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Geoelectrical resistivity data sets for subsurface characterisation and aquifer delineation in Iyesi, southwestern Nigeria.
Aizebeokhai, Ahzegbobor P; Oyeyemi, Kehinde D; Noiki, Funmilola R; Etete, Blessing I; Arere, Akpore U E; Eyo, Ubongabasi J; Ogbuehi, Valentino C.
Affiliation
  • Aizebeokhai AP; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Oyeyemi KD; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Noiki FR; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Etete BI; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Arere AUE; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Eyo UJ; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
  • Ogbuehi VC; Applied Geophysics Group, College of Science and Technology, Covenant University, Ota, Nigeria.
Data Brief ; 15: 828-832, 2017 Dec.
Article in En | MEDLINE | ID: mdl-29159221
ABSTRACT
This article consists of geoelectrical resistivity data sets for thirty (30) vertical electrical sounding (VES) and four (4) traverses of 2D electrical resistivity imaging (ERI) collected within Iyesi, Ota, southwestern Nigeria for about five (5) weeks between December, 2016 and January, 2017 using an ABEM Terrameter (SAS1000/4000). The observed apparent resistivity data sets for the VES were processed using WinResist to obtain geoelectric layer parameters while those of the 2D ERI were processed with RES2DINV to obtain 2D inverse model resistivity images. The geoelectric parameters for the VES and the inverse models for the 2D ERI were integrated to characterise the subsurface and delineate the underlying aquifer units.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Data Brief Year: 2017 Document type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Data Brief Year: 2017 Document type: Article