TY - JOUR
T1 - Joint Inversion of GPR and ER Data
AU - Domenzain, Diego
AU - Bradford, John
AU - Mead, Jodi
N1 - Electrical methods are proven tools for successfully imaging the subsurface (Jol, 2008; Knight, 2001). Ground penetrating radar (GPR) is sensitive to electrical permittivity through reflectivity and electrical conductivity through attenuation. Electrical resistivity tomography (ER) is directly sensitive to electrical conductivity. GPR and ER data hold high and low spacial-frequency information respectively of the media of interest.
PY - 2018/8/27
Y1 - 2018/8/27
N2 - Electrical methods are proven tools for successfully imaging the subsurface (Jol, 2008; Knight, 2001). Ground penetrating radar (GPR) is sensitive to electrical permittivity through reflectivity and electrical conductivity through attenuation. Electrical resistivity tomography (ER) is directly sensitive to electrical conductivity. GPR and ER data hold high and low spacial-frequency information respectively of the media of interest. We propose a joint inversion of GPR and ER data to image electrical permittivity and conductivity. The two types of data are inherently linked through Maxwell’s equations and work cooperatively to regularize each other while honoring the physics. We first compute sensitivity updates separately for both the GPR and ER data using the adjoint method, and then we sum these updates to account for both types of sensitivities. Our algorithm makes no assumption of the subsurface geometry with the caveat of needing a good initial model. In this work, we test our method with a numerical experiment.
AB - Electrical methods are proven tools for successfully imaging the subsurface (Jol, 2008; Knight, 2001). Ground penetrating radar (GPR) is sensitive to electrical permittivity through reflectivity and electrical conductivity through attenuation. Electrical resistivity tomography (ER) is directly sensitive to electrical conductivity. GPR and ER data hold high and low spacial-frequency information respectively of the media of interest. We propose a joint inversion of GPR and ER data to image electrical permittivity and conductivity. The two types of data are inherently linked through Maxwell’s equations and work cooperatively to regularize each other while honoring the physics. We first compute sensitivity updates separately for both the GPR and ER data using the adjoint method, and then we sum these updates to account for both types of sensitivities. Our algorithm makes no assumption of the subsurface geometry with the caveat of needing a good initial model. In this work, we test our method with a numerical experiment.
KW - 2D
KW - electrical/resistivity
KW - full-waveform inversion
KW - ground-penetrating radar (GPR)
KW - imaging
UR - http://dx.doi.org/10.1190/segam2018-2997794.1
UR - http://www.scopus.com/inward/record.url?scp=85121841508&partnerID=8YFLogxK
U2 - 10.1190/segam2018-2997794.1
DO - 10.1190/segam2018-2997794.1
M3 - Article
SN - 1949-4645
SP - 4763
EP - 4767
JO - SEG Technical Program Expanded Abstracts 2018
JF - SEG Technical Program Expanded Abstracts 2018
T2 - Society of Exploration Geophysicists International Exposition and 88th Annual Meeting, SEG 2018
Y2 - 14 October 2018 through 19 October 2018
ER -