Percolation Model for Permeability Reduction in Porous Media by Continuous-Gas Foams

2000 ◽  
Vol 39 (8) ◽  
pp. 2709-2716 ◽  
Author(s):  
Randy D. Hazlett ◽  
Mary J. Furr
2016 ◽  
Vol 43 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Pingkang Wang ◽  
Xuhui Zhang ◽  
Xiaobing Lu ◽  
Wei Zheng ◽  
Qingjie Liu

2013 ◽  
Author(s):  
M. Khederzadeh ◽  
S. Ostadrezaei ◽  
Iran R. Kharrat ◽  
H. Bagherzadeh ◽  
S. Mahdavi ◽  
...  

SPE Journal ◽  
2021 ◽  
pp. 1-14
Author(s):  
Xin Su ◽  
Rouzbeh G. Moghanloo ◽  
Minhui Qi ◽  
Xiang-an Yue

Summary Formation damage mechanisms in general lower the quality of the near wellbore, often manifested in the form of permeability reduction, and thus reducing the productivity of production wells and injectivity of injection wells. Asphaltene deposition, as one of the important causes, can trigger serious formation damage issues and significantly restrict the production capacity of oil wells. Several mechanisms acting simultaneously contribute to the complexity associated with prediction of permeability impairment owing to asphaltene deposition; thus, integration of modeling efforts for asphaltene aggregation and deposition mechanisms seems inevitable for improved predictability. In this work, an integrated simulation approach is proposed to predict permeability impairment in porous medium. The proposed approach is novel because it integrates various mathematical models to study permeability impairment considering porosity reduction, particle aggregation, and pore connectivity loss caused by asphaltene deposition. To improve the accuracy of simulation results, porous media is considered as a bundle (different size) of capillary tubes with dynamic interconnectivity. The total volume change of interconnected tubes will directly represent permeability reduction realized in porous media. The prediction of asphaltene deposition in porous media is improved in this paper via integration of the particle aggregation model into calculation. The simulation results were verified by comparing with existing experimental data sets. After that, a sensitivity analysis was performed to study parameters that affect permeability impairment. The simulation results show that our permeability impairment model—considering asphaltene deposition, aggregation, and pore connectivity loss—can accurately reproduce the experimental results with fewer fitting or empirical parameters needed. The sensitivity analysis shows that longer aggregation time, higher flow velocity, and bigger precipitation concentration will lead to a faster permeability reduction. The findings of this study can help provide better understanding of the permeability impairment caused by asphaltene deposition and pore blockage, which provides useful insights for prediction of production performance of oil wells.


2020 ◽  
Author(s):  
Giuseppe Maddinelli ◽  
Martin Bartosek ◽  
Stefano Carminati ◽  
Leili Moghadasi ◽  
Nicolò Manfredini ◽  
...  

2008 ◽  
Vol 48 (1) ◽  
pp. 21
Author(s):  
Changhong Gao

Capture of emulsion droplets in porous media can be costly or beneficial. When produced water is injected into reservoir for pressure maintenance, the oil droplets in produced water can plug reservoir rocks and cause the well to lose injectivity. Enhanced oil recovery (EOR) technology takes advantage of this feature and plugs high-injectivity zones with emulsions. Previous studies reveal that interception and straining are the mechanisms of permeability decline. Established models rely on filtration data to determine key parameters. In this work, a network model is proposed to simulate capture of oil droplets in reservoir rocks and resultant permeability reduction. The model is validated with test data and reasonably good results are obtained. The simulation also reveals that the wettability of the tested porous media was altered by injection of emulsions. The new approach considers the characteristics of the porous media and incorporates the damage mechanisms, thus providing more scientific insights into the flow and capture of droplets in porous media.


Fuel ◽  
2008 ◽  
Vol 87 (10-11) ◽  
pp. 2178-2185 ◽  
Author(s):  
R. Hamadou ◽  
M. Khodja ◽  
M. Kartout ◽  
A. Jada

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