Research On Microseismic Positioning And Imaging Based On Improved MFO-SOA Algorithm

With the rapid development of information technology and artificial intelligence,intelligent microseismic positioning and imaging technology is widely used in volcanoes,coal mines,oilfields and many other areas.In recent years,with the increase of coal mining depth and the improvement of mining intensity in China,large energy mine earthquakes occur frequently,resulting in a large number of human and material losses.Therefore,accurate and effective microseismic positioning and imaging methods are hot issues in the field of coal mine monitoring.Microseismic positioning and imaging technology depends on the monitoring data of energy wave signals emitted by microsources when microearthquakes occur.Affected by the heterogeneity of underground medium velocity structure,most energy wave signals do not propagate along the line.At the same time,due to the influence of background noise,there are a lot of errors in monitoring data.The traditional microseismic positioning and imaging technology often can not be solved,and the calculation results deviate from the actual,resulting in low positioning accuracy,poor robustness,slow convergence speed of the algorithm,and the imaging results deviate from the actual.In this paper,the microseismic location and imaging methods are studied in depth.Aiming at the shortcomings of existing methods,a microseismic location and imaging method based on improved MFO-SOA algorithm is proposed.The main research work is as follows:(1)An improved MFO microseismic positioning method is proposed for the problem of time error.Firstly,through cross-correlation algorithm,the difference matrix of time data is calculated.Through robust estimation,the robust difference method is proposed as the objective function of the algorithm.Secondly,based on MFO algorithm,the update strategy of nonlinear inertia weight is adopted.Finally,the location of the source point is iteratively solved by the interaction between individuals in the algorithm.(2)Aiming at the heterogeneity of velocity structure of underground medium,an improved SOA microseismic imaging algorithm is proposed.First,a pair of microseismic events is formed according to the location of all microseismic events.Secondly,the huge sparse matrix is constructed according to the double difference results of events on the time dimension,and the mean square deviation of the matrix is set as the objective function.Again,based on SOA algorithm,the Levy flight strategy is introduced for iterative update.Finally,the Kriging interpolation method is used to invert the imaging results of the whole space.(3)The experimental verification of real data and simulated data is carried out,and the results are compared with various algorithms in terms of positioning accuracy,positioning convergence rate,imaging resolution,imaging convergence rate and imaging stability.The experimental results show that the proposed method has fast convergence speed,high positioning accuracy,strong stability of imaging results and is consistent with the actual situation.