Petrophysical log-driven kerogen typing: unveiling the potential of hybrid machine learning
Abstract The importance of characterizing kerogen type in evaluating source rock and the nature of hydrocarbon yield is emphasized. However, traditional laboratory geochemical assessments can be time-intensive and costly. In this study, an innovative approach was taken to bridge this gap by utilizin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-08-01
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| Series: | Journal of Petroleum Exploration and Production Technology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13202-023-01688-1 |