Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements

Bala, Muhammad Sabiu (2018) Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements. PhD thesis, Universiti Sains Malaysia.

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Abstract

Multiple linear regression (MLR) models for rapid estimation of true subsurface resistivity from apparent resistivity measurements are developed and assessed in this study. The objective is to minimize the processing time required to carry out inversion with conventional algorithms. The arrays considered are Wenner, Wenner-Schlumberger and Dipole-dipole. The parameters investigated are apparent resistivity ( a  ), horizontal location (x) and depth (z) as independent variable; while true resistivity ( t  ) is dependent variable.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QC Physics > QC1 Physics (General)
Divisions:	Pusat Pengajian Sains Fizik (School of Physics) > Thesis
Depositing User:	ASM Ab Shukor Mustapa
Date Deposited:	23 Apr 2019 01:16
Last Modified:	23 Apr 2019 01:16
URI:	http://eprints.usm.my/id/eprint/44169

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