4.5 Article

Quantitative Two-Layer Conductivity Inversion of Multi-Configuration Electromagnetic Induction Measurements

期刊

VADOSE ZONE JOURNAL
卷 10, 期 4, 页码 1319-1330

出版社

SOIL SCI SOC AMER
DOI: 10.2136/vzj2011.0035

关键词

-

资金

  1. 'Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation' [SFB/TR 32]
  2. 'TERrestrial ENvironmental Observatories' (TERENO)
  3. Deutsche Forschungsgemeinschaft (DFG)

向作者/读者索取更多资源

Electromagnetic induction (EMI) measurements return an apparent electrical conductivity that represents a weighted average of the electrical conductivity distribution over a certain depth range. Different sensing depths are obtained for different orientations, different coil off sets, and different frequencies, which, in principle, can be used for a multi-layer inversion. However, instrumental shifts, which often occur in EMI data, prevent the use of quantitative multi-layer inversion. Recently, a new calibration method was developed that uses electrical resistivity tomography (ERT) inversion results and returns quantitative apparent conductivity values. Here, we introduce an inversion scheme that uses calibrated EMI data and inverts for a two-layer earth. The inversion minimizes the misfit between the measured and modeled magnetic field by a combined global and local search and does not use any smoothing parameter. Application of this new scheme to synthetic data demonstrates its efficacy in providing the required physical property information. Inversion of calibrated experimental EMI data using horizontal coplanar (HCP) and vertical coplanar (VCP) loop configurations, coil off sets of 1 and 1.22 m, and frequencies of 8 and 15 kHz provides lateral and vertical conductivity variations very similar to those observed in an elaborate ERT experiment. The inversion is verified using synthetic EMI data calculated from ERT data. Inverting quantitative EMI data using this two-layer inversion enables the quantitative mapping of lateral and vertical electrical conductivity variations over large areas.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据