Artificial neural network inversion of magnetic anomalies caused by 2D fault structures

被引:0
作者
Mansour A. Al-Garni
机构
[1] King Abdulaziz University,Department of Geophysics, Faculty of Earth Sciences
来源
Arabian Journal of Geosciences | 2016年 / 9卷
关键词
Neural network; Magnetic; 2D fault structures; Inversion;
D O I
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学科分类号
摘要
A new approach is proposed to interpret magnetic anomalies caused by 2D fault structures. This approach is based on the artificial neural network inversion, utilizing particularly modular neural network algorithm. The inversion process is implemented to estimate the parameters of 2D fault structures where it has been verified first on synthetic models. The results of the inversion show that the parameters derived from the inversion agree well with the true ones. The analysis of noise has been studied in order to investigate the stability of the approach where it has been tested for contaminated anomalies with 5 and 10 % of white Gaussian noise. The results of the inversion provide satisfactory results even with contaminated signals.
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