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

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.