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dc.contributor.authorRezaee, Reza
dc.date.accessioned2022-07-18T03:25:02Z
dc.date.available2022-07-18T03:25:02Z
dc.date.issued2022
dc.identifier.citationRezaee, R. 2022. Nuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia. Fuels. 3(2): pp. 316-325.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/88942
dc.identifier.doi10.3390/fuels3020019
dc.description.abstract

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.

dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleNuclear Magnetic Resonance (NMR) Outputs Generation for Clastic Rocks Using Multi Regression Analysis, Examples from Offshore Western Australia
dc.typeJournal Article
dcterms.source.titleFuels
dc.date.updated2022-07-18T03:25:01Z
curtin.departmentWASM: Minerals, Energy and Chemical Engineering
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidRezaee, Reza [0000-0001-9342-8214]
curtin.contributor.researcheridRezaee, Reza [A-5965-2008]
curtin.contributor.scopusauthoridRezaee, Reza [39062014600]


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