Show simple item record

dc.contributor.authorObanijesu, Emmanuel
dc.contributor.authorOmidiora, E.
dc.date.accessioned2017-01-30T13:23:34Z
dc.date.available2017-01-30T13:23:34Z
dc.date.created2016-09-12T08:36:47Z
dc.date.issued2008
dc.identifier.citationObanijesu, E. and Omidiora, E. 2008. Artificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety. Petroleum Science and Technology. 26 (16): pp. 1977-1991.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/31131
dc.identifier.doi10.1080/10916460701399485
dc.description.abstract

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.

dc.publisherTaylor & Francis Group
dc.titleArtificial neural network's prediction of wax deposition potential of Nigerian crude oil for pipeline safety
dc.typeJournal Article
dcterms.source.volume26
dcterms.source.number16
dcterms.source.startPage1977
dcterms.source.endPage1991
dcterms.source.issn1091-6466
dcterms.source.titlePetroleum Science and Technology
curtin.departmentDepartment of Chemical Engineering
curtin.accessStatusFulltext not available


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record