001     866395
005     20220930130222.0
024 7 _ |a 10.1190/geo2018-0597.1
|2 doi
024 7 _ |a 0016-8033
|2 ISSN
024 7 _ |a 1942-2156
|2 ISSN
024 7 _ |a WOS:000501594400020
|2 WOS
037 _ _ |a FZJ-2019-05549
082 _ _ |a 550
100 1 _ |a Klotzsche, Anja
|0 P:(DE-Juel1)129483
|b 0
|e Corresponding author
245 _ _ |a Review of crosshole ground-penetrating radar full-waveform inversion of experimental data: Recent developments, challenges, and pitfalls
260 _ _ |a Alexandria, Va.
|c 2019
|b GeoScienceWorld
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1582126413_3360
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Heterogeneous small-scale high-contrast layers and spatial variabilities of soil properties can have a large impact on flow and transport processes in the critical zone. Because their characterization is difficult and critical, high-resolution methods are required. Standard ray-based approaches for imaging the subsurface consider only a small amount of the measured data and suffer from limited resolution. In contrast, full-waveform inversion (FWI) considers the full information content of the measured data and could yield higher resolution images in the subwavelength scale. In the past few decades, ground-penetrating radar (GPR) FWI and its application to experimental data have matured, which makes GPR FWI an established approach to significantly improve resolution. Several theoretical developments were achieved to improve the application to experimental data from crosshole GPR FWI. We have determined the necessary steps to perform FWI for experimental data to obtain reliable and reproducible high-resolution images. We concentrate on experimental crosshole GPR data from a test site in Switzerland to illustrate the challenges of applying FWI to experimental data and discuss the obtained results for different development steps including possible pitfalls. Thereby, we acknowledge out the importance of a correct time-zero correction of the data, the estimation of the effective source wavelet, and the effect of the choice of starting models. The reliability of the FWI results is investigated by analyzing the fit of the measured and modeled traces, the remaining gradients of the final models, and validating with independently measured logging data. Thereby, we found that special care needs to be taken to define the optimal inversion parameters to avoid overshooting of the inversion or truncation errors.
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|f POF III
|x 0
536 _ _ |a Better predictions with environmental simulation models: optimally integrating new data sources (jicg41_20100501)
|0 G:(DE-Juel1)jicg41_20100501
|c jicg41_20100501
|f Better predictions with environmental simulation models: optimally integrating new data sources
|x 1
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Vereecken, Harry
|0 P:(DE-Juel1)129549
|b 1
|u fzj
700 1 _ |a van der Kruk, Jan
|0 P:(DE-Juel1)129561
|b 2
|u fzj
773 _ _ |a 10.1190/geo2018-0597.1
|g Vol. 84, no. 6, p. H13 - H28
|0 PERI:(DE-600)2033021-2
|n 6
|p H13 - H28
|t Geophysics
|v 84
|y 2019
|x 1942-2156
856 4 _ |u https://juser.fz-juelich.de/record/866395/files/ORD6601.pdf
856 4 _ |u https://juser.fz-juelich.de/record/866395/files/ORD6601.pdf?subformat=pdfa
|x pdfa
909 C O |o oai:juser.fz-juelich.de:866395
|p OpenAPC
|p VDB
|p VDB:Earth_Environment
|p openCost
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)129483
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)129549
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)129561
913 1 _ |a DE-HGF
|l Terrestrische Umwelt
|1 G:(DE-HGF)POF3-250
|0 G:(DE-HGF)POF3-255
|2 G:(DE-HGF)POF3-200
|v Terrestrial Systems: From Observation to Prediction
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Erde und Umwelt
914 1 _ |y 2019
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b GEOPHYSICS : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
920 1 _ |0 I:(DE-82)080012_20140620
|k JARA-HPC
|l JARA - HPC
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 _ _ |a I:(DE-82)080012_20140620
980 _ _ |a APC
980 _ _ |a UNRESTRICTED
980 1 _ |a APC


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21