دورية أكاديمية
A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model
| العنوان: | A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model |
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| المؤلفون: | Yunsheng WEI, Junlei WANG, Wei YU, Yadong QI, Jijun MIAO, He YUAN, Chuxi LIU |
| المصدر: | Petroleum Exploration and Development, Vol 48, Iss 4, Pp 911-922 (2021) |
| بيانات النشر: | KeAi Communications Co., Ltd., 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | fractal discrete fracture network, multiplicative cascade process, embedded discrete fracture model, intelligent history matching, reservoir parameter inversion, shale gas, Petroleum refining. Petroleum products, TP690-692.5 |
| الوصف: | The generation method of three-dimensional fractal discrete fracture network (FDFN) based on multiplicative cascade process was developed. The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model. Based on an assisted history matching (AHM) using multiple-proxy-based Markov chain Monte Carlo algorithm (MCMC), an embedded discrete fracture modeling (EDFM) incorporated with reservoir simulator was used to predict productivity of shale gas well. When using the natural fracture generation method, the distribution of natural fracture network can be controlled by fractal parameters, and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different- scale fractures in shale after fracturing. The EDFM, with fewer grids and less computation time consumption, can characterize the attributes of natural fractures and artificial fractures flexibly, and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly. The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters, and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells. Application demonstrates the results from the proposed productivity prediction model integrating FDFN, EDFM and AHM have high credibility. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English Chinese |
| تدمد: | 1876-3804 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S1876380421600769; https://doaj.org/toc/1876-3804 |
| DOI: | 10.1016/S1876-3804(21)60076-9 |
| URL الوصول: | https://doaj.org/article/40f0f5bc589345afb795b7e641cfe4be |
| رقم الأكسشن: | edsdoj.40f0f5bc589345afb795b7e641cfe4be |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 18763804 |
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| DOI: | 10.1016/S1876-3804(21)60076-9 |