Work

The reservoir screening standard of CO2 huff-n-puff based on orthogonal analysis method and random forest algorithm

Year: 2024

Type: article

Abstract: In heavy oil reservoirs, favorable reservoir properties have a positive impact on the production performance during CO 2 huff-n-puff. It is significant to study the screening method of applicable conditions for CO 2 huff-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 CO 2 huff-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 CO 2 huff-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 CO 2 huff-n-puff considering different reservoir geological parameters. This method increased the accuracy and efficiency in screening reservoir conditions that was suitable for CO 2 huff-n-puff.

Source: Journal of Petroleum Exploration and Production Technology

DOI: 10.1007/s13202-024-01879-4