| Autor: |
Wang, Xiaoyan, Li, Dongping, Zhang, Yang, Wang, Haifeng, Liu, Shuangfeng, Li, Lingling, Pang, Zhanxi |
| Zdroj: |
Journal of Petroleum Exploration and Production Technologies; November 2024, Vol. 14 Issue: 11 p3111-3123, 13p |
| Abstrakt: |
In heavy oil reservoirs, favorable reservoir properties have a positive impact on the production performance during CO2huff-n-puff. It is significant to study the screening method of applicable conditions for CO2huff-n-puff in actual reservoirs. To solve these problems, this paper introduced the orthogonal design method to analyze the main factors based on numerical simulation. The technical analysis and the economic evaluation were both employed to obtain the applicable conditions of selecting oil layers or injection wells during CO2huff-n-puff. And a new algorithms of machine learning, the random forest algorithm, was introduce to find the weighted factors and the scoring standards that were suitable for CO2huff-n-puff. Finally, a set of method for screening suitable reservoir conditions was established. Based on the introduction of orthogonal analysis method and random forest algorithm, a software was established to achieve the purpose of analyzing the feasibility of CO2huff-n-puff considering different reservoir geological parameters. This method increased the accuracy and efficiency in screening reservoir conditions that was suitable for CO2huff-n-puff. |
| Databáze: |
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