Reconstruction of Induced Polarization Information from Electromagnetic Data Using Neural Network Approach
Electromagnetic responses arising from the interaction of electromagnetic fields with the electrical properties of the subsurface structures provide useful information about such structures. Furthermore, if polarizable materials are present within the investigated structure, the observed data from t...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Korean Institute of Electromagnetic Engineering and Science
2025-07-01
|
| Series: | Journal of Electromagnetic Engineering and Science |
| Subjects: | |
| Online Access: | https://www.jees.kr/upload/pdf/jees-2025-4-r-301.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Electromagnetic responses arising from the interaction of electromagnetic fields with the electrical properties of the subsurface structures provide useful information about such structures. Furthermore, if polarizable materials are present within the investigated structure, the observed data from the electromagnetic measurements will contain inherently induced polarization responses, thereby introducing additional parameters for distinguishing subsurface materials. In this regard, the concept of introducing an inversion framework to extract information about induced polarization characteristics from electromagnetic measurements has recently attracted considerable attention. In this paper, an inversion setting is presented to estimate the induced polarization parameters of a stratified, polarizable, and layered medium from scattered electromagnetic fields. The proposed setting handles the inverse problem through a learning procedure that employs a neural network design. Several neural network design factors were tuned to achieve optimal performance. The proposed neural network with tuned design factors was also evaluated under noisy conditions. Error analysis verified the effectiveness of the proposed neural network design in inverting electromagnetic data to derive induced polarization parameters. |
|---|---|
| ISSN: | 2671-7255 2671-7263 |