordings further confirms that the proposed method can make the corresponding first break more clear.