Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety
Paraffin wax deposition from crude oil along pipeline is a global problem, making preventive methods preferred to removal methods. In this work, a neural network model based on mathematical modeling technique using regression analysis as the statistical tool was developed to predict the wax depositi...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
Taylor & Francis Group
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/31131 |
| _version_ | 1848753289795993600 |
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| author | Obanijesu, Emmanuel Omidiora, E. |
| author_facet | Obanijesu, Emmanuel Omidiora, E. |
| author_sort | Obanijesu, Emmanuel |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Paraffin wax deposition from crude oil along pipeline is a global problem, making preventive methods preferred to removal methods. In this work, a neural network model based on mathematical modeling technique using regression analysis as the statistical tool was developed to predict the wax deposition potential of 11 reservoirs in Nigeria. Using the viscosity-pressure-temperature data obtained from these fields to supervise the model, the model accurately predicted the present real-life situation in each field. Conclusively, the model could be used to predict wax deposition potential of any reservoir that is yet to be explored provided the temperature used during prediction is close to the actual reservoir temperature. |
| first_indexed | 2025-11-14T08:22:09Z |
| format | Journal Article |
| id | curtin-20.500.11937-31131 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:22:09Z |
| publishDate | 2008 |
| publisher | Taylor & Francis Group |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-311312017-09-13T15:11:18Z Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety Obanijesu, Emmanuel Omidiora, E. Paraffin wax deposition from crude oil along pipeline is a global problem, making preventive methods preferred to removal methods. In this work, a neural network model based on mathematical modeling technique using regression analysis as the statistical tool was developed to predict the wax deposition potential of 11 reservoirs in Nigeria. Using the viscosity-pressure-temperature data obtained from these fields to supervise the model, the model accurately predicted the present real-life situation in each field. Conclusively, the model could be used to predict wax deposition potential of any reservoir that is yet to be explored provided the temperature used during prediction is close to the actual reservoir temperature. 2008 Journal Article http://hdl.handle.net/20.500.11937/31131 10.1080/10916460701399485 Taylor & Francis Group restricted |
| spellingShingle | Obanijesu, Emmanuel Omidiora, E. Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title | Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title_full | Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title_fullStr | Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title_full_unstemmed | Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title_short | Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety |
| title_sort | artificial neural network's prediction of wax deposition potential of nigerian crude oil for pipeline safety |
| url | http://hdl.handle.net/20.500.11937/31131 |