Jo Feb 25, 2024

In magneto-telluric (MT) method, data processing for transfer functions (TF) estimation is routinely carried out based on the regression model of 4-element impedance under the assumption of plane electromagnetic wave. However, observed EM field contains not only MT signals subjected to the assumption of plane wave but also remarkable amounts of various noises with non-planar nature.

Jo Kyong Rae, a researcher at the Faculty of Earth Science and Technology, has introduced a regression model of impedance and admittance with 6 elements. He has also derived a mathematical formula for their estimation.

To decrease the influence of industrial noise as well as long-period noise, he employed 6-element regression models of impedance and admittance tensors in MT data processing to improve the predicted coherences of TFs estimation by about 0.02, both in single station and remote reference modes. He tested the proposed method through the processing of MT data, from four stations in the northern part of our country.

The results showed that the 6-element model makes it possible to improve the predicted coherences in TFs estimation and to decrease the scattering of the curves of apparent resistivity and phases, and that the difference between common 4-element and 6-element models gradually gets bigger as frequency decreases. It was also demonstrated that when the vertical magnetic component has amplitude as great as or greater than horizontal ones in auto-power curves, there is no doubt that the 6-element regression model is more appropriate for MT data processing than commonly used 4-element regression models.