Prediction of total organic carbon at Rumaila oil field, Southern Iraq using conventional well logs and machine learning algorithms

Author:

Handhal Amna M.,Al-Abadi Alaa M.,Chafeet Hussein E.,Ismail Maher J.

Publisher

Elsevier BV

Subject

Stratigraphy,Economic Geology,Geology,Geophysics,Oceanography

Reference57 articles.

1. Estimation of Total Organic Carbon from well logs and seismic sections via neural network and ant colony optimization approach: a case study from the Mansuri oil field, SW Iran;Abdizadeh;Geopersia,2017

2. Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study;Al-Abadi;Arab. J. Geosci.,2018

3. Evaluating the Dibdibba aquifer productivity at the Karbala–Najaf plateau (Central Iraq) using GIS-based tree machine learning algorithms;Al-Abadi;Nat. Resour. Res.,2019

4. Spatial mapping of artesian zone at Iraqi southern desert using a GIS-based random forest machine learning model;Al-Abadi;Model. Earth Syst. Environ.,2016

5. Palynofacies and source potential for hydrocarbon, uppermost Jurassic-basal Cretaceous in Sulaiy Formation, southern Iraq;Al-Ameri;Cretac. Res.,1999

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