FUW TRENDS IN SCIENCE & TECHNOLOGY JOURNAL

(A Peer Review Journal)
e–ISSN: 2408–5162; p–ISSN: 2048–5170

FUW TRENDS IN SCIENCE & TECHNOLOGY JOURNAL

BASEMENT AQUIFER POTENTIALS DELINEATION IN ABEOKUTA SOUTHWESTERN BASEMENT COMPLEX OF NIGERIA USING ELECTRICAL RESISTIVITY SURVEY
Pages: 665-673
O. O. Bayewu 1 *, M. O. Oloruntola 2 , G. O. Mosuro 1 , S. O. Ariyo 1 , and O. O. Odugbesan


keywords: Basement aquifer, basement resistivity, reflection coefficient, water potential

Abstract

Electrical resistivity survey was carried out in some parts of Abeokuta, southwestern Nigeria with the aim of delineating the resistivity characteristics of the basement groundwater yield in the study area. The study area lies within the Southwestern Basement Complex of Nigeria and it is underlain by granite gneiss, biotite gneiss and porphyroblastic gneiss rock types. Thirty (30) Vertical Electrical Sounding (VES) points were probed using the Schlumberger configuration with maximum electrode spacing (AB/2) of 100 m. The VES data were plotted and were initially interpreted with the aid of partial curve matching approach, the results were further processed using the WINREST software to produce iterated curves which were used to delineate the respective layers, resistivity and depth of the subsurface. Iterated curves showed the presence of three (3) to five (5) inferred lithological units which include the topsoil (59.4 – 914.2 Ω m), the weathered layer which include clay/sandy-clay/sand (15.4 – 544.3 Ωm) and fresh/fractured basement (123.1 – 21858.5 Ωm). The overburden thickness ranges between 3.2 to 43.7 m; while reflection coefficient ranges between 0.71 – 0.99. The consideration of basement resistivity, overburden thickness and the reflection coefficient values were used to categorize the sample point into their yield potentials as either low, medium or high and it was used to generate a groundwater potential map for the area. The combination of these three resistivity survey parameters in predicting the water potential of the area therefore enhances the accuracy of the interpretation better than using one parameter for its prediction.

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