Development Of Distributed Microseismic Monitoring Data Processing Software

With the development of digitalization and informatization of mine development,microseismic monitoring technology is widely used.The array composed of microseismic data acquisition stations is used to receive the microseismic signals,and the microseismic data processing software is used to invert the fracturing parameters such as the source position,which is of great significance to guide the fracturing and other production activities.In this project,a distributed microseismic monitoring data processing software based on clustering and BP neural network algorithm is developed.Combined with the microseismic data acquisition station independently developed by the research group,a set of rare microseismic data real-time acquisition,receiving and processing integrated microseismic monitoring system in China is formed.The software design starts with the acquisition of microseismic data,and makes in-depth research on the key factors affecting the microseismic source location,such as the first break picking method,the establishment of work area model,the forward problem,and the source inversion.It uses C # language to complete the collection data acquisition,accurate first break picking,the establishment of work area model,the forward data acquisition,the source inversion algorithm,the real-time monitoring map display,and the real-time monitoring The data processing software of microseismic monitoring is integrated with waveform display and other functions.The software takes source inversion and location as the ultimate goal.Firstly,it receives the microseismic data from the shared memory created by the software or through the microseismic data file;calculates and records the performance parameters of the instrument through the noise and crosstalk data;establishes the initial work area model according to the basic information of the work area;based on the seismic ray theory,it uses the logging data to correct the initial work area model to obtain the final result Based on the established work area model,the forward data of the corresponding work area can be obtained by using the fast marching algorithm;the BP neural network is established according to the basic information of the work area,the forward data is used to train the network,and the test data is selected to verify it,so as to establish the nonlinear relationship between the time difference and the source of the corresponding work area;the measured data are analyzed The fuzzy c-means clustering algorithm is used to pick up the first break,which can quickly and accurately obtain the arrival time difference between the acquisition stations;the arrival time difference is input into the trained BP neural network to invert the source position and draw the 3D image.In addition,the software also includes auxiliary functions such as the map display of the construction site acquisition station and the waveform display of the microseismic data.This project has completed the research and development of distributed microseismic monitoring data software based on C #.The software system is stable and reliable after testing.Combined with the microseismic acquisition station,Internet of things and receiving software developed by China University of Geosciences(Beijing),it can realize high-resolution real-time monitoring of fracturing and other production activities,which has important guiding significance for fracturing and other production activities.