The two important characteristics of microseismic are: tiny and shear rupture. The resulting monitoring characteristics are significantly different from those used to monitor natural earthquakes and artificial seismic exploration sources. Microseismic and its monitoring characteristics are the cornerstone of the development, application, and judgment of microseismic monitoring methods. First, different monitoring methods were investigated, suggestions were puts forward for their development and scope of application, and the reasons why some methods have not improved much were exploved. Among them, the most important ones are: when the number of microseismic, positive and negative initial motion, and signal-to-noise ratio are not easy known, it is necessary to conduct large-scale trial calculations and statistically investigate the combination of focal mechanisms with a high probability, so as to complete reasonable migration stacking. Mathematical statistics in the denoising should be used throughout all steps of detection, and so on. From the perspective of probability and mathematical statistics, following the characteristics of microseismic and its monitoring, the results show that microseismic monitoring has to be based on the fact of low signal-to-noise ratio, summarizes and improves the principle and denoising of VS(vector scanning). In the process of VS processing and interpretation automation, a large number of mathematical statistics are implemented to confirm the noise coherence parameters and analyze the microseismic activity. It makes up also for the defect that the vertical accuracy of ground monitoring is poor and cannot confirm the vertical height of the stimulation rock volume. VS has formed a relatively complete ground monitoring system after more than 20 years of research and development. Probability and mathematical statistics are important concepts and tools to ensure the success of the development and application of microseismic monitoring methods.