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Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function

delete2024-07-01
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PRE
AI
Z
Zhongkun Qiao *
Z
Zongyu Zhang
R
R.J. Hu
Z
Zheng-Hao Shen
P
Peng Yuan
H
Hang Zhou
X
Xinyi Huang
Z
Zhou Fei
H
Huiyan Shi
X
Xuemin Wu *
B
Bin Wu
X
Xiao-Long Wang *
Q
Qiang Lin
DOI:10.1109/JSEN.2024.3398301delete
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摘要

摘要

En 中文
Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data reflect the different distribution characteristics of subsurface anomalous objects, and therefore, the single data inversion cannot achieve an accurate identification for the underground objects and suffer from stronger nonuniqueness problems. To accurately identify the location and distribution characteristics of subsurface objects, we first construct models to perform separate inversions of gravity and gravity gradient data, analyze the identification ability of different anomaly components, and then innovatively introduce a cross-gradient function for the joint inversion of two gravity tensor data, V-xx and V-yy. The results show that the method combines the advantages of these two components and reflects the horizontal position of the targeted bodies more accurately; meanwhile, the portrayal of the boundary is also closer to the real model. Finally, we apply the above method to the Vinton Dome, and the inversion results recover the accurate spatial location of the Vinton Dome. The practical application results show that the joint cross-gradient inversion of gravity and gravity gradient data is more efficient for spatial location trapping and boundary inscription of subsurface targeted bodies compared with the inversion of individual component.
Keyword:
Cross-gradient function
gravity and gradient data
joint inversion
Vinton Dome

期刊

IEEE Sensors Journal 封面图
IEEE Sensors Journal
IF:
4.5
论文数:
2.2W
被引数:
7.3W

机构

Z
zhejiang university of technology
学者数:
3.3W
论文数: 2.0W
被引数: 22
A
Auckland University of Technology
学者数:
4.0K
论文数: 4.4K
被引数: 4.7K
Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
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