Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques
Abstract This study uses advanced deep learning techniques to present an efficient and data-driven method for predicting the Hydrocarbon Reservoir Quality Index (HRQI) in deepwater carbonate systems. Traditional approaches like core sampling and Nuclear Magnetic Resonance logging are often costly an...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
|
| Series: | Geomechanics and Geophysics for Geo-Energy and Geo-Resources |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40948-025-01030-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|