Abstract
Transient electromagnetic (TEM) soundings are being increasingly used in engineering applications of environmental and regional surveys and shallow metal detection. Efficient and real time of the processing of the observed TEM data is the trend for the engineering geophysical prospecting and detection instrument in modern times. This letter presents a fast resistivity imaging method of TEM using artificial neural networks. The input–output mapping relations of neural networks are established based on the TEM response characteristics under different transmitter loop devices. The built network could map the recorded TEM data and quickly obtain the resistivity image. The proposed method offers accuracy and fast computation for resistivity imaging, and only 9.003 s costs for the calculation of 142 measured points’ data. Feasibility and technical attractiveness of the proposed method in fast resistivity imaging of TEM mean that it is well suited for instantaneous of survey results to a client. The proposed TEM imaging method can be used in real time so that the recorded TEM data can be calculated without retraining, which avoids time-consuming iteration and inversion computation.
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