Two-dimensional fast imaging of airborne EM data based on U-net - Liu, Qiang; Yin, Changchun; Su, Yang; Liu, Yunhe; Wang, Luyuan; Liang, Hao; Wang, Han (Frontiers in Earth Science, 2023)
As an efficient geophysical exploration tool, the airborne electromagnetic (AEM) method has been widely used in mineral exploration, geological mapping, environmental and engineering investigation, etc. Currently, the imaging and 1D inversions are the mainstream means for AEM interpretation as the amount of AEM data is huge and 2D and 3D inversions are not efficient. In this paper, we propose a 2D fast imaging method for frequency-domain AEM data based on U-net network. The U-net is a symmetric full-convolution neural network, in which the partial pooling operation between convolution layers is replaced by the up-sampling operation, while the target location is achieved by skipping connection. This method does not need to consider the complex coupling between the EM wave and underground structures, but instead it establishes a mapping relationship between EM signal and resistivity model and can quickly achieve accurate imaging of AEM data. We use this network to image both synthetic and field survey data and compare the results with the traditional inversion algorithm. The results show that the U-net imaging have high resolution at high speed that provides a new way for interpreting large amounts of AEM data.