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Detailed explanation of the principle:
Microseismic data processing and interpretation involves multiple steps, including data preprocessing, noise suppression, signal display, waveform analysis, seismic phase picking and microseismic event location. Each step is explained in detail below:
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Data preprocessing: Data preprocessing aims to remove trends and means from the data for better analysis of seismic signals. Common preprocessing methods include detrending (removing linear trends), demeaning (subtracting the average value of the signal), etc.
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Noise suppression: Noise suppression is to suppress background noise in order to extract microseismic signals. Commonly used methods include filter design, of which low-pass filters are a common choice, which can filter out high-frequency noise and retain the low-frequency components of seismic signals.
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Signal display: Signal display is for visually observing the amplitude and waveform characteristics of seismic signals. By drawing time series graphics of seismic signals, preliminary visual analysis of the data can be performed to check data quality and signal characteristics.
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Waveform analysis: Waveform analysis aims to further analyze the spectral characteristics, amplitude changes, and time differences between events of seismic signals. Common methods include time-frequency analysis (such as wavelet transform), power spectrum analysis, frequency filtering, etc., to obtain more information about seismic signals.
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Seismic phase picking: Seismic phase picking is to identify specific seismic phases in seismic signals, such as P waves, S waves, etc. Usually threshold is used