Joint inversion of full-waveform ground-penetrating radar and electrical resistivity data — Part 2: Enhancing low frequencies with the envelope transform and cross gradients

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. H115-H132 ◽  
Author(s):  
Diego Domenzain ◽  
John Bradford ◽  
Jodi Mead
Keyword(s):  
Electrical Resistivity ◽  
Ground Penetrating Radar ◽  
Material Properties ◽  
Joint Inversion ◽  
Low Frequency ◽  
Model Parameters ◽  
Frequency Content ◽  
Low Frequencies ◽  
Full Waveform ◽  
Ground Penetrating

Recovering material properties of the subsurface using ground-penetrating radar (GPR) data of finite bandwidth with missing low frequencies and in the presence of strong attenuation is a challenging problem. We have adopted three nonlinear inverse methods for recovering electrical conductivity and permittivity of the subsurface by joining GPR multioffset and electrical resistivity (ER) data acquired at the surface. All of the methods use ER data to constrain the low spatial frequency of the conductivity solution. The first method uses the envelope of the GPR data to exploit low-frequency content in full-waveform inversion and does not assume structural similarities of the material properties. The second method uses cross gradients to manage weak amplitudes in the GPR data by assuming structural similarities between permittivity and conductivity. The third method uses the envelope of the GPR data and the cross gradient of the model parameters. By joining ER and GPR data, exploiting low-frequency content in the GPR data, and assuming structural similarities between the electrical permittivity and conductivity, we are able to recover subsurface parameters in regions where the GPR data have a signal-to-noise ratio close to one.

Joint inversion of full-waveform ground-penetrating radar and electrical resistivity data: Part 1

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. H97-H113 ◽  
Author(s):  
Diego Domenzain ◽  
John Bradford ◽  
Jodi Mead
Keyword(s):  
Electrical Conductivity ◽  
Electrical Resistivity ◽  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Geophysical Methods ◽  
Data Types ◽  
Full Waveform ◽  
Electrical Permittivity ◽  
Ground Penetrating ◽  
Subsurface Geometry

We have developed an algorithm for joint inversion of full-waveform ground-penetrating radar (GPR) and electrical resistivity (ER) data. The GPR data are sensitive to electrical permittivity through reflectivity and velocity, and electrical conductivity through reflectivity and attenuation. The ER data are directly sensitive to the electrical conductivity. The two types of data are inherently linked through Maxwell’s equations, and we jointly invert them. Our results show that the two types of data work cooperatively to effectively regularize each other while honoring the physics of the geophysical methods. We first compute sensitivity updates separately for the GPR and ER data using the adjoint method, and then we sum these updates to account for both types of sensitivities. The sensitivities are added with the paradigm of letting both data types always contribute to our inversion in proportion to how well their respective objective functions are being resolved in each iteration. Our algorithm makes no assumptions of the subsurface geometry nor the structural similarities between the parameters with the caveat of needing a good initial model. We find that our joint inversion outperforms the GPR and ER separate inversions, and we determine that GPR effectively supports ER in regions of low conductivity, whereas ER supports GPR in regions with strong attenuation.

Joint full-waveform GPR and ER inversion applied to field data acquired on the surface

Geophysics ◽  
2021 ◽  
pp. 1-77
Author(s):  
diego domenzain ◽  
John Bradford ◽  
Jodi Mead
Keyword(s):  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Shallow Groundwater ◽  
Computational Domain ◽  
Alluvial Deposits ◽  
Subsurface Structures ◽  
Full Waveform ◽  
Stable Source ◽  
Ground Penetrating

We exploit the different but complementary data sensitivities of ground penetrating radar (GPR) and electrical resistivity (ER) by applying a multi-physics, multi-parameter, simultaneous 2.5D joint inversion without invoking petrophysical relationships. Our method joins full-waveform inversion (FWI) GPR with adjoint derived ER sensitivities on the same computational domain. We incorporate a stable source estimation routine into the FWI-GPR.We apply our method in a controlled alluvial aquifer using only surface acquired data. The site exhibits a shallow groundwater boundary and unconsolidated heterogeneous alluvial deposits. We compare our recovered parameters to individual FWI-GPR and ER results, and to log measurements of capacitive conductivity and neutron-derived porosity. Our joint inversion provides a more representative depiction of subsurface structures because it incorporates multiple intrinsic parameters, and it is therefore superior to an interpretation based on log data, FWI-GPR, or ER alone.

