In physical exploration including magnetic prospecting, it is a basic requirement to explore in a regular network of standards. However, due to the various obstacles encountered in the survey, measurement is generally not performed in a regular network. Therefore, it is very important to study inversion algorithms with high noise reduction ability and increase the accuracy of sampling of the measured data at irregular intervals.
Ri Hyon Sok, a researcher at the Faculty of Earth Science and Technology, proposed a method of using the Fourier transform-based robust estimation method for processing magnetic prospecting data measured at disproportionate intervals, based on its high sampling accuracy and high noise enhancement capability, and demonstrated the advantage of the proposed method though model experiments and application.
The results of model calculations and field applications show that the magnetic prospecting analysis by the Fourier transform-based robust estimation method is superior to the existing magnetic susceptibility tracking imaging.
For more information, please refer to his paper “Study on the Application of Fourier Transform-Based Robust Optimization for Magnetic Inversion” in “Proceedings of KUTIC-2025”.