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A Self-Adaptive Algorithm of Inverse Wavefield Transform for the Vertically Magnetic Components of the Loop-Source Transient Electromagnetic Data
We present a self-adaptive algorithm of inverse wavefield transform for the vertically magnetic components of the loop-source transient electromagnetic method (TEM) data to highlight the subsurface interfaces of electric resistivity. Based on the theory of wavefield transform between the electromagn...
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Published in: | IEEE geoscience and remote sensing letters 2025-01, Vol.22, p.1-5 |
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Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | We present a self-adaptive algorithm of inverse wavefield transform for the vertically magnetic components of the loop-source transient electromagnetic method (TEM) data to highlight the subsurface interfaces of electric resistivity. Based on the theory of wavefield transform between the electromagnetic (EM) diffusion and the EM wave, the transform formula of the TEM field and its time derivative are presented. The velocity of the pseudo-wavefield is given. To numerically accomplish the inverse wavefield transform in a finite interval, the shortest time window for the pseudo-wavefield is determined by a newly proposed formula. Then the pseudo-time window can be directly figured out according to the time wind of TEM measuring time. To solve the inverse wavefield transform equation accurately, the precise integral method (PIM) is introduced with an automatic iteration control scheme. In the numerical results, the pseudo-wavefield traces transformed from the modeled TEM responses are physically rational as the pseudo-wavefield reflection arrives as expected. The data misfit between the fit and the modeled data is smaller than 10% and is smaller than 1% for the TEM responses earlier than 1 ms. The results illustrate that the transformed pseudo-wavefield can highlight the location and features of the electric interfaces through the reflection arrival and waveform. |
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ISSN: | 1545-598X 1558-0571 |
DOI: | 10.1109/LGRS.2024.3372525 |