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29. GLOBAL OPTIMIZATION OF VERTICAL ELECTRICAL SOUNDING DATA USING GENETIC ALGORITHM: A CASE STUDY OF AGBOYI OGUDU LAGOS STATE IN SOUTHWESTERN NIGERIA by Adeoti L., Ademilola J.A., Oigbochie L., Ishola K.S., Adegbola A.B., Adeogun O.Y., Allo, O.J., Oyenir
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GLOBAL OPTIMIZATION OF VERTICAL ELECTRICAL SOUNDING DATA USING GENETIC ALGORITHM: A CASE STUDY OF AGBOYI OGUDU LAGOS STATE IN SOUTHWESTERN NIGERIA

Adeoti L., Ademilola J.A., Oigbochie L., Ishola K.S., Adegbola A.B.1, Adeogun O.Y., Allo, O.J., Oyeniran T.A., and Matthew S.

Department of Geosciences, University of Lagos, Lagos, Nigeria

Department of Physics, Lagos State University, Ojo, Lagos, Nigeria

Department of Physical Science, Yaba College of Technology, Lagos, Nigeria

Abstract

Genetic Algorithm (GA) technique was applied on Vertical Electrical Sounding (VES) data acquired at Agboyi - Ogudu Lagos state, Nigeria, with a view to obtaining the global optimized resistivity of the study area. A total of 33 VES points on 6 profiles were analyzed. The VES data were constrained by borehole data. A stand-alone GA-based computer program in MATLAB programming language was developed for optimizing the subsurface layer parameters from the VES data and to reject bad data points, which have abrupt resistivity changes compared to the surrounding points. The optimized VES geoelectric sections delineate four geoelectric layers which correspond to topsoil (sand), sandy clay, clayey sand, and clay. The topsoil with thickness ranging from 0.84-3.1 m and resistivity values ranging from 1.37-200 ohm-m is indicative of clay and sand at various locations. The second optimized geoelectric layer has thickness ranging from 0.52-10.6 m and resistivity values ranging from 0.68- 36 ohm-m, diagnostic of sand in some locations and clay in other locations, the third optimized geoelectric layer with thickness ranging from 2.59-25.74 m and resistivity ranging from 1.99-8.49 ohm-m is symptomatic of  clayey sand, sandy clay and clay at various locations. The fourth geoelectric layer has resistivity values ranging from 2.16 – 9.47 ohm-m is indicative of clay, clayey sand, sandy clay and sand at various locations. The thickness in the fourth layers cannot be determined because the current terminated within the region. The subsurface layer parameters which are the true resistivity and thickness were obtained by the GA technique, which show the contrasts in local and optimized VES data as expressed in the root mean square error (RMSE) values ranging from 1.67 to 34.11, with larger values indicating significant difference in the local and optimized VES data. The results of this work show close agreement between the observed and calculated (global) apparent resistivity at most VES points, and hence implies that GA optimization technique could be efficient and reliable for determining subsurface layer parameters. However, where large error margins at other VES points are observed, the program used for this study should be improved to reduce root mean square error (RMSE).

Keywords: Genetic algorithm, Vertical Electrical Sounding, Global optimization technique

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