Data-driven total organic carbon prediction using feature selection methods incorporated in an automated machine learning framework

Data-driven total organic carbon prediction using feature selection methods incorporated in an automated machine learning framework

An accurate assessment of shale gas resources is highly important for the sustainable development of these energy resources. Total organic carbon (TOC) analysis thus becomes fundamental for understanding the distribution and quality of hydrocarbon source rocks within a shale gas reservoir. The eleva...

Full description

Bibliographic Details
Main Authors: Macêdo, Bruno da Silva, Wayo, Dennis Delali Kwesi, Campos, Deivid, De Santis, Rodrigo Barbosa, Martinho, Alfeu Dias, Yaseen, Zaher Mundher, Saporetti, Camila M., Goliatt, Leonardo
Format: Article
Language:English
Published: Nature Publishing Group 2025
Subjects:
QA75 Electronic computers. Computer science
TD Environmental technology. Sanitary engineering
TP Chemical technology
Online Access:http://umpir.ump.edu.my/id/eprint/45116/
http://umpir.ump.edu.my/id/eprint/45116/1/Data-driven%20total%20organic%20carbon%20prediction%20using%20feature%20selection.pdf

Internet

http://umpir.ump.edu.my/id/eprint/45116/
http://umpir.ump.edu.my/id/eprint/45116/1/Data-driven%20total%20organic%20carbon%20prediction%20using%20feature%20selection.pdf

Similar Items