A Nondestructive Alternative for Kerogen Type Determination in Potential Hydrocarbon Source Rocks Using Hyperspectral Data and Machine Learning

A Nondestructive Alternative for Kerogen Type Determination in Potential Hydrocarbon Source Rocks Using Hyperspectral Data and Machine Learning

In petroleum geology, to assess the hydrocarbon generation potential in source rocks involves the determination of the kerogen type by some destructive method. The usage of such methods is a bottleneck in the process because it is time-consuming, requires specialized tools and personnel, and ends up...

Full description

Bibliographic Details
Main Authors: Taina T. Guimaraes, Lucas S. Kupssinsku, Milena B. Cardoso, Leonardo Bachi, Alysson S. Aires, Emilie C. Koste, Andre L. D. Spigolon, Luiz Gonzaga, Mauricio R. Veronez
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Classification
hydrocarbon source rock
hyperspectral
kerogen type
machine learning (ML)
Online Access:https://ieeexplore.ieee.org/document/9844790/

Internet

https://ieeexplore.ieee.org/document/9844790/

Similar Items