Quantitative identification of dominant seepage channels in streamline numerical simulation

Xin-liang Zhang

doi:10.1117/12.2639284

17 May 2022 Quantitative identification of dominant seepage channels in streamline numerical simulation

Xin-liang Zhang

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 1225906 (2022) https://doi.org/10.1117/12.2639284
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

Dominant seepage channels are formed after chemical flooding，lead to the low efficient and even non-efficient circulation of subsequent EOR methods，need quantitative identification. At present, dominant seepage channel identification methods are only judge whether there is dominant seepage channel in Wells, and cannot quantify the evolution process of dominant seepage channel between injection-production well pairs. In this paper, the streamline numerical simulation software is used to identify the dominant seepage channels quantitatively. Firstly, time-dependent and quantifiable fluid flow between wells, original permeability, water injection efficiency and water saturation were selected as the key parameters for characterization of dominant seepage channels. Secondly, the comprehensive identification mathematical model of dominant seepage channels is established and the weight of key parameters is given. Finally, the history of chemical flooding was accurately matched with the streamline numerical simulation software, and the key parameters are obtained. The distribution and evolution process of dominant seepage channels in chemical flooding process are given by comprehensive identification model. The results show that the calculated are high consistency with the injection profile of testing wells. This method can accurately identification the plugging layers of dominant seepage channels.

Citation Download Citation

Xin-liang Zhang "Quantitative identification of dominant seepage channels in streamline numerical simulation", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 1225906 (17 May 2022); https://doi.org/10.1117/12.2639284

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