Quantitative conductivity and permittivity estimation using full-waveform inversion of on-ground GPR data

Geophysics ◽  
2012 ◽  
Vol 77 (6) ◽  
pp. H79-H91 ◽  
Author(s):  
Sebastian Busch ◽  
Jan van der Kruk ◽  
Jutta Bikowski ◽  
Harry Vereecken
Keyword(s):  
Quantitative Estimation ◽  
Waveform Inversion ◽  
Measured Data ◽  
Optimization Approach ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Full Waveform ◽  
Novel Approach ◽  
Wide Range ◽  
Starting Model

Conventional ray-based techniques for analyzing common-midpoint (CMP) ground-penetrating radar (GPR) data use part of the measured data and simplified approximations of the reality to return qualitative results with limited spatial resolution. Whereas these methods can give reliable values for the permittivity of the subsurface by employing only the phase information, the far-field approximations used to estimate the conductivity of the ground are not valid for near-surface on-ground GPR, such that the estimated conductivity values are not representative for the area of investigation. Full-waveform inversion overcomes these limitations by using an accurate forward modeling and inverts significant parts of the measured data to return reliable quantitative estimates of permittivity and conductivity. Here, we developed a full-waveform inversion scheme that uses a 3D frequency-domain solution of Maxwell’s equations for a horizontally layered subsurface. Although a straightforward full-waveform inversion is relatively independent of the permittivity starting model, inaccuracies in the conductivity starting model result in erroneous effective wavelet amplitudes and therefore in erroneous inversion results, because the conductivity and wavelet amplitudes are coupled. Therefore, the permittivity and conductivity are updated together with the phase and the amplitude of the source wavelet with a gradient-free optimization approach. This novel full-waveform inversion is applied to synthetic and measured CMP data. In the case of synthetic single layered and waveguide data, where the starting model differs significantly from the true model parameter, we were able to reconstruct the obtained model properties and the effective source wavelet. For measured waveguide data, different starting values returned the same wavelet and quantitative permittivities and conductivities. This novel approach enables the quantitative estimation of permittivity and conductivity for the same sensing volume and enables an improved characterization for a wide range of applications.

scholarly journals Full Waveform Inversion in generalized coordinates for zones of curved topography

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
César Augusto Arias- Chica ◽  
David Abreo ◽  
Sergio Abreo ◽  
Luis Fernando Duque- Gómez ◽  
Ana Beatríz Ramírez- Silva
Keyword(s):  
Computing Time ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
Wide Range ◽  
Rugged Topography ◽  
Uniform Rectangular Grid

Full waveform inversion (FWI) has been recently used to estimate subsurface parameters, such as velocity models. This method, however, has a number of drawbacks when applied to zones with rugged topography due to the forced application of a Cartesian mesh on a curved surface. In this work, we present a simple coordinate transformation that enables the construction of a curved mesh. The proposed transformation is more suitable for rugged surfaces and it allows mapping a physical curved domain into a uniform rectangular grid, where acoustic FWI can be applied in the traditional way by introducing a modified Laplacian. We prove that the proposed approximation can have a wide range of applications, producing precise near-surface velocity models without increasing the computing time of the FWI.

FULL-WAVEFORM INVERSION WITH SOURCE AND RECEIVER COUPLING EFFECTS CORRECTION

Geophysics ◽  
2021 ◽  
pp. 1-37
Author(s):  
Xinhai Hu ◽  
Wei Guoqi ◽  
Jianyong Song ◽  
Zhifang Yang ◽  
Minghui Lu ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Nonlinear Least Squares ◽  
Real Data ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Linear Inversion ◽  
Near Surface ◽  
Model Parameter ◽  
Full Waveform ◽  
Coupling Factors

Coupling factors of sources and receivers vary dramatically due to the strong heterogeneity of near surface, which are as important as the model parameters for the inversion success. We propose a full waveform inversion (FWI) scheme that corrects for variable coupling factors while updating the model parameter. A linear inversion is embedded into the scheme to estimate the source and receiver factors and compute the amplitude weights according to the acquisition geometry. After the weights are introduced in the objective function, the inversion falls into the category of separable nonlinear least-squares problems. Hence, we could use the variable projection technique widely used in source estimation problem to invert the model parameter without the knowledge of source and receiver factors. The efficacy of the inversion scheme is demonstrated with two synthetic examples and one real data test.

