TR32-Database: Database of Transregio 32

[1451] - Calibration and multi-layer inversion of multiple electromagnetic induction sensor data

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Citation
von Hebel, C., van der Kruk, J., Mester, A., Altdorff, D., Zimmermann, E., Endres, A. ., Vereecken, H., 2016. Calibration and multi-layer inversion of multiple electromagnetic induction sensor data. EGU General Assembly 2016, April 17 - 22, 2016, Vienna. Accessed from http://www.tr32db.uni-koeln.de/data.php?dataID=1451 at 2017-11-18.
Identification
Title(s):Main Title: Calibration and multi-layer inversion of multiple electromagnetic induction sensor data
Description(s):Abstract: Multi-coil electromagnetic induction (EMI) sensors record simultaneously the apparent electrical conductivity (ECa) distribution of different integrated depths that can principally be used to invert for hydrologically relevant subsurface structures. However, EMI sensors induce not only magnetic fields in the subsurface but external conditions, e.g. the field setup, generate additional fields that shift the recorded ECa values. To obtain quantitative multi-coil EMI-ECa that make a multi-layer inversion possible, a post-calibration is required. Calibration for each coil configuration is performed using linear regressions between measured and predicted ECa that were obtained by inserting the electrical conductivities of inverted electrical resistivity tomography (ERT) data into a Maxwellbased EMI forward model. We measured 43 of these calibration lines using different field setups at various test sites and dates. Analyzing the data, we found a well-working calibration and a successful subsequent multi-layer inversion when relatively large lateral and vertical ECa values were found along the calibration line. However, we observed failure when either the measured or the predicted ECa range is < 3 mS/m and/or when the ground electrical conductivity is < 5 mS/m. Using selected calibration lines with coefficients of determination R2 > 0.75 in the linear regression equations, universal calibration parameters were obtained. Since the inversion of universally calibrated EMI-ECa returned similar subsurface structures as the ERT images, the results indicate that future ERT calibration measurements might become unnecessary. We also extended our three-layer inversion using one EMI sensor with 6 coil configurations to a combined multi-layer inversion of multiple sensors. Here, we preliminary show 4 and 5 layer inversion results of post-calibrated EMI-ECa measured above paleo-river channels with 24 coil configurations, i.e. DualEM plus a three- and a six coil CMD-MiniExplorer. Conclusively, the post-calibrated EMI-ECa data enable quantitative inversions reflecting large-scale vadose zone properties.
Responsible Party
Creator(s):Author: Christian von Hebel
Author: Jan van der Kruk
Author: Achim Mester
Author: Daniel Altdorff
Author: Egon Zimmermann
Author: Anthony Endres
Author: Harry Vereecken
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Soil
Related Sub-project(s):B6
Subject(s):CRC/TR32 Keywords: Soil
File Details
File Name:CvH_EMI_EGU2016.pptx
Data Type:Event
File Size:2500 kB (2.441 MB)
Date(s):Issued: 2016-04-21
Mime Type:application/vnd.openxmlformats-officedocument.presentationml.presentation
Data Format:MS PowerPoint
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Presentation
Presenter:von Hebel
Presentation Date:2016-04-21
Presentation Type:Poster
Event Name:EGU General Assembly 2016
Event Type:Conference
Event Location:Vienna
Event Period:17th of April, 2016 - 22nd of April, 2016
Metadata Details
Metadata Creator:Christian von Hebel
Metadata Created:2016-10-12
Metadata Last Updated:2016-10-12
Subproject:B6
Funding Phase:3
Metadata Language:English
Metadata Version:V41
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Metadata Downloads:0
Dataset Downloads:1
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