Joint acoustic full-waveform inversion of crosshole seismic and ground-penetrating radar data in the frequency domain

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. H41-H56 ◽  
Author(s):  
Xuan Feng ◽  
Qianci Ren ◽  
Cai Liu ◽  
Xuebing Zhang
Keyword(s):  
Frequency Domain ◽  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Structural Similarity ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Frequency Domain Methods ◽  
Ground Penetrating

Integrating crosshole ground-penetrating radar (GPR) with seismic methods is an efficient way to reduce the uncertainty and ambiguity of data interpretation in shallow geophysical investigations. We have developed a new approach for joint full-waveform inversion (FWI) of crosshole seismic and GPR data in the frequency domain to improve the inversion results of both FWI methods. In a joint objective function, three geophysical parameters (P-wave velocity, permittivity, and conductivity) are effectively connected by three weighted cross-gradient terms that enforce the structural similarity between parameter models. Simulation of acoustic seismic and scalar electromagnetic problems is implemented using 2D finite-difference frequency-domain methods, and the inverse problems of seismic FWI and GPR FWI are solved using a matrix-free truncated Newton algorithm. The joint inversion procedure is performed in several hierarchical frequencies, and the three parameter models are sequentially inverted at each frequency. The joint FWI approach is illustrated using three numerical examples. The results indicate that the joint FWI approach can effectively enhance the structural similarity among the models, modify the structure of each model, and improve the accuracy of inversion results compared with those of individual FWI approaches. Moreover, joint inversion can reduce the trade-off between permittivity and conductivity in GPR FWI, leading to an improved conductivity model in which artifacts are significantly decreased.

scholarly journals Waveform inversion based on wavefield decomposition

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. R457-R470 ◽  
Author(s):  
Fang Wang ◽  
Daniela Donno ◽  
Hervé Chauris ◽  
Henri Calandra ◽  
François Audebert
Keyword(s):  
Waveform Inversion ◽  
Low Frequency ◽  
Velocity Model ◽  
Model Parameters ◽  
Data Set ◽  
Low Frequencies ◽  
Full Waveform ◽  
Highly Nonlinear ◽  
Gradient Based ◽  
Wavefield Decomposition

Full-waveform inversion (FWI) is a technique for determining the optimal model parameters by minimizing the seismic data misfit between observed and modeled data. The objective function may be highly nonlinear if the model is complex and low-frequency data are missing. If a data set mainly contains reflections, this problem particularly prevents the gradient-based methods from recovering the long wavelengths of the velocity model. Several authors observed that nonlinearity could be reduced by progressively introducing higher wavenumbers to the model. We have developed a new inversion workflow to solve this problem by breaking down the FWI gradient formula into four terms after wavefield decomposition and then selecting proper terms to invert for the short- and long-wavelength components of the velocity model alternately. Numerical tests applied on a 2D synthetic model indicate that this method is efficient at recovering the long wavelengths of the velocity model using mainly offset-limited reflection events. The source does not need to contain low frequencies. The initial velocity model may have large errors that would otherwise prevent convergence for conventional FWI.

scholarly journals Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes

2021 ◽  
Vol 13 (9) ◽  
pp. 1846
Author(s):  
Vivek Kumar ◽  
Isabel M. Morris ◽  
Santiago A. Lopez ◽  
Branko Glisic
Keyword(s):  
Compressive Strength ◽  
Ground Penetrating Radar ◽  
Material Properties ◽  
Temporal Variations ◽  
Concrete Bridges ◽  
Spatial And Temporal Variation ◽  
Reflected Waves ◽  
Ground Penetrating ◽  
Over Time

Estimating variations in material properties over space and time is essential for the purposes of structural health monitoring (SHM), mandated inspection, and insurance of civil infrastructure. Properties such as compressive strength evolve over time and are reflective of the overall condition of the aging infrastructure. Concrete structures pose an additional challenge due to the inherent spatial variability of material properties over large length scales. In recent years, nondestructive approaches such as rebound hammer and ultrasonic velocity have been used to determine the in situ material properties of concrete with a focus on the compressive strength. However, these methods require personnel expertise, careful data collection, and high investment. This paper presents a novel approach using ground penetrating radar (GPR) to estimate the variability of in situ material properties over time and space for assessment of concrete bridges. The results show that attributes (or features) of the GPR data such as raw average amplitudes can be used to identify differences in compressive strength across the deck of a concrete bridge. Attributes such as instantaneous amplitudes and intensity of reflected waves are useful in predicting the material properties such as compressive strength, porosity, and density. For compressive strength, one alternative approach of the Maturity Index (MI) was used to estimate the present values and compare with GPR estimated values. The results show that GPR attributes could be successfully used for identifying spatial and temporal variation of concrete properties. Finally, discussions are presented regarding their suitability and limitations for field applications.

Ground-penetrating radar and electrical resistivity tomography studies in the biblical Pisidian Antioch city, southwest Anatolia

2018 ◽  
Vol 25 (4) ◽  
pp. 285-300 ◽  
Author(s):  
Çağlayan Balkaya ◽  
Ümit Yalçın Kalyoncuoğlu ◽  
Mehmet Özhanlı ◽  
Gözde Merter ◽  
Olcay Çakmak ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Ground Penetrating Radar ◽  
Electrical Resistivity Tomography ◽  
Resistivity Tomography ◽  
Ground Penetrating
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