Airborne electromagnetic data levelling based on the structured variational method

IF 1.8 4区地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY

Geoscientific Instrumentation Methods and Data Systems Pub Date : 2024-06-26 DOI:10.5194/gi-13-193-2024

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

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Abstract

Abstract. Levelling errors are defined as the data difference among flight lines in airborne geophysical data. The differences in the signal levelling always appear as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided levelling error model using an anisotropic Gabor filter. We then embed the levelling error model into a total variational framework to flexibly calculate levelling errors. The guided levelling error model constrains the noise term of total variation rather than just using blind removal. Moreover, we can also apply the structured variational method to remove other noises in airborne geophysical data. This would just require replacing the noise prior models in the proposed method. We have applied this method to the airborne electromagnetic, magnetic, and apparent conductivity data collected by the Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level the airborne geophysical data based on the space properties of the levelling error.

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基于结构变分法的机载电磁数据平差

摘要平差误差是指机载地球物理数据中飞行线路之间的数据差异。在成像图上，信号平差总是以平行于飞行线的条纹图案出现。这种固定的结构模式启发我们使用各向异性的 Gabor 滤波器来构建一个引导平差误差模型。然后，我们将配平误差模型嵌入总变分法框架，以灵活计算配平误差。引导式平差误差模型约束了总变分的噪声项，而不仅仅是盲目去除噪声。此外，我们还可以应用结构变分法去除机载地球物理数据中的其他噪声。这只需要替换拟议方法中的噪声先验模型即可。我们将该方法应用于安大略省地质调查局收集的机载电磁、磁场和视导率数据，通过将结果与已公布的数据进行比较，证实了该方法的有效性和稳健性。根据平差误差的空间特性，结构变分法可以更好地平整机载地球物理数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geoscientific Instrumentation Methods and Data Systems GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES

CiteScore

3.70

自引率

0.00%

发文量

审稿时长

37 weeks

期刊介绍： Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following: concepts, design, and description of instrumentation and data systems; retrieval techniques of scientific products from measurements; calibration and data quality assessment; uncertainty in measurements; newly developed and planned research platforms and community instrumentation capabilities; major national and international field campaigns and observational research programs; new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters; networking of instruments for enhancing high temporal and spatial resolution of observations. GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following: foster scientific discussion; maximize the effectiveness and transparency of scientific quality assurance; enable rapid publication; make scientific publications freely accessible.

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