Evidence of electrical anisotropy in limestone formations using the RMT technique

Détails

ID Serval
serval:BIB_7BB490140AD1
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Evidence of electrical anisotropy in limestone formations using the RMT technique
Périodique
Geophysics
Auteur⸱e⸱s
Linde N., Pedersen L.B.
ISSN-L
0016-8033
Statut éditorial
Publié
Date de publication
2004
Peer-reviewed
Oui
Volume
69
Pages
909-916
Langue
anglais
Notes
ISI:000223303700004
Résumé
Azimuthal resistivity surveys are often applied to complement
hydrological information or to improve the location of observation
boreholes in pump tests. Symmetric electrode configurations cannot
distinguish anisotropy from lateral changes or dipping layers, but
asymmetric arrays (e.g., the offset Wenner array) can. Tensor
radiomagnetotellurics (RMT) is presented as an alternative method in
studies of electrical anisotropy in the shallow subsurface. The
electromagnetic. and geomagnetic transfer functions provide information
about the dimensionality of the data; These transfer functions can also
be used to find the directions of anisotropy. Data with an anisotropic
signature can be inverted for a one-dimensional (113) azimuthal
anisotropy model. The method is faster than the azimuthal resistivity
method.
A 380-m-long profile of tensor RMT data (12.7-243 kHz) from limestones
that overlie shale on the island of Gotland, Sweden, is used to show the
merits of the method. The data have a clear anisotropic signature. The
data are inverted for a three-layer ID model with azimuthal anisotropy
using two different approaches: (1) a moving median filter of five
neighboring stations and neglecting static shift parameters; and (2)
treating each station separately and including static shifts of the
electric field in the inversion.' Both inversions show models having a
marked anisotropy with anisotropy factors of 3.7 and 4.5, respectively,
in the limestones. The second approach has a significantly better data
fit. However, the first approach is preferred because the models are
smoother from station to station.
Création de la notice
30/03/2012 13:21
Dernière modification de la notice
20/08/2019 15:37
Données d'usage