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近场源浅地表多频电磁法正反演研究

Research on Forward Modeling and Inversion of Multi-Frequency Electromagnetic Method with Near-Field Source in Shallow Surface
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摘要 工程地质及环境问题日渐突出,浅地表电磁探测也日渐发展起来。相较于传统直流电法,近场源频率域电磁探测方法及其装置均有更显著的优势。论文首先介绍了近场源多频电磁法正演公式及数值解法,并对反演方法进行了阐述;然后对文献中的经典模型进行正演,分析了正演结果的精度;最后基于不同的地电模型、不同噪声水平的电磁数据进行已知与未知模型反演,并对比了反演结果。对比反演结果可知,近场源多频电磁法对三层模型中的H型地电模型在较强噪声水平下仍与理论模型吻合较好,且按不固定的未知模型来反演也能较好拟合。研究结果表明,本文正演过程精度高,反方法也表现出了很强的抗干扰能力,为近场源频率域电磁探测方法推广提供理论依据。 Engineering geology and environmental problems are becoming more and more prominent, and shallow surface EM detection is also developing. Compared with the traditional direct current method, the method and device of near-field source and frequency domain EM detection have more significant advantages. In this paper, the formula and numerical solution of near-field source and multi-frequency EM method are introduced, and the inversion method is described. Then, the classical models in the literature are performed and the accuracy of the forward results is analyzed. Finally, based on the different electromagnetic models and different noise levels, the known and unknown models are retrieved, and the results are compared. The comparison inversion results show that multi-frequency electromagnetic method of the near-field source is consistent with the theoretical model for the H-type geoelectric model under the strong noise level, and it can also be well fitted by the unfixed unknown model inversion. The research shows that forward modeling has a high precision and the inversion calculation has a high anti-interference ability in this paper, which provides a theoretical basis for the promotion of near-field source and frequency domain EM method.
作者 郑冕 肖建平 Mian Zheng;Jianping Xiao(School of Geosciences and Info-Physics, Central South University, Changsha Hunan)
机构地区 中南大学
出处 《地球科学前沿(汉斯)》 2018年第2期367-377,共11页 Advances in Geosciences
基金 国家科技基础性工作专项项目(2013FY110800)。
关键词 近场源电磁法 频率域电磁正演 阻尼最小二乘反演 浅地表探测 Near-Field Source EM Method Frequency Domain EM Forward Modeling Inversion of DampingLeast Square Method Shallow Surface Detection
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