Work

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

Year: 2017

Type: article

Source: Arabian Journal of Geosciences

DOI: 10.1007/s12517-017-3344-y

Authors: Rafik Baouche, Tahar Aïfa, Kamel Baddari

Institutions: University of Boumerdes, Centre National de la Recherche Scientifique, Géosciences Rennes, Université Rennes 1, Université de Rennes

Language: English

Topic: Hydrocarbon exploration and reservoir analysis

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W2781182254

FWCI: 0.727

Cites: 46

Cited by: 13

Related to: 10