分形计盒维数的微震波初至自动识别

    Automatic Identification First Arrival of Microseismic Waves by Fractal Box-counting Dimension

    • 摘要: 微震波初至到时的自动拾取是实现微震震源定位的技术难点,也是微震监测数据处理的关键技术之一。在分形原理和计盒维数的基础上,建立了分形计盒维数模型,对不同类型的微震波初至到时的计盒维数特征进行分析和描述,并针对不同微震波时间序列进行分析和研究,提出了分形计盒维数自动识别微震波初至到时的具体方法,利用分形盒维数法对具有不同噪声信号的微震波初至到时进行了研究,提高了自动拾取结果的准确性。研究结果表明,典型的信噪比高的微震波,到时自动拾取的结果与手工拾取的结果基本一致;信噪比低和到时点不清晰的微震波自动拾取必须先经过小波分析后应用计盒维数法来识别。

       

      Abstract: The automatically picking of microseism first arrival time is not only a technical difficulty of fixing the position of microseism focus, but also the key technology of data processing of microseism monitoring. Based on the fractal theory and box-counting dimension, the fractal box-counting dimension model was built. The box-counting dimension features of different types of microseismic waves first arrival time was analyzed and described, and a study on time series of different microseismic waves was conducted. Then, the specific method on how the fractal box-counting dimension automatically identifies the microseismic wave first arrival time was raised. By using the fractal box-counting dimension method to study microseismic waves with different noise signals, the reliability of automatically picking results was advanced. Study results showed that for typical microseism waves with high SNR (Signal Noise Ratio), the automatically picking results were generally same with those by manual. For microseismic waves with low SNR or with ill-defined arrival point, the automatically picking must be proceeded after wavelet analysis, then used the box-counting dimension method to identify.

       

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