| Summary: | 碩士 === 國立交通大學 === 土木工程學系 === 100 === The data reduction of existing borehole seismic methods are currently based on travel-time analysis in which first-arrival times of the seismogram are manually picked. However, manual picking is not efficient and depends heavily on the data quality and analyst’s experience. Besides the difficulty of picking first arrivals in the time domain, no information is obtained regarding the effective frequency of the analysis. Several automatic picking methods were proposed to increase the efficiency of data processing. But most of them are based on time-domain analysis and work well only on some specific conditions. Data reduction methods based on the frequency domain and time-frequency domain were proposed in the study. The aim of the study was to observe the behavior of the borehole seismic waves from different domains (i.e. frequency and time-frequency domain) and propose a semi-automatic procedure for more objective first-arrival time picking. Field data from PS-Log testing and down-hole testing were used to evaluate the feasibility of the proposed procedure, in particular for the shear wave velocity.
In the frequency domain, the phase velocity can be calculated from the phase shift of two receiving stations in each frequency. To avoid the difficulty of unwrapping phase angles in lack of low frequency components, the formation around the borehole is assumed homogeneous and isotropic such that the phase velocity can be calculated from the slope of the phase difference versus frequency at certain frequency range. A better understanding of the seismic signal can be achieved by time-frequency analysis, such as multi-filter analysis or wavelet transform. In the time-frequency domain, a semi-automatic procedure was proposed to determine the first arrival times from the envelope of the time-frequency spectrum at specific frequency range.
Evaluation using field data shows that the spectral analysis method is suitable for PS-Log testing with stable source and two simultaneous recording channels. The method is easy to be automated and yields Vs and the corresponding effective frequency. However, more study should be conducted to overcome occasional failure in low S/N data. The semi-automatic time-frequency spectrum analysis, either based on multi-filter analysis or Morlet wavelet transformation, works well both in PS-Log testing and down-hole testing. The picked first arrival times from the proposed method agree well with the manually-picked results in high quality data. The procedure is stable and yields reasonable results in data with low S/N. But it should be noted that the method inherit the tradeoff between frequency and time resolution from the time-domain analysis. The parameters used in the time-frequency analysis should be optimized for different source types. The parameters for PS-Log testing and down-hole testing were suggested respectively in the study and verified by the field data.
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