Applicability of Machine Learning and Mathematical Equations to the Prediction of Total Organic Carbon in Cambrian Shale, Sichuan Basin, China
Accurate Total Organic Carbon (TOC) prediction in the deeply buried Lower Cambrian Qiongzhusi Formation shale is constrained by extreme heterogeneity (TOC variability: 0.5–12 wt.%, mineral composition Coefficient of Variation > 40%) and ambiguous geophysical responses. This study introduces three...
Saved in:
| Main Authors: | Majia Zheng, Meng Zhao, Ya Wu, Kangjun Chen, Jiwei Zheng, Xianglu Tang, Dadong Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/9/4957 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Slope Belts of Paleouplifts Control the Pore Structure of Organic Matter of Marine Shale: A Comparative Study of Lower Cambrian Rocks in the Sichuan Basin
by: Pengfei Wang, et al.
Published: (2021-01-01) -
Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models
by: Guoli Huang, et al.
Published: (2025-06-01) -
Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province
by: Yao Zhang, et al.
Published: (2025-07-01) -
Experimental evaluation of an environmentally friendly drilling fluid for clay stabilization in shale formations
by: Ali Momeni, et al.
Published: (2025-08-01) -
Influence of Lamina Types and Combinations of Deep Marine Shale on Reservoir Quality in Zigong Block of Southern Sichuan Basin
by: Xiangyang Pei, et al.
Published: (2024-11-01)