Asset Details
Do you wish to reserve the book?
Effect of organic macerals on hydrocarbon generation ability of oil shale and coal and establishment of a contribution model – constraints from machine learning
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Effect of organic macerals on hydrocarbon generation ability of oil shale and coal and establishment of a contribution model – constraints from machine learning
Do you wish to request the book?
Effect of organic macerals on hydrocarbon generation ability of oil shale and coal and establishment of a contribution model – constraints from machine learning
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Effect of organic macerals on hydrocarbon generation ability of oil shale and coal and establishment of a contribution model – constraints from machine learning
2026
Overview
To quantify the impact of organic macerals on hydrocarbon generation in oil shale and coal, this study analyzed 403 datasets. The results show distinct differences in maceral composition between the two materials. Using a random forest model with aquatic liptinite, terrigenous liptinite, vitrinite, and inertinite as inputs, TOC and HI predictions achieved R² values of 0.62 and 0.73, respectively. SHAP analysis reveals that aquatic liptinite is the dominant positive contributor to both parameters, while terrigenous liptinite shows a bidirectional effect. Based on these relationships, a quantitative contribution model for organic macerals in oil shale is established, offering insights for resource evaluation and exploration.
Publisher
Estonian Academy Publishers
Subject
