Airborne Transient Electromagnetic Modeling and Inversion Under Full Attitude Change

Qi, Yunping; Huang, Ling; Wang, Xucun; Fang, Guangyou; Yu, Gang

doi:10.1109/lgrs.2017.2724558

Cited by 20 publications

(6 citation statements)

References 8 publications

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“…However, geometry effects are rarely considered in forward modeling and inversion. The authors of [9] use magnetic dipoles to simulate the geometry of the transmitter in an ATEM survey, yet their application is limited to the closed transmitter coil. The authors of [10] employ xand y-oriented electric dipoles to simulate the ground large loop TEM.…”

Section: Discussionmentioning

confidence: 99%

“…The authors of [8] developed a novel "agree-to-disagree" strategy to identify and correct misrecorded flight height in ATEM. In [9], the authors proposed to record the orientation of the ATEM bird and decompose the tilted loop as a linear combination of three orthogonal magnetic dipoles. The authors of [10] modeled the actual geometry of a large ground loop using a series of electrical dipoles.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Chen

Yang

2022

Remote Sensing

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Airborne and semi-airborne transient electromagnetic (TEM) surveys have high efficiency but may suffer from systematic errors due to the inexact shape, position, and orientation of the transmitter and receiver, which can deviate from the nominal design because of complex terrain, platform instability, or external forces. Without considering actual survey geometry, modeling and inversion can bias the interpretation of results. We develop a universal approach to layered earth capable of modeling arbitrarily complex transmitter and receiver geometry used in airborne and semi-airborne surveys. Our algorithm decomposes an airborne loop or grounded wire source to a set of x-, y-, or z-oriented electric dipoles. An arbitrarily oriented receiver coil is simulated by projecting three-component data to the actual direction of receiving. In airborne TEM, the transmitter loop and receiver coil are often bound together on a rigid frame and tilt during the flight. Our simulations and synthetic inversion show that such a tilt may reduce responses relative to the data obtained with the nominal geometry; an inversion without considering the tilt can underestimate near-surface conductivity. In semi-airborne TEM, the transmitter wire on the surface can be crooked, and the airborne receiver coil can also tilt. Our modeling shows that the simulated data can change significantly if the actual transmitter and receiver geometry does not exactly follow the nominal survey design; if not appropriately accounted for, such an error may distort the recovered conductivity model. Finally, the benefit of our algorithm is demonstrated by an airborne TEM field data inversion of groundwater problems with the tilt angle of the transmitter–receiver frame accurately modeled. Our work provides a tool for improving the resolution of airborne and semi-airborne TEM in near-surface conductivity characterization.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Chen

Yang

2022

Remote Sensing

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“…Zhdanov & Pavlov [18] implemented a similar configuration for interpreting the subsurface structure with both electrical conductivity and magnetic permeability inhomogeneities. Qi, et al [19] employed an airborne TEM system using a pair of transmitter-receiver coil antennas to investigate the subsurface structure taking into account the effects of the antennas' attitude changes. Blatter, et al [20] used an airborne TEM configuration to image a subglacial hydrology structure in Antarctica.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2021

J. Eng. Technol. Sci.

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The PSO inversion scheme was applied to the grounded wire TDEM method to infer subsurface resistivity models. The forward modeling part was expressed in the Laplace domain, while the transformation into the time-domain was conducted using the Gaver-Stehvest method. The inversion scheme was tested on noise-free and noisy synthetic data to evaluate the accuracy of the scheme and was then applied to field data recorded at two stations in a volcanic-geothermal region. The inversion scheme gave an excellent fit between the observed data and the calculated data.

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“…Ren (2017) investigated a three-dimensional time-domain airborne electromagnetic model based on the finite volume method, and then used the strategy of separating the primary field from the secondary field, which significantly saved on calculation time [10]. For airborne transient electromagnetic measurement, a three-dimensional forward simulation method which considered attitude change was proposed, and the electromagnetic response of a shallow surface was analyzed in Reference [11]. Later, the spectral element method (SE) was used to carry out three-dimensional modeling of GREATEM, effectively improving the modeling accuracy [12].…”

Section: Introductionmentioning

confidence: 99%

3D Numerical Modeling of Induced-Polarization Grounded Electrical-Source Airborne Transient Electromagnetic Response Based on the Fictitious Wave Field Methods

Meng

Huang

et al. 2020

Applied Sciences

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The grounded electrical-source airborne transient electromagnetic (GREATEM) system is widely used in mineral exploration. Meanwhile, the induced polarization (IP) effect, which indicates the polarizability of the earth, is often found. In this paper, the Maxwell equations in the frequency domain are transformed into fictitious wave domain, where Maxwell equations are solved by the time domain finite difference method. Then, an integral transformation method is used to convert the calculation results back to the time domain. A three-dimensional (3D) numerical simulation in a polarizable medium is presented. The accuracy of this method is proven by comparing it with the analytical solution and the existing method, and the calculation efficiency is increased five-fold. The simulation results show that the GREATEM system has a higher response amplitude in the conductive region, while IP effects cannot be identified in the conductive area. The GREATEM system has a higher response amplitude in the low-resistance region, but IP effects cannot be identified in the low-resistance area, and the detection of IP effects is more suitable for the high-resistance area. Therefore, it is necessary to improve the detection ability of the GREATEM system in the low-resistance area.

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Airborne Transient Electromagnetic Modeling and Inversion Under Full Attitude Change

Cited by 20 publications

References 8 publications

Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Untitled

3D Numerical Modeling of Induced-Polarization Grounded Electrical-Source Airborne Transient Electromagnetic Response Based on the Fictitious Wave Field Methods

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