Estimating petrophysical properties using Geostatistical inversion and data-driven extreme gradient boosting: A case study of late Eocene McKee formation, Taranaki Basin, New Zealand

Estimating petrophysical properties using Geostatistical inversion and data-driven extreme gradient boosting: A case study of late Eocene McKee formation, Taranaki Basin, New Zealand

Estimation of petrophysical properties holds significant importance in evaluating the feasibility of hydrocarbon extraction and enhancing production efficiency. Therefore, theintegration of seismic data with well data for reservoir characterization has garnered significant attention in the oil and g...

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Bibliographic Details
Main Authors: John Oluwadamilola Olutoki, Mohamed Elsaadany, Numair Ahmed Siddiqui, AKM Eahsanul Haque, Syed Haroon Ali, Alidu Rashid, Oluwaseun Daniel Akinyemi
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Results in Engineering
Subjects:
Reservoir characterization
Porosity prediction
Machine learning
Extreme gradient boosting
Geostatistical inversion
McKee
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024017468
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