A first-arrival picking method for microseismic signals based on approximate negative entropy
A technology of microseismic and negative entropy, which is applied in seismic signal processing, seismology, geophysical measurement, etc., can solve the problem of picking up the first arrival time point of microseismic signals, and achieve accurate picking, fast speed and high accuracy Effect
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experiment example 1
[0077] Experimental example 1 synthesis record
[0078] Simulate and generate a synthetic microseismic record of 100 channels with a sampling frequency of 1000 Hz, each channel has 512 sampling points, and the main frequency of the effective signal is 300 Hz. Gaussian white noise of different intensities is added to the pure seismic record, and the signal-to-noise ratio is obtained from -1dB Synthetic noisy microseismic records to -12dB. In order to verify the influence of SNR on the performance of the first break picking method, firstly, a single trace of noisy microseismic data with a first arrival time of 160 ms is selected from the noisy record with a SNR of -3 dB, as shown in Fig. 2(a) Show. The AIC method, STA / LTA method and approximate negative entropy method are used to pick the first arrival point of this noisy seismic data, and the picking results are shown in Fig. 2(b), Fig. 2(c) and Fig. 2(d) .
[0079]Figure 2(b) is the picking result of the AIC method, and its...
experiment example 2
[0087] Experimental example 2 actual record
[0088] Figure 5 shows a set of actual three-component microseismic data, which contains 15 traces, each with 512 sampling points. AIC, STA / LTA and approximate negative entropy methods are used to extract the first arrival time respectively. It can be seen from the noisy data that the signal-to-noise ratio and signal amplitude on different components are inconsistent, and the data in the three component directions are picked up by AIC, STA / LTA and approximate negative entropy methods respectively. One of the data is extracted from the X, Y, and Z component picking results, and its single-channel waveform is shown in Figure 6. From the single-channel waveform diagram in Figure 6, it can also be seen that when the SNR is high, the positions of the first arrivals picked up by the three methods are close, and the picking error is small. When the SNR is low, the AIC and STA There is obviously a large error in the picking position of th...
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