A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model
| Autor: | Wei Yu, Jijun Miao, He Yuan, Yadong Qi, Yunsheng Wei, Junlei Wang, Chuxi Liu |
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| Rok vydání: | 2021 |
| Předmět: |
Scale (ratio)
Petroleum engineering fractal discrete fracture network Computation intelligent history matching shale gas Energy Engineering and Power Technology Geology Markov chain Monte Carlo Geotechnical Engineering and Engineering Geology embedded discrete fracture model symbols.namesake reservoir parameter inversion Fractal Geochemistry and Petrology Fracture (geology) symbols Economic Geology multiplicative cascade process Petroleum refining. Petroleum products Multiplicative cascade Oil shale TP690-692.5 Network model |
| Zdroj: | Petroleum Exploration and Development, Vol 48, Iss 4, Pp 911-922 (2021) |
| ISSN: | 1876-3804 |
| DOI: | 10.1016/s1876-3804(21)60076-9 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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