000907641 001__ 907641
000907641 005__ 20220930130341.0
000907641 0247_ $$2Handle$$a2128/31151
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000907641 020__ $$a978-3-95806-623-6
000907641 037__ $$aFZJ-2022-02120
000907641 1001_ $$0P:(DE-Juel1)166264$$aMozaffari, Amirpasha$$b0$$eCorresponding author$$ufzj
000907641 245__ $$aTowards 3D crosshole GPR full-waveform inversion$$f- 2021-12-10
000907641 260__ $$c2022
000907641 300__ $$aviii, 122
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000907641 4900_ $$aSchriften des Forschungszentrums Jülich Reihe Energie & Umwelt / Energy & Environment$$v574
000907641 502__ $$aDissertation, RWTH Aachen University, 2022$$bDissertation$$cRWTH Aachen University$$d2022
000907641 520__ $$aHigh-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
000907641 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
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000907641 9141_ $$y2022
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