Land-based TEM Data Processing: from Turn-off Ramp to Full Waveform

Li, Jianhui; Wang, Xingchun; Hu, Xiangyun; Wang, Yuan; Wang, Peng

doi:10.1002/essoar.10510985.1

Cited by 2 publications

(1 citation statement)

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“…The center point is considered the observation point of the station and is used to receive electromagnetic induction signals. The z-axis is positive and negative below the ground [45]. Pass a current of amplitude I through the coil and immediately turn it off.…”

Section: Tem Forward and Inversionmentioning

confidence: 99%

TEM Strata Inversion Imaging with IP Effect Based on Enhanced GCN by Extracting Long-Dependency Features

Li,

Di,

Tian

et al. 2023

Electronics

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Utilizing neural network models to inverse time-domain electromagnetic signals enables rapid acquisition of electrical structures, a non-intrusive method widely applied in geological and environmental surveys. However, traditional multi-layer perceptron (MLP) feature extraction is limited, struggling with cases involving complex electrical media with induced polarization effects, thereby limiting the inversion model’s predictive capacity. A graph-topology-based neural network model for strata electrical structure imaging with long-dependency feature extraction was proposed. We employ graph convolutional networks (GCN) for capturing non-Euclidean features like resistivity-thickness coupling and Long Short-Term Memory (LSTM) to capture long-dependency features. The LSTM compensates for GCN’s constraints in capturing distant node relationships. Using case studies with 5-strata and 9-strata resistivity models containing induced polarization effects, compared to traditional MLP networks, the proposed model utilizing time-domain features and graph-topology-based electrical structure extraction significantly improves performance. The mean absolute error in inversion misfit is reduced from 10–20% to around 2–3%.

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Section: Tem Forward and Inversionmentioning

confidence: 99%

TEM Strata Inversion Imaging with IP Effect Based on Enhanced GCN by Extracting Long-Dependency Features

Li,

Di,

Tian

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

One-dimensional full-waveform inversion for magnetic induction data in ground-based transient electromagnetic methods

Wang

et al. 2023

Journal of Geophysics and Engineering

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The full waveform effects refer to the total effects of turn-on, steady, and turn-off durations for a transmitting-current waveform as well as its repetition number in transient electromagnetic (TEM) methods. In this study, the full waveform effects are investigated using both forward-modelling and inversion methods considering typical background noise. The forward-modelling results of homogeneous half-space models show that the magnetic induction, bz, is less affected by the background noise but more affected by the full waveform effects than the time derivative of magnetic induction ∂bz/∂t. Therefore, this study focuses on investigating the full waveform effects on bz. The inversion results for synthetic and field examples show that the inversion algorithm without considering the full waveform effects leads to over-estimated resistivities in deeper parts of the recovered models compared to the true model. Therefore, it is crucial to consider the full waveform effects when processing TEM data. Furthermore, a standard deviation factor (STDF) is estimated for model parameters of the inversion. The results show that the STDF increases as the layer depth increases for 1D layered models. This indicates that the inverted parameters are well resolved for shallower layers and moderately to poorly resolved for deeper layers.

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Land-based TEM Data Processing: from Turn-off Ramp to Full Waveform

Cited by 2 publications

References 0 publications

TEM Strata Inversion Imaging with IP Effect Based on Enhanced GCN by Extracting Long-Dependency Features

TEM Strata Inversion Imaging with IP Effect Based on Enhanced GCN by Extracting Long-Dependency Features

One-dimensional full-waveform inversion for magnetic induction data in ground-based transient electromagnetic methods

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