Research on 1-D forward modeling and inversion of TEM Considering induced polarization effects

The transient electromagnetic (TEM) method, as an efficient geophysical exploration technique, plays a crucial role in mineral resource exploration, environmental engineering, and geological hazard assessment. TEM forward modeling and inversion sometimes neglect the subsurface medium's induced polarization (IP) effects. This may result in inaccurate interpretation of the subsurface electrical structure. To address this issue, this study conducts TEM forward modeling and inversion incorporating IP effects, aiming to improve TEM data's inversion accuracy and interpretability under geological conditions involving polarizable bodies. First, based on the Cole-Cole complex resistivity model, 1-D TEM forward modeling considering IP effects is implemented, and the accuracy and reliability of the algorithm are validated. Subsequently, nonlinear optimization algorithms are applied to process TEM data during the inversion, with a focus on comparing and analyzing the inversion performance of the particle swarm optimization (PSO) algorithm and the velocity pausing particle swarm optimization (VPPSO) algorithm in some layered medium models. The results demonstrate that although the computational efficiency of the VPPSO algorithm is slightly lower than that of the PSO algorithm, it exhibits significant advantages in convergence speed, global search capability, and noise resistance. Finally, inversion experiments using field data further validate the effectiveness and practicality of the VPPSO algorithm. The research works in this article provide new methods for TEM exploration of subsurface polarizable bodies.