Forward modeling of radio-magnetotelluric method based on Julia acceleration and study on effect of displacement current

Radio-magnetotelluric method (RMT) is one of the important tools for shallow surface electromagnetic exploration. Since the exploration frequency band is 10‒300 kHz, the propagation of electromagnetic fields is greatly affected by the dielectric permittivity of the earth. The electromagnetic response calculated with traditional quasi-static conditions severely restricts the accuracy of RMT forward modeling and further affects the resolution of the inversion imaging. In response to this problem, a numerical simulation method of full-current RMT electromagnetic response based on Julia parallel acceleration was proposed. Then, the calculation of each frequency point was sent through the distributed computing in Julia to different processes for solving, so as to achieve the purpose of accelerating the calculation. At the same time, the influence of displacement current was considered in the calculation to improve the accuracy of forward modeling. Besides, the influence law of displacement current on the apparent resistivity and phase response of electromagnetic field in the radio frequency band was analyzed and summarized by calculating the RMT response of several typical high-resistance/high-dielectric models. The numerical simulation results show that: The calculated RMT apparent resistivity and phase response under the quasi-static conditions were relatively high in case that a high-resistance overburden is present in the shallow surface. Besides, the higher the frequency, the greater the resistivity of the overburden, and the larger the response deviation is. For the coal goaf model, the RMT method can effectively reflect the location of the abnormal body, but ignoring the displacement currents may cause a large calculation error in the goaf and its vicinity. As shown in the calculation example of rugged terrains, the RMT numerical response of underground anomalous body may be covered by the terrain, especially at the corner of terrain. Further, the parallel numerical examples at two different scales comparatively demonstrate the efficiency of the parallel algorithm herein, and the efficiency of the parallel algorithm is improved with the increasing scale of the problem to be solved. Our research improved the computational efficiency and accuracy of RMT forward modeling, laying the foundation for the realization of subsequent rapid inversion algorithm. In addition, the numerical calculation examples also indicate that the RMT method has a good application prospect in the actual exploration of coal goaf.