Abstract:Prediction of magnetic body top based on magnetic anomaly is one of the major objectives of magnetic exploration.It is of great significance for the investigation of magnetic minerals,igneous rocks and magnetic basement.By extracting the magnetic anomalies from a large number of theoretical cuboid models and the maximum values of the first,second,or third derivatives in the vertical direction,three extremum ratios were obtained and a sequence dataset was formed.The constructed BP neural network was trained by the extremum ratio sequences and the depth of the model top to build training samples,and the trained BP neural network was stored for predicting the magnetic body top.Modeling results show that the prediction errors of more than 91% of the training samples are less than 10%,and the prediction of the samples not participating in the training also matches well with the results.The method has been applied for the prediction of the depth of the igneous rock in the YX area,China.The predicted depth highly agrees with the depth of the igneous rocks from drilling data,indicating the effectiveness of the method.
赵文举, 刘云祥, 陶德强, 赵荔, 胡文涛. BP神经网络磁性体顶面埋深预测方法[J]. 石油地球物理勘探, 2020, 55(5): 1139-1148.
ZHAO Wenju, LIU Yunxiang, TAO Deqiang, ZHAO Li, HU Wentao. Prediction of magnetic body top based on BP neural network. Oil Geophysical Prospecting, 2020, 55(5): 1139-1148.
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