Data-driven inversion of GPR surface reflection data for lossless layered media

Slob, Evert; Wapenaar, Kees

doi:10.1109/eucap.2014.6902553

Cited by 5 publications

(7 citation statements)

References 12 publications

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“…It is a full waveform inversion method if the electric and magnetic parameters are obtained as a function of the subsurface position. Recently, some datadriven methods based on the Marchenko scheme have been proposed [11,15,17]. It was shown that the wave fields and focusing wave fields inside an unknown medium can be retrieved by solving a set of Marchenko-type equations [11,19].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, some datadriven methods based on the Marchenko scheme have been proposed [11,15,17]. It was shown that the wave fields and focusing wave fields inside an unknown medium can be retrieved by solving a set of Marchenko-type equations [11,19]. The Marchenko inversion scheme can be implemented as long as the Green's function or/and the focusing function are obtained because the local reflectivity or impedance can be obtained as a starting point for further inversion [11,17].…”

Section: Introductionmentioning

confidence: 99%

“…It was shown that the wave fields and focusing wave fields inside an unknown medium can be retrieved by solving a set of Marchenko-type equations [11,19]. The Marchenko inversion scheme can be implemented as long as the Green's function or/and the focusing function are obtained because the local reflectivity or impedance can be obtained as a starting point for further inversion [11,17]. The theory for 1D GPR inversion based on Marchenko redatuming has been derived for a lossless medium [11].…”

Section: Introductionmentioning

confidence: 99%

“…The Marchenko inversion scheme can be implemented as long as the Green's function or/and the focusing function are obtained because the local reflectivity or impedance can be obtained as a starting point for further inversion [11,17]. The theory for 1D GPR inversion based on Marchenko redatuming has been derived for a lossless medium [11]. A 3D Marchenko redatuming method for dissipative acoustic media has been developed [13].…”

Section: Introductionmentioning

confidence: 99%

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Marchenko Inversion of GPR Data for a 1d Dissipative Medium

Yang¹,

Slob²

2021

PIER M

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Radar data collected on two sides of a horizontally dissipative layered medium are required to invert for the medium parameters. The two-sided reflection and transmission responses are reduced to two single-sided reflection responses. One is the measured dissipative medium response, and the other is the reflection response of the corresponding effectual medium, which has negative dissipation. Marchenko-type equations are solved using these two reflection responses. The obtained focusing functions in the dissipative and effectual media are used to invert for the permittivity and the permeability under the assumption of weak dissipation in reflection. Once these parameters are known, the travel times are used to estimate the layer thicknesses. Finally, the focusing functions are used to estimate the conductivity in each layer. The method does not require any model information and runs as a fully automated process. A numerical example shows that the method works well for a horizontally dissipative layered medium. Statistical analysis for several noise models shows that the method is robust at least up to 40 dB additive and multiplicative white noise.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Marchenko Inversion of GPR Data for a 1d Dissipative Medium

Yang¹,

Slob²

2021

PIER M

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“…It can be used to eliminate the effect of internal multiples in a seismic or GPR image [9][10] [11]. A GPR inversion method for lossless medium based on Marchenko method has been developed [12]. This is a data-driven method, but it can deal only with lossless media and still needs to know the source signature.…”

Section: Introductionmentioning

confidence: 99%

Theory for 1D GPR data inversion for a dissipative layered medium

Yang

Slob

2018

2018 17th International Conference on Ground Penetrating Radar (GPR)

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We present a data driven method of full waveform inversion in one dimension. This means that the inversion is carried out as a sequence of processing steps. The first step is known as Marchenko redatuming. In this step we retrieve focusing functions from the measured data. In the second step we isolate the last event in the focusing function to obtain the local reflection coefficient of a particular reflecting boundary. This is done for the dissipative and equivalent effectual model. An effectual medium amplifies a propagating wave in the same way as a dissipative medium attenuates it. From these two models the reflection coefficient of the corresponding lossless medium can be computed. This is then inverted for the electric permittivity. Once the permittivity is found, the individual layer thicknesses are obtained from the travel times. The ratio of the reflection coefficient in the physical and effectual medium provides an estimate of the attenuation in each layer from which the conductivity in each layer can be found. We show that in this case the full waveform inversion is a linear problem. We need reflection and transmission data measured at two sides of the medium. We use an unconditionally convergent iterative technique to compute the focusing functions. The method only needs the upand downgoing parts of the electric field at the receiver levels. A 1D numerical example with a lossy model shows that the proposed GPR inversion method is effective on modeled data.

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Electromagnetic Marchenko imaging in 1D

Zhang

Slob

2016

2016 16th International Conference on Ground Penetrating Radar (GPR)

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Data-driven inversion of GPR surface reflection data for lossless layered media

Cited by 5 publications

References 12 publications

Marchenko Inversion of GPR Data for a 1d Dissipative Medium

Marchenko Inversion of GPR Data for a 1d Dissipative Medium

Theory for 1D GPR data inversion for a dissipative layered medium

Electromagnetic Marchenko imaging in 1D

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