Oil Saturation Estimation With the Shale Oil Geochemical Mud Logging for the Liu 2 Member of the Weixi South Sag
In shale oil exploration and development, oil saturation is a key parameter for evaluating shale oil resources. But current methods for calculating shale oil saturation mainly rely on experimental evaluation, with few studies using logging data. This paper proposes a shale oil saturation calculation...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Well Logging Technology
2025-04-01
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| Series: | Cejing jishu |
| Subjects: | |
| Online Access: | https://www.cnpcwlt.com/en/#/digest?ArticleID=5721 |
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| Summary: | In shale oil exploration and development, oil saturation is a key parameter for evaluating shale oil resources. But current methods for calculating shale oil saturation mainly rely on experimental evaluation, with few studies using logging data. This paper proposes a shale oil saturation calculation method based on geochemical logging data, using nuclear magnetic resonance (NMR) experiments and closed pyrolysis logging. Through multi-state NMR experiments, an NMR fluid component chart for the Weixi south sag is constructed, and NMR saturation is calculated using the fluid volume method. Meanwhile, movable oil content and total oil content are obtained via closed pyrolysis experiments. Combining these experimental results with parameters like rock density and total porosity, an improved closed pyrolysis logging saturation model based on NMR technology is developed. In practical application, considering possible hydrocarbon loss during on-site geochemical logging, a lost hydrocarbon correction model is built using closed pyrolysis logging data. This forms an evaluation method for calculating shale oil saturation based on geochemical logging data. Results from a case study show that the absolute errors for movable oil saturation and oil saturation are 3.82% and 8.81%, respectively, with calculation ranges of 11%～46% and 30%～91%. This method offers a new approach for evaluating shale reservoir saturation using logging data. |
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| ISSN: | 1004-1338 |