Intelligent methods for predicting nuclear magnetic resonance of porosity and permeability by conventional well-logs : a case study of Saharan field

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dc.contributor.authorBaouche, Rafik
dc.contributor.authorAïfa, Tahar
dc.date.accessioned2018-01-10T08:15:29Z
dc.date.available2018-01-10T08:15:29Z
dc.date.issued2017
dc.identifier.issn1866-7511
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/4305
dc.identifier.urihttps://doi.org/10.1007/s12517-017-3344-y
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesArabian Journal of Geosciences/ (2017);p. 21
dc.subjectPorosity/permeability estimationen_US
dc.subjectIntelligent reservoir characterizationen_US
dc.subjectSaharan oil fielden_US
dc.subjectNMR predictionen_US
dc.titleIntelligent methods for predicting nuclear magnetic resonance of porosity and permeability by conventional well-logs : a case study of Saharan fielden_US
dc.typeArticleen_US

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