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A hybrid embedded discrete fracture model for simulating tight porous media with complex fracture systems

Journal Article · · Journal of Petroleum Science and Engineering
 [1];  [1];  [2]
  1. China Univ. of Petroleum, Qingdao (China). School of Petroleum Engineering
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Computational Earth Science Group

Numerical simulation considering complex fracture networks in tight oil reservoir becomes a hot issue during these years. Recently, embedded discrete fracture model (EDFM) shows great advantages over the DFM approaches in both calculation efficiency and simplicity of simulation workflow. EDFM has been widely used in tight oil/gas natural energy or enhanced oil recovery (EOR) development. If a large number of small-scale natural fractures exist in reservoir, the calculation efficiency of EDFM method may decrease. A new hybrid simulation model combining the EDFM and dual porosity (DP) model is proposed. The large-scale fractures are dealt with EDFM method while small scale fractures are dealt with DP model. Considering the low permeability of matrix, transient transfer between matrix and natural fracture is considered. The proposed hybrid model is validated compared with the local grid refinement (LGR) model and EDFM-MINC model, and the difference between transient transfer and pseudo-steady-state transfer effect on production is presented. Finally, two test cases are presented, and the sensitivity of some key parameters are investigated. Result shows that the new simulation model has higher calculation efficiency than LGR and EDFM-MINC models. Meanwhile, it honors a good accuracy. The pseudo-steady-state transfer between matrix and natural fracture leads to big error in tight oil production performance analysis both in single phase and two phases flow. Low matrix permeability and big matrix size increase the production difference between pseudo-steady-state transfer and transient transfer models. The proposed model can simulate reservoirs considering stochastic permeability distribution.

Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); China Univ. of Petroleum, Qingdao (China)
Sponsoring Organization:
USDOE; National Natural Science Foundation of China (NSFC); Natural Science Foundation of Shandong Province (China); China Univ. of Petroleum; Fundamental Research Funds for the Central University (China)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1503192
Report Number(s):
LA-UR--18-30867
Journal Information:
Journal of Petroleum Science and Engineering, Journal Name: Journal of Petroleum Science and Engineering Vol. 174; ISSN 0920-4105
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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