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

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 consi...

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Main Author: Bala, Muhammad Sabiu
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://eprints.usm.my/44169/
http://eprints.usm.my/44169/1/MUHAMMAD%20SABIU%20BALA.pdf
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author Bala, Muhammad Sabiu
author_facet Bala, Muhammad Sabiu
author_sort Bala, Muhammad Sabiu
building USM Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T17:56:00Z
format Thesis
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institution Universiti Sains Malaysia
institution_category Local University
language English
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publishDate 2018
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spelling usm-441692019-04-23T01:16:38Z http://eprints.usm.my/44169/ Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements Bala, Muhammad Sabiu QC1 Physics (General) 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. 2018-06 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/44169/1/MUHAMMAD%20SABIU%20BALA.pdf Bala, Muhammad Sabiu (2018) Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements. PhD thesis, Universiti Sains Malaysia.
spellingShingle QC1 Physics (General)
Bala, Muhammad Sabiu
Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title_full Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title_fullStr Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title_full_unstemmed Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title_short Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
title_sort multiple linear regression models for estimating true subsurface resistivity from apparent resistivity measurements
topic QC1 Physics (General)
url http://eprints.usm.my/44169/
http://eprints.usm.my/44169/1/MUHAMMAD%20SABIU%20BALA.pdf