Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery

doi:10.1016/j.cjche.2025.05.005

Chinese Journal of Chemical Engineering ›› 2025, Vol. 87 ›› Issue (11): 19-34.DOI: 10.1016/j.cjche.2025.05.005

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Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery

Zhihong Chen¹, Jiawei Wu¹, Wei Zhang¹, Wenjing Zhang², Xiaoling Lou¹, Junxian Yun²

1. State Key Laboratory of Green Chemistry Synthesis and Conversion Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China;
2. State Key Laboratory of Advanced Separation Membrane Materials, Zhejiang Key Laboratory of Surface and Interface Science and Engineering for Catalysts, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

Received:2025-03-10 Revised:2025-05-16 Accepted:2025-05-19 Online:2025-05-24 Published:2025-11-28
Contact: Wei Zhang,E-mail:zhangwei@zjut.edu.cn;Junxian Yun,E-mail:yunjx@zjut.edu.cn
Supported by:
The authors gratefully acknowledge the financial supports partially by the National Natural Science Foundation of China (22078296, 21576240) and the Zhejiang Provincial Natural Science Foundation of China (LD21B060001).

Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery

Zhihong Chen¹, Jiawei Wu¹, Wei Zhang¹, Wenjing Zhang², Xiaoling Lou¹, Junxian Yun²

1. State Key Laboratory of Green Chemistry Synthesis and Conversion Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China;
2. State Key Laboratory of Advanced Separation Membrane Materials, Zhejiang Key Laboratory of Surface and Interface Science and Engineering for Catalysts, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

通讯作者: Wei Zhang,E-mail:zhangwei@zjut.edu.cn;Junxian Yun,E-mail:yunjx@zjut.edu.cn
基金资助:
The authors gratefully acknowledge the financial supports partially by the National Natural Science Foundation of China (22078296, 21576240) and the Zhejiang Provincial Natural Science Foundation of China (LD21B060001).

Abstract

Abstract: The displacement of residual crude oil and enhanced oil recovery from reservoirs of mature oil fields are challenging worldwide and have received intensive attentions in oil and gas industry. In this work, a novel method for enhanced oil recovery by displacement of oil with bionanofluids was proposed. Micro-displacement hydrodynamics of crude oil in microchannel sand-packed porous media by the bionanofluid were investigated by high-speed imaging. The machine learning models with the extreme gradient boosting (XGBoost) algorithm was developed for the prediction of residual oil saturation during the micro-displacement processes. The residual oil droplets within the porous media after the waterflooding were effectively removed through bionanofluid-flooding, resulting in additional enhanced oil recovery of 39.0%, which is double the recovery achieved by waterflooding at the same displacement velocity. By wavelet-transform image enhancement and the XGBoost algorithm in the machine learning, the residual oil saturations along the porous media were predicted accurately with the mean squared errors of 0.0045 and 0.0030 in the waterflooding and the bionanofluid-flooding, respectively. The results indicated that the machine learning is effective in characterizing the displacement behaviors and the bionanofluid-flooding could be an interesting approach, and thus has potential applications in enhanced oil recovery of waterflooding reservoirs.

Key words: Microchannels, Two-phase flow, Biotechnology, Bionanofluid, Enhanced oil recovery, Machine learning

摘要： The displacement of residual crude oil and enhanced oil recovery from reservoirs of mature oil fields are challenging worldwide and have received intensive attentions in oil and gas industry. In this work, a novel method for enhanced oil recovery by displacement of oil with bionanofluids was proposed. Micro-displacement hydrodynamics of crude oil in microchannel sand-packed porous media by the bionanofluid were investigated by high-speed imaging. The machine learning models with the extreme gradient boosting (XGBoost) algorithm was developed for the prediction of residual oil saturation during the micro-displacement processes. The residual oil droplets within the porous media after the waterflooding were effectively removed through bionanofluid-flooding, resulting in additional enhanced oil recovery of 39.0%, which is double the recovery achieved by waterflooding at the same displacement velocity. By wavelet-transform image enhancement and the XGBoost algorithm in the machine learning, the residual oil saturations along the porous media were predicted accurately with the mean squared errors of 0.0045 and 0.0030 in the waterflooding and the bionanofluid-flooding, respectively. The results indicated that the machine learning is effective in characterizing the displacement behaviors and the bionanofluid-flooding could be an interesting approach, and thus has potential applications in enhanced oil recovery of waterflooding reservoirs.

关键词: Microchannels, Two-phase flow, Biotechnology, Bionanofluid, Enhanced oil recovery, Machine learning

Zhihong Chen, Jiawei Wu, Wei Zhang, Wenjing Zhang, Xiaoling Lou, Junxian Yun. Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery[J]. Chinese Journal of Chemical Engineering, 2025, 87(11): 19-34.

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Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery

Machine learning-assisted characterization of oil micro-displacement hydrodynamics by bionanofluid-flooding in microchannel sand-packed porous media towards enhanