Microseismic data are typically characterized as low S/N. The noise suppression or S/N enhancement is often desired to enhance the waveform quality for better processing results. We apply time-frequency denoising using a combination of an S transform and a continuous wavelet transform. A thresholding function is used to suppress the noise energy in the transform domain and the filtered waveforms are reconstructed. We show waveform examples for a set of downhole microseismic data from China. We find that with good S/N data, the used workflow suppresses the background noise efficiently while preserving the vector fidelity of signal waveform. However, when the S/N becomes very low (～1), part of the signal also gets suppressed along with noise energy.
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