A Hybrid Deep Learning Approach for Integrating Transient Electromagnetic and Magnetic Data to Enhance Subsurface Anomaly Detection

A Hybrid Deep Learning Approach for Integrating Transient Electromagnetic and Magnetic Data to Enhance Subsurface Anomaly Detection

Recent advancements in geophysical exploration have highlighted the importance of integrating electromagnetic (EM) and magnetic data to enhance subsurface target detection. Conventional inversion techniques often struggle with the non-uniqueness of solutions and sensitivity to noise when relying on...

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Bibliographic Details
Main Authors: Zhijie Qu, Yuan Gao, Shiyan Li, Xiaojuan Zhang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
joint inversion
convolutional neural network (CNN)
subsurface target detection
magnetic field response
Online Access:https://www.mdpi.com/2076-3417/15/6/3125
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