3-D Gravity data inversion based on Enhanced Dual U-Net Framework

Three-dimensional gravity inversion is an effective method for restoring underground density distribution from gravity anomaly data. Conventional regularization inversion has good data fitting, but its inversion model has insufficient model fitting capabilities due to its low-depth resolution. Altho...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2023-01, Vol.61, p.1-1
Hauptverfasser:	Dong, Siyuan, Jiao, Jian, Zhou, Shuai, Lu, Pengyu, Zeng, Zhaofa
Format:	Artikel
Sprache:	eng
Schlagworte:	Data models Deep learning Density distribution Distribution enhanced framework Fitting Frameworks Geophysical measurements Gravity Gravity anomalies Gravity data Gravity inversion Inversion Mathematical models model and data fitting Physical properties prior information constraints Regularization Solid modeling Training U-Net
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