Total Organic Carbon Characterization Using Neural-Network Analysis of XRF Data-Reference-Cited by-同舟云学术

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Total Organic Carbon Characterization Using Neural-Network Analysis of XRF Data

Published:2019-08-01 Issue:4 Volume:60 Page:480-493
ISSN:1529-9074
Container-title:Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description
language:
Short-container-title:Petro S Journ

Author:

Owolabi Lawal Lateef, ,Mahmoud Mohamed,Saheed Alade Olalekan,Abdulraheem Abdulazeez, , ,

Publisher

Society of Petrophysicists and Well Log Analysts (SPWLA)

Subject

Geotechnical Engineering and Engineering Geology

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Petrophysical log-driven kerogen typing: unveiling the potential of hybrid machine learning;Journal of Petroleum Exploration and Production Technology;2023-08-09

2. An approach for total organic carbon prediction using convolutional neural networks optimized by differential evolution;Neural Computing and Applications;2023-07-25

3. Prediction of Total Organic Carbon in Organic-Rich Shale Rocks Using Thermal Neutron Parameters;ACS Omega;2023-01-24

4. Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods;Environmental Science: Advances;2023

5. Effect of Silica Nanoparticles on Polymer Adsorption Reduction on Marcellus Shale;ACS Omega;2021-10-29

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