| The automatic pick of seismic first arrivals plays a key role in seismic data processing such as refraction static correction, VSP data interpretation, shallow refraction exploration and seismic tomography, as the accuracy directly influences the processing result. In addition, dealing with these data annually spends much of time, which brings huge challenge for real-time monitoring, quick analysis, the quality evaluation and rapid processing. Because of these, the picking speed directly affects the work efficiency.Finding a kind of highly efficient and stable automatic picking method is deserving of research for high density seismic exploration data, and much more important thing is to speed up the picking of first-arrivals and improve the efficiency of monitoring and analysis for the high density seismic exploration field, with guaranteeing the precision of high density seismic exploration data.Firstly, the thesis introduces briefly the storage structure of seismic data and automatic first-arrival picking, and focus on analytizing three methods:using energy ratio, relevent and nerve network, and then the method of energy ratio is accepted. And then I illustrate the advantage of using wavelet transform in picking. On this basis, I propose an improved method using energy ratios. Using wavelet transforming, we obtain the low frequency band, which is replaced the original data body to be picked of first arrivals. So that it reduces workload and improves the efficiency. And then using improved algorithm to pick of first-arrival for increasing accuracy. Finally, I use the median filter to first arrivals in order to obtain more accurate result.On the basis of the algorithm, I designed and developed the corresponding sesimic exploration data analysis software on the development platform of Visual C++ 6.0. It includes many functions, such as real-time display of seismic data, waveform operation, picking of first-arrivals, amplitude recovery and wavelet transform. |
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