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https://doi.org/10.5194/egusphere-2024-306
https://doi.org/10.5194/egusphere-2024-306
26 Mar 2024
 | 26 Mar 2024

Airborne electromagnetic data leveling based on structured variational method

Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, and Yunqing Liu

Abstract. The leveling errors are defined as the data difference among flight lines in airborne geophysical data. The differences of the signal leveling always show as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided leveling error model by an anisotropic Gabor filter. Then we embed the leveling error model in total variational framework to flexibly calculate leveling errors. The guided leveling error model constrain the noise term of total variation rather than just blind removal. Moreover, the structured variational method can be extended to remove other type of noises which have general noise priors. We have applied the method to the airborne electromagnetic, magnetic data, and apparent conductivity data collected by Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level airborne geophysical data based on the space properties of leveling error.

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Journal article(s) based on this preprint

26 Jun 2024
Airborne electromagnetic data levelling based on the structured variational method
Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, and Yunqing Liu
Geosci. Instrum. Method. Data Syst., 13, 193–203, https://doi.org/10.5194/gi-13-193-2024,https://doi.org/10.5194/gi-13-193-2024, 2024
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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In airborne survey, the dynamic flight conditions cause the unequal data levels which have...
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