Research on Recognition Methods of Micro-seismic Events Based on Convolutional Neural Network
In recent years,the development of science and technology has brought considerable benefits to society.Mi-cro-seismic event identification using deep learning has also become a research hotspot.Unconventional oil and gas exploration and development has become the main way of current oil and gas resources.Unconventional exploration and development also requires micro-seismic event identification.For micro-seismic event identification,the main solution is to detect micro-seismic events quickly and accurately,which is of great significance to oil exploration work.In order to solve the shortcomings of introducing uncer-tainty in extracting features,in this paper,the micro-seismic signal data is generated by the forward modeling of the rake pre-wave,and the Gaussian voice is added for the model research,and the convolutional neural network is used to identify the mi-cro-seismic events.The identification method is realized through the steps of constructing a data set,building a network model,and evaluating the output results of the model.After repeated experiments and simulation experiments,the method of convolutional neu-ral network can quickly and accurately detect the effective signal of micro-seismic and remove redundant information,and improve the effective data transmission of microseismic.
万方数据
维普
