摘要
针对传统反演方法存在依赖初始模型、反演时间较长等问题,提出一种基于改进残差网络的大地电磁反演方法。该方法首先构造不同形状和不同电阻率的地电模型,在TM模式下正演得到视电阻率数据,组成数据集;然后在经典的残差网络ResNet基础上进行改进得到一种新的反演网络iResNet(improved residual network),并使用上述数据集训练该网络;最后将视电阻率数据输入到训练好的网络中,直接得到反演结果。实验结果表明,该方法能快速、准确地反演出地电模型的位置、形态和电阻率值,具有较好的泛化能力和抗噪能力,并能有效解决大地电磁实测数据问题。
Traditional inversion techniques rely on initial models and exhibit prolonged inversion times.This study proposed a magneto-telluric inversion method based on an improved residual network.Specifically,geoelectric models of varying shapes and resistivity val-ues were established,and apparent resistivity data were obtained using the TM mode,forming a dataset.Then,a novel inversion net-work-iResNet(an improved residual network)-was established by improving classic residual network ResNet,and the new network was trained using the afore-mentioned data set.Finally,the apparent resistivity data were input to trained network,directly producing in-version results.The experimental results demonstrate that the method proposed in this study can accurately determine the positions,shapes,and resistivity values of the geoelectric models through swift inversion,suggesting high generalization and anti-noise capabili-ties.Therefore,this method can effectively deermine measured magnetotelluric data.
作者
李思平
刘彩云
熊杰
田慧潇
王方
LI Si-Ping;LIU Cai-Yun;XIONG Jie;TIAN Hui-Xiao;WANG Fang(School of Electronics Information,Yangtze University,Jingzhou434023,China;School of Information and Mathematics,Yangtze University,Jingzhou434023,China)
出处
《物探与化探》
CAS
北大核心
2023年第6期1508-1518,共11页
Geophysical and Geochemical Exploration
基金
国家自然科学基金项目(62273060)
长江大学大学生创新创业项目(Yz2022055)。
关键词
残差网络
大地电磁
反演
residual network
magnetotelluric
inversion
