Results 161 to 170 of about 1,776,592 (192)
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Wavelet Basis Function of the Microseismic Signal Analysis
2011Wavelet transform is an important method in signal processing for microseismic signals, and the wavelet basis function is the key factor that must be considered in the wavelet signal processing. In this chapter, through the analysis of the commonly used wavelet basis function’s properties, spectrogram, and power spectrum diagram, combined with the ...
Tang Shou-feng +2 more
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Tracking Microseismic Signal Loss From Reservoir to Surface
Proceedings, 2013A comprehensive test is used to compare microseismic monitoring from surface, shallow well and downhole arrays. In particular, a long-aperture borehole array was deployed with sensors spanning from the reservoir depth to surface. This array allows tracking of microseismic signals and measurement of the signal degradation that occurs between the various
S.C. Maxwell +3 more
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Signal and Noise on Buried and Surface Geophones for Microseismic Monitoring
Proceedings, 2013Surface or near-surface monitoring on microseismic events overcomes the low signal by stacking many geophones. To reduce the number of geophones it is essential to find the optimal placement of geophones, to obtain the highest possible signal to noise ratio. The noise level decreases with depth, but the signal is enhanced in near surface layers, due to
C. Czanik, L. Eisner
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A polarization filter method and applications for preprocessing microseismic signals
2013 Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, 2013The microseismic signal generated in rock rupture is wildly used in oilfields to inverse the seismic source and detect the direction and dimension of formation fractures. However, the SNR of effective signal in seismic events is especially low, and in many cases the onset of P- and S-wave is submerged in various noises. In this paper, we use the method
Xin Fu, Hao Chen, Xiu-Ming Wang
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Shape Fitting Remediation of Amplitude Saturation Microseismic Signals
2011The microseismic signal was the main evaluation basis for the monitored objects. In this chapter, we review a variety of analyses and processing methods for microseismic signals, put forward an effective shape fitting remediation method for the amplitude saturation problem in waveform analysis, and analyze the repairing effect by the spectrum, the ...
Tang Shou-feng +2 more
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An automatic recognition method of microseismic signals based on EEMD-SVD and ELM
Computers & Geosciences, 2019Abstract The recognition of microseismic and blasting signals is important for the prediction of geological disasters. Feature parameters for pattern recognition are usually designed manually, which is inconvenient to adopt. A new method combining ensemble empirical mode decomposition (EEMD), singular value decomposition (SVD) and extreme learning ...
Jinyong Zhang +3 more
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Automatic recognition of mining microseismic and blasting vibration signals
Physics of FluidsMicroseismic monitoring systems enable real-time acquisition of vibration signals generated by coal and rock fracturing, deriving key parameters (e.g., event time, spatial location, and energy release) via inversion algorithms for rock burst risk prediction in coal mining operations.
Baolin Li +5 more
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Geophysical Prospecting, 2014
ABSTRACTIn this paper, we treat passive surface microseismic monitoring as a predominantly statistical problem of location sources of weak seismicity recorded in the presence of strongly correlated noise using dense seismic arrays. We introduce two statistically optimal algorithms (adaptive maximal likelihood algorithm and statistically optimal phase ...
Alexander Kushnir +4 more
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ABSTRACTIn this paper, we treat passive surface microseismic monitoring as a predominantly statistical problem of location sources of weak seismicity recorded in the presence of strongly correlated noise using dense seismic arrays. We introduce two statistically optimal algorithms (adaptive maximal likelihood algorithm and statistically optimal phase ...
Alexander Kushnir +4 more
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A first arrival detection method for low SNR microseismic signal
Acta Geophysica, 2018Most of the microseismic signals have low signal-to-noise ratio (SNR) due to the strong background noise, which makes it difficult to locate the first arrival time. Both accuracy and stability of conventional methods are poor in this situation. To overcome this problem, here we proposed a new method based on the adaptive Morlet wavelet and principal ...
Ruiqing Hu, Yanchun Wang
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Application of Multi-scaled Morphology in Microseismic Weak Signal Detection
Proceedings, 2015As reliable signal detection determines the accuracy of microseismic data processing, we have sought an effective method to distinguish useful signal and noise. The theory of this method is multi-scaled mathematical morphology based on slight differences of seismic wave shape.
X.Q. Chen, R.Q. Wang, H.J. Li, C.G. Lu
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