Tunnel detection at Yuma Proving Ground, Arizona, USA — Part 1: 2D full-waveform inversion experiment

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. B95-B105 ◽  
Author(s):  
Yao Wang ◽  
Richard D. Miller ◽  
Shelby L. Peterie ◽  
Steven D. Sloan ◽  
Mark L. Moran ◽  
...  
Keyword(s):  
Surface Wave ◽  
Waveform Inversion ◽  
Velocity Profiles ◽  
Infinite Length ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Near Surface ◽  
Tunnel Detection ◽  
Full Waveform ◽  
Wave Methods

We have applied time domain 2D full-waveform inversion (FWI) to detect a known 10 m deep wood-framed tunnel at Yuma Proving Ground, Arizona. The acquired seismic data consist of a series of 2D survey lines that are perpendicular to the long axis of the tunnel. With the use of an initial model estimated from surface wave methods, a void-detection-oriented FWI workflow was applied. A straightforward [Formula: see text] quotient masking method was used to reduce the inversion artifacts and improve confidence in identifying anomalies that possess a high [Formula: see text] ratio. Using near-surface FWI, [Formula: see text] and [Formula: see text] velocity profiles were obtained with void anomalies that are easily interpreted. The inverted velocity profiles depict the tunnel as a low-velocity anomaly at the correct location and depth. A comparison of the observed and simulated waveforms demonstrates the reliability of inverted models. Because the known tunnel has a uniform shape and for our purposes an infinite length, we apply 1D interpolation to the inverted [Formula: see text] profiles to generate a pseudo 3D (2.5D) volume. Based on this research, we conclude the following: (1) FWI is effective in near-surface tunnel detection when high resolution is necessary. (2) Surface-wave methods can provide accurate initial S-wave velocity [Formula: see text] models for near-surface 2D FWI.

A focusing study of near-surface full-waveform inversion based on wave-mode separation

2017 ◽  
Author(s):  
Yao Wang ◽  
Richard Miller ◽  
Shelby Peterie ◽  
Steven Sloan ◽  
Mark Moran ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Wave Mode ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Full Waveform ◽  
Mode Separation

3D elastic full-waveform inversion of surface waves in the presence of irregular topography using an envelope-based misfit function

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. R1-R11 ◽  
Author(s):  
Dmitry Borisov ◽  
Ryan Modrak ◽  
Fuchun Gao ◽  
Jeroen Tromp
Keyword(s):  
Surface Wave ◽  
Objective Function ◽  
Surface Waves ◽  
Large Scale ◽  
Body Wave ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Near Surface ◽  
Full Waveform

Full-waveform inversion (FWI) is a powerful method for estimating the earth’s material properties. We demonstrate that surface-wave-driven FWI is well-suited to recovering near-surface structures and effective at providing S-wave speed starting models for use in conventional body-wave FWI. Using a synthetic example based on the SEG Advanced Modeling phase II foothills model, we started with an envelope-based objective function to invert for shallow large-scale heterogeneities. Then we used a waveform-difference objective function to obtain a higher-resolution model. To accurately model surface waves in the presence of complex tomography, we used a spectral-element wave-propagation solver. Envelope misfit functions are found to be effective at minimizing cycle-skipping issues in surface-wave inversions, and surface waves themselves are found to be useful for constraining complex near-surface features.

Full-waveform inversion of salt models using shape optimization and simulated annealing

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R793-R804 ◽  
Author(s):  
Debanjan Datta ◽  
Mrinal K. Sen ◽  
Faqi Liu ◽  
Scott Morton
Keyword(s):  
Simulated Annealing ◽  
Least Squares ◽  
Level Set ◽  
Waveform Inversion ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform ◽  
Starting Model

A good starting model is imperative in full-waveform inversion (FWI) because it solves a least-squares inversion problem using a local gradient-based optimization method. A suboptimal starting model can result in cycle skipping leading to poor convergence and incorrect estimation of subsurface properties. This problem is especially crucial for salt models because the strong velocity contrasts create substantial time shifts in the modeled seismogram. Incorrect estimation of salt bodies leads to velocity inaccuracies in the sediments because the least-squares gradient aims to reduce traveltime differences without considering the sharp velocity jump between sediments and salt. We have developed a technique to estimate velocity models containing salt bodies using a combination of global and local optimization techniques. To stabilize the global optimization algorithm and keep it computationally tractable, we reduce the number of model parameters by using sparse parameterization formulations. The sparse formulation represents sediments using a set of interfaces and velocities across them, whereas a set of ellipses represents the salt body. We use very fast simulated annealing (VFSA) to minimize the misfit between the observed and synthetic data and estimate an optimal model in the sparsely parameterized space. The VFSA inverted model is then used as a starting model in FWI in which the sediments and salt body are updated in the least-squares sense. We partition model updates into sediment and salt updates in which the sediments are updated like conventional FWI, whereas the shape of the salt is updated by taking the zero crossing of an evolving level set surface. Our algorithm is tested on two 2D synthetic salt models, namely, the Sigsbee 2A model and a modified SEG Advanced Modeling Program (SEAM) Phase I model while fixing the top of the salt. We determine the efficiency of the VFSA inversion and imaging improvements from the level set FWI approach and evaluate a few sources of uncertainty in the estimation of salt shapes.

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