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@PHDTHESIS{Mozaffari:907641,
      author       = {Mozaffari, Amirpasha},
      title        = {{T}owards 3{D} crosshole {GPR} full-waveform inversion},
      volume       = {574},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      reportid     = {FZJ-2022-02120},
      isbn         = {978-3-95806-623-6},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {viii, 122},
      year         = {2022},
      note         = {Dissertation, RWTH Aachen University, 2022},
      abstract     = {High-resolution imaging of the subsurface improves our
                      understanding of thesubsurface flow and solute
                      transportation that can directly help us protectgroundwater
                      resources and remediate contaminated sites. The ground
                      penetratingradar (GPR) is a useful non/minimal invasive
                      method that consists of a transmitter(Tx) unit that emits
                      electromagnetic (EM) waves and a receiver (Rx) that
                      measuresthe arriving electromagnetic waves and can provide
                      high-resolution tomograms of thesubsurface properties.In
                      specific, the crosshole GPR setup in which two-neighbouring
                      boreholes are placedin the earth can provide much more
                      in-depth access to the target area. However,
                      theinterpretation of the GPR data remains challenging. The
                      simpler ray-based inversion(RBI) is computationally
                      attractive while fail to provide high-resolution tomogramsas
                      the results always smoothed over the target area. The
                      full-waveform inversion(FWI) can provide detailed subsurface
                      tomograms that can carry up to more thanan order of the
                      magnitude resolution compared to RBI from the same data set.
                      Asophisticated method such as FWI requires detailed
                      modelling tools and powerfulinversion algorithm that needs
                      significant computational resources. In last decades,
                      byexponential increase in computing power and the memory,
                      alongside to wider usage ofhigh performance computing
                      resources; FWI application in GPR data gain popularity.All
                      these computational advances such as FWI method. could be
                      very demandingto be modelled in 3D domain. Thus, some
                      fundamentals assumptions are made toreduce the computational
                      requirements, especially computational time and
                      requiredmemory by using 2D modeling domain. Despite the
                      usefulness of these simplifications,these assumptions led to
                      introducing inaccuracy that compromises the performanceof
                      the FWI in complex structures. We investigated the effect of
                      the assumption thatenables us to use a 2D model instead of a
                      computationally expensive 3D modelling tosimulate the EM
                      propagation. These assumptions are made for specific state
                      that notnecessary is always valid, and therefore it can
                      introduce inaccuracies in transferreddata. Study of several
                      synthetic cases revealed that the performance of the 3D to
                      2Dtransformation in complex structures such as high contrast
                      layer is much lower thanwhat is anticipated. Therefore, in
                      the complex subsurface system; 2D transferreddata inherently
                      carry inaccuracy that jeopardises the accuracy of any
                      further analysissuch as FWI. Thus, we introduced a FWI that
                      utilise a native 3D forward model touse the original
                      measured 3D data. The novel method is called 2.5D FWI, and
                      itshowed improvements compared to 2D FWI for synthetic and
                      measured data},
      cin          = {IBG-3},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:0001-2022052307},
      url          = {https://juser.fz-juelich.de/record/907641},
}