Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling | Zendy

Jawad Ali | Zendy; Umar Ashraf | Zendy; Aqsa Anees | Zendy; Sanxi Peng | Zendy; Muhammad Ubaid Umar | Zendy; Hung Vo Thanh | Zendy; Umair Khan | Zendy; Mohamed Abioui | Zendy; Hassan Nasir Mangi | Zendy; Muhammad Ali | Zendy; Jar Ullah | Zendy

Open Access

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling

Author(s) -

Jawad Ali,

Umar Ashraf,

Aqsa Anees,

Sanxi Peng,

Muhammad Ubaid Umar,

Hung Vo Thanh,

Umair Khan,

Mohamed Abioui,

Hassan Nasir Mangi,

Muhammad Ali,

Jar Ullah

Publication year - 2022

Publication title -

acs omega

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.779

H-Index - 40

ISSN - 2470-1343

DOI - 10.1021/acsomega.2c05759

Subject(s) - petrophysics , geology , oil shale , well logging , petroleum engineering , formation evaluation , reservoir modeling , hydrocarbon exploration , permeability (electromagnetism) , oil in place , petroleum reservoir , petroleum , petrology , structural basin , porosity , mineralogy , geomorphology , geotechnical engineering , paleontology , membrane , biology , genetics

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