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基于BP神经网络的时域激电谱Cole-Cole模型参数反演及应用

杨海明 姚卫星 唐塑 潘展超 关力伟

物探与化探2025,Vol.49Issue(2):433-440,8.
物探与化探2025,Vol.49Issue(2):433-440,8.DOI:10.11720/wtyht.2025.1422

基于BP神经网络的时域激电谱Cole-Cole模型参数反演及应用

Parameter inversion and application of the Cole-Cole model for time-domain induced polarization spectra based on the backpropagation neural network

杨海明 1姚卫星 1唐塑 1潘展超 2关力伟2

作者信息

  • 1. 中国地质调查局 乌鲁木齐自然资源综合调查中心,新疆 乌鲁木齐 830057
  • 2. 中国地质调查局 乌鲁木齐自然资源综合调查中心,新疆 乌鲁木齐 830057||中亚造山带成矿预测与找矿示范创新基地,新疆 乌鲁木齐 830057
  • 折叠

摘要

Abstract

The spectral parameters of the Cole-Cole model can improve the resolution of comprehensive interpretation of time-domain in-duced polarization(IP)data,contributing somewhat to the exploration of metal deposits.Applying the backpropagation neural network(BPNN)model to the prediction and inversion of spectral parameters can avoid high computational complexity to improve the inversion speed.Moreover,the BPNN model can fully explore the utilization efficiency of time-domain IP data to enrich the characteristic infor-mation of subsurface ore bodies.Based on this,this study derived the mathematical expression of the time-domain apparent polarizabili-ty attenuation curve using the digital filtering algorithm.With the mathematical expression as the forward/inverse model,this study comparatively analyzed the impacts of four factors-the sample size of the training set,the number of neurons in the input layer,the node number of hidden layers,and the number of hidden layers-on the training and inversion effects of the BPNN model,determining the op-timal model.Furthermore,this study trained the BPNN model using time-domain IP data from eight time windows.Finally,this study applied the trained BPNN model for prediction and inversion based on the measured time-domain IP data.The results indicate that the BPNN model is feasible in inverting spectral parameters based on both theoretical and measured datasets,manifesting high inversion ac-curacy and minor errors.Overall,the results of this study can assist in distinguishing paragenetic and associated minerals and reducing misinterpretation.

关键词

Cole-Cole模型/时间域激电/BP神经网络/反演

Key words

Cole-Cole model/time-domain induced polarization/backpropagation neural network/inversion

分类

地质学

引用本文复制引用

杨海明,姚卫星,唐塑,潘展超,关力伟..基于BP神经网络的时域激电谱Cole-Cole模型参数反演及应用[J].物探与化探,2025,49(2):433-440,8.

基金项目

中国地质调查局矿产资源评价项目"新疆阿勒泰清水泉—昌吉双泉金矿重点调查区调查评价"(DD20230380) (DD20230380)

物探与化探

1000-8918

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