Neural Network for Mapping Full Time Apparent Resistivity Solution from TEM Electromotive Force Data

The apparent resistivity of the induced electromotive force observed by the transient electromagnetic (TEM) in center loop is proposed by using the neural network. According to the characteristics of increasing of the induced electromotive force with the resistivity of the transient electromagnetic sounding, the neural network input and output relationship and the network structure of the transient electromagnetic induction electromotive force response are designed according to the uniform half space central line observation mode. The nonlinear model of transient electromagnetic induction electromotive force and apparent resistivity is fitted by the neural network to obtain the full apparent resistivity value of the measured induced electromotive force data at a certain sampling time, and the aim of resistivity and imaging is achieved quickly. Through the calculation and verification of the simulation model of the transient electromagnetic in grounding grids, the apparent resistivity section can be obtained, and the position of the breakpoint can be clearly determined, and the effect of solving the inverse problem is achieved. The calculation of the verification model shows that the method makes the calculation time of the transient electromagnetic apparent resistivity greatly shorten, which is a practical algorithm.