Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia
A large database of nuclear magnetic resonance (NMR) logging data from clastic rocks of offshore oil and gas fields of Western Australia was used to assess the performance of multi regression analysis (MRA) to calculate NMR log outputs from conventional well logs. This short paper introduces a set o...
| Main Author: | |
|---|---|
| Format: | Journal Article |
| Published: |
2022
|
| Online Access: | http://hdl.handle.net/20.500.11937/88942 |
| _version_ | 1848765120114589696 |
|---|---|
| author | Rezaee, Reza |
| author_facet | Rezaee, Reza |
| author_sort | Rezaee, Reza |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A large database of nuclear magnetic resonance (NMR) logging data from clastic rocks of offshore oil and gas fields of Western Australia was used to assess the performance of multi regression analysis (MRA) to calculate NMR log outputs from conventional well logs. This short paper introduces a set of MRA equations for the calculation of the NMR log outputs using conventional well logs as inputs. This study shows that unlike machine learning methods the MRA approach fails to predict most of the NMR log outputs with acceptable accuracy but can provide Coates and SDR permeabilities with R2 of more than 0.75. |
| first_indexed | 2025-11-14T11:30:12Z |
| format | Journal Article |
| id | curtin-20.500.11937-88942 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:30:12Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-889422022-08-05T07:55:39Z Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia Rezaee, Reza A large database of nuclear magnetic resonance (NMR) logging data from clastic rocks of offshore oil and gas fields of Western Australia was used to assess the performance of multi regression analysis (MRA) to calculate NMR log outputs from conventional well logs. This short paper introduces a set of MRA equations for the calculation of the NMR log outputs using conventional well logs as inputs. This study shows that unlike machine learning methods the MRA approach fails to predict most of the NMR log outputs with acceptable accuracy but can provide Coates and SDR permeabilities with R2 of more than 0.75. 2022 Journal Article http://hdl.handle.net/20.500.11937/88942 10.3390/fuels3020019 http://creativecommons.org/licenses/by/4.0/ fulltext |
| spellingShingle | Rezaee, Reza Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title | Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title_full | Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title_fullStr | Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title_full_unstemmed | Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title_short | Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia |
| title_sort | nuclear magnetic resonance (nmr) outputs generation for clastic rocks using multi regression analysis, examples from offshore western australia |
| url | http://hdl.handle.net/20.500.11937/88942 |