Shear wave slowness prediction and application based on BP neural network optimized by AdaBoost algorithm

Jun ZHAO, HaoChen PEI, MouBing LUO, Yu PENG, Xin SHI, Xuan HE

Prog Geophy ›› 2025, Vol. 40 ›› Issue (5) : 2085-2096.

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Prog Geophy ›› 2025, Vol. 40 ›› Issue (5) : 2085-2096. DOI: 10.6038/pg2025II0277

Shear wave slowness prediction and application based on BP neural network optimized by AdaBoost algorithm

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Abstract

Due to the lack of shear wave time difference data in the study area and the poor accuracy of conventional shear wave time difference prediction methods as a result of coal seam hole enlargement, the AdaBoost algorithm was introduced to optimize BP neural network method for predicting shear wave time difference. The prediction model of shear wave time difference is established by selecting the sensitive logging curves and setting the best model parameters to improve the prediction accuracy of shear wave time difference. Also, the prediction effect of shear wave time difference by multiple linear regression method, BP neural network method and AdaBoost optimized BP neural network algorithm is compared. The rock mechanical parameters and brittleness characteristics of coal seam are evaluated by the predicted shear wave time difference, and the types of coal structure are classified according to the relationship between the brittleness index and the Young's modulus. The results show that the BP neural network optimization model based on AdaBoost can predict the shear wave time difference efficiently, and the average relative error of the prediction results is 2.7%. The brittleness index is calculated by the predicted shear wave time difference and the coal structure type is identified, which is in good agreement with the core description. This approach can effectively improve the prediction accuracy of shear wave time difference and provide reliable data support for coal seam brittleness evaluation and coal structure identification.

Key words

AdaBoost / BP neural network / Shear wave time difference / Brittleness / Coal structure type

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Jun ZHAO , HaoChen PEI , MouBing LUO , et al . Shear wave slowness prediction and application based on BP neural network optimized by AdaBoost algorithm[J]. Progress in Geophysics. 2025, 40(5): 2085-2096 https://doi.org/10.6038/pg2025II0277

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