TY - GEN
T1 - (Pseudo-)3D inversion of geophysical electromagnetic induction data by using an arbitrary prior and constrained to ancillary information
AU - Zaru, Nicola
AU - Rossi, Matteo
AU - Vacca, Giuseppina
AU - Vignoli, Giulio
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/7/30
Y1 - 2023/7/30
N2 - Electromagnetic induction (EMI) methods are often used to map rapidly large areas with minimal logistical efforts. However, they are limited by a small number of frequencies and by their severe ill-posedness. On the other hand, electrical resistivity tomography (ERT) results are generally considered more reliable, with no need for specific calibration procedures and easy 2D/3D inversion. Still, ERT surveys are definitely more time-consuming, and, ideally, an approach with the advantages of both EMI and ERT would be optimal. The present research addresses this issue by incorporating realistic constraints into EMI inversion, going beyond simplistic spatial constraints like smooth or sharp regularization terms, while taking into consideration the ancillary information already available about the investigated site. We demonstrate how additional pre-existing information, such as a reference model (i.e., an existing ERT section) can enhance the EMI inversion. The study verifies the results against observations from boreholes.
AB - Electromagnetic induction (EMI) methods are often used to map rapidly large areas with minimal logistical efforts. However, they are limited by a small number of frequencies and by their severe ill-posedness. On the other hand, electrical resistivity tomography (ERT) results are generally considered more reliable, with no need for specific calibration procedures and easy 2D/3D inversion. Still, ERT surveys are definitely more time-consuming, and, ideally, an approach with the advantages of both EMI and ERT would be optimal. The present research addresses this issue by incorporating realistic constraints into EMI inversion, going beyond simplistic spatial constraints like smooth or sharp regularization terms, while taking into consideration the ancillary information already available about the investigated site. We demonstrate how additional pre-existing information, such as a reference model (i.e., an existing ERT section) can enhance the EMI inversion. The study verifies the results against observations from boreholes.
KW - Electromagnetic Induction
KW - Realistic Prior Distribution
KW - Spatially Constrained Inversion
UR - http://www.scopus.com/inward/record.url?scp=85164981334&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-37126-4_40
DO - 10.1007/978-3-031-37126-4_40
M3 - Conference article in proceedings
AN - SCOPUS:85164981334
SN - 978-3-031-37125-7
T3 - Lecture Notes in Computer Science
SP - 624
EP - 638
BT - Computational Science and Its Applications – ICCSA 2023 Workshops
A2 - Gervasi, Osvaldo
A2 - Murgante, Beniamino
A2 - Scorza, Francesco
A2 - Rocha, Ana Maria A.C.
A2 - Garau, Chiara
A2 - Karaca, Yeliz
A2 - Torre, Carmelo M.
PB - Springer
T2 - 23rd International Conference on Computational Science and Its Applications, ICCSA 2023
Y2 - 3 July 2023 through 6 July 2023
ER -