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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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Online Access: | http://eprints.usm.my/44169/ http://eprints.usm.my/44169/1/MUHAMMAD%20SABIU%20BALA.pdf |
| _version_ | 1848879990029942784 |
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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 |
| id | usm-44169 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:56:00Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 |