scholarly journals Improved hydrogeophysical characterization using joint inversion of cross-hole electrical resistance and ground-penetrating radar traveltime data

2006 ◽  
Vol 42 (12) ◽  
Author(s):  
Niklas Linde ◽  
Andrew Binley ◽  
Ari Tryggvason ◽  
Laust B. Pedersen ◽  
André Revil
Keyword(s):  
Ground Penetrating Radar ◽  
Electrical Resistance ◽  
Joint Inversion ◽  
Ground Penetrating

Monte Albán's Hidden Past: Buried Buildings and Sociopolitical Transformation

2020 ◽  
pp. 1-23
Author(s):  
Marc N. Levine ◽  
Scott W. Hammerstedt ◽  
Amanda Regnier ◽  
Alex E. Badillo
Keyword(s):  
Ground Penetrating Radar ◽  
Electrical Resistance ◽  
Early History ◽  
Buried Structures ◽  
Systematic Survey ◽  
Monte Alban ◽  
Ground Penetrating ◽  
Shed Light

In this article, we present the most significant results of the Monte Albán Geophysical Archaeology Project. Using ground-penetrating radar, gradiometry, and electrical resistance, we carried out a systematic survey of the site's Main Plaza to identify buried prehispanic features that might shed light on Monte Albán's early history. The most important discoveries include three buried structures dating between the Danibaan (500–300 BC) and Nisa phases (100 BC–AD 100). We argue that the largest structure, measuring 18 × 18 m, was probably a temple platform and that all three of the structures were razed and buried by the end of the Nisa phase at the latest. Furthermore, we contend that these events were part of a major renovation and expansion of the site's Main Plaza that occurred during a pivotal period of dramatic sociopolitical transformation in the Zapotec capital.

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 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 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.

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.

scholarly journals Sensitivity Analysis for Joint Inversion of Ground-Penetrating Radar and Thermal-Hydrological Data from a Large-Scale Underground Heater Test

2008 ◽  
Vol 164 (2) ◽  
pp. 169-179 ◽  
Author(s):  
M. B. Kowalsky ◽  
J. Birkholzer ◽  
J. Peterson ◽  
S. Finsterle ◽  
S. Mukhopadhyay ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ground Penetrating Radar ◽  
Large Scale ◽  
Joint Inversion ◽  
Hydrological Data ◽  
Ground Penetrating

REFLECTION COEFFICIENT OF AN ELECTROMAGNETIC WAVE IN CONDUCTIVE MEDIA

2018 ◽  
pp. 100-106
Author(s):  
M. S. Sudakova ◽  
M. L. Vladov ◽  
M. R. Sadurtdinov
Keyword(s):  
Reflection Coefficient ◽  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Water Contamination ◽  
Survey Design ◽  
Direct And Inverse Problems ◽  
The Difference ◽  
Ground Penetrating ◽  
Ideal Dielectric

Within the ground penetrating radar bandwidth the medium is considered to be an ideal dielectric, which is not always true. Electromagnetic waves reflection coefficient conductivity dependence showed a significant role of the difference in conductivity in reflection strength. It was confirmed by physical modeling. Conductivity of geological media should be taken into account when solving direct and inverse problems, survey design planning, etc. Ground penetrating radar can be used to solve the problem of mapping of halocline or determine water contamination.

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