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Zheng Jing, Cao Ziyuan, Jiang Tianqi, et al. Deep belief neural networkbased arrival picking for microseismic data[J]. Journal of Mining Science and Technology, 2018, 3(6): 521-526.
Citation: Zheng Jing, Cao Ziyuan, Jiang Tianqi, et al. Deep belief neural networkbased arrival picking for microseismic data[J]. Journal of Mining Science and Technology, 2018, 3(6): 521-526.
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Deep belief neural networkbased arrival picking for microseismic data

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  • In order to improve the picking accuracy of the weak signal in low signal to noise ratio，a pickup method based on STransform and deep belief neural network（DBN）was proposedThe network model training was divided into two stepsFirst，the original data processed by STransformation was subjected to unsupervised pretraining by using a restricted Boltzmann machine（RBM），and the initial values of the network model parameters were obtainedNetwork parameters adjusted by error backpropagation were used to build the final DBN modelThen，the trained network was used to pick up the dataCompared with pickup results of the STA/LTA method，the method we used has higher antinoise performance
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