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Simulation results of model 2. (a) Cagniard apparent resistivity and (b) divergence of tipper real induction vector. Black dotted lines indicate the locations of the two low resistance targets.
Context in source publication
Context 1
... divergence of tipper real induction vector can directly indicate the property of an abnormal body through the plus-minus sign and show its location by the abnormal shape and range. Figure 4 shows the results of model 2 when two same size low resistance targets are buried at a relatively shallow depth. Besides the shadow and rotation angle, there are also some false anomalies in the Cagniard apparent resistivity image, which is unfavorable for anomaly identification interpretation. ...
Citations
... By studying the interaction between adjacent sources, they focused on solving the problem of field installation of multi-source transmitter system, and verified the feasibility of the multi-source SAFEM method through experiments. On this basis, Zhou et al. [57] proposed a tensor-tipper real induction vector divergence detection method to improve the detection accuracy of the SAFEM system for three-dimensional objects based on a pair of orthogonal electrical sources, and the advantages and feasibility of this method have been proved by field experiments. ...
Semi-airborne Electromagnetic Method (SAEM) is a geophysical electromagnetic detection method which places the transmitting subsystem on the ground and the receiver subsystem on the flight platform. This transceiver configuration has been found to be more efficient than that of the traditional ground electromagnetic methods, while it can get much deeper penetration than the traditional airborne electromagnetic methods. Therefore, SAEM has been widely used in mineral, groundwater, geothermal and other resources exploration fields. In this paper, we would like to take the most key problems encountered in the SAEM system design and application as the starting point, and then we focus mainly on reviewing the progress of the transmitter, sensor and receiver technology, as well as data processing, modeling and imaging methods of the SAEM in China. In particular, the research progress of multi-source SAEMs will be introduced. Beyond that, two prospecting examples with different SAEM systems will be introduced. Finally, we will discuss the future of SAEM in terms of equipment developing, data processing, modeling and inversion, to promote the research and application in this field to a higher level.
