Special Oil & Gas Reservoirs ›› 2022, Vol. 29 ›› Issue (2): 110-114.DOI: 10.3969/j.issn.1006-6535.2022.02.016

• Reservoir Engineering • Previous Articles     Next Articles

Numerical Modeling Method of Low-permeability Reservoir Based on Stress Sensitivity and Matrix Shrinkage Effect and Its Application

Wan Xiaolong1,2, Wang Siyi1,2, Guo Xifeng1,2, Lan Zhengkai3,4   

  1. 1. PetroChina Changqing Oilfield Company, Xi′an, Shaanxi 710018, China;
    2. National Engineering Laboratory of Low-permeability Oil & Gas Exploration and Development, Xi′an, Shaanxi 710018, China;
    3. China University of Geosciences (Wuhan), Wuhan, Hubei 430000, China;
    4. Nanjing Tracy Energy Technology Co., Ltd., Nanjing, Jiangsu 210000, China
  • Received:2021-04-14 Revised:2021-12-31 Online:2022-04-25 Published:2023-01-10

Abstract: In low-permeability reservoirs, stress sensitivity effect is often considered while matrix pore shrinkage effect is ignored, resulting in great errors in the evaluation results of reservoir permeability and productivity. To address the above problems, a mathematical model considering the effects of both stress sensitivity and matrix shrinkage was established with reservoir engineering methods, to explore its feasibility in predicting production performance in the Ansai Oilfield, in combination with a permeability evolution model based on fractal theory. The study showed that under the effective stress below 5 MPa, if the matrix shrinkage effect was ignored, the reservoir permeability was underestimated, which affected the later adjustment of the development plan; the theoretical model established in this paper matched the actual production data by 92%, indicating that the model can better predict the production performance of oil wells in the study area. The study results can be used as an important reference for the late tapping potential and adjustment of similar low-permeability reservoirs in Changqing Oilfield.

Key words: low-permeability reservoir, shrinkage effect, stress sensitivity, pore size, numerical modeling, Ansai Oilfield

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