Permeability Evaluation Method for Marine Low Porosity and Permeability Sandstone Based on Improved Electrical Imaging Porosity Spectrum
The reservoirs of Enping and Wenchang formation in Lufeng sag, Pearl River Mouth basin are mainly low porosity and low permeability sandstone reservoirs, with strong heterogeneity and complex pore structures. The permeability calculated by conventional methods is difficult to meet the actual needs o...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Well Logging Technology
2023-12-01
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| Series: | Cejing jishu |
| Subjects: | |
| Online Access: | https://www.cnpcwlt.com/#/digest?ArticleID=5549 |
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| Summary: | The reservoirs of Enping and Wenchang formation in Lufeng sag, Pearl River Mouth basin are mainly low porosity and low permeability sandstone reservoirs, with strong heterogeneity and complex pore structures. The permeability calculated by conventional methods is difficult to meet the actual needs of exploration and development, while the vertical resolution of nuclear magnetic logging is low, which makes it difficult to effectively identify high-quality thin layer. In response to the above issues, the author chose electrical imaging logging with higher vertical resolution, based on core experiment and forward modeling, after deeply analyzes the reasons for the shortcomings of traditional porosity spectrum in characterizing the rock pore structure, the author innovatively proposed a method for constructing porosity spectrum based on pore volume statistics. By comparing with core nuclear magnetic resonance T2 spectrum, the improved porosity spectrum can truly reflect the characteristics of reservoir pore structure. On this basis, referring to the SDR permeability calculation formula of nuclear magnetic logging, a permeability calculation model based on improved porosity spectrum is constructed. The actual well evaluation results show that the relative error of permeability calculation is reduced by 77.3% compared to conventional pore permeability methods, and it can more effectively identify high-quality thin sand layers, which can provide reliable basic data for fine reservoir description and productivity prediction. |
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| ISSN: | 1004-1338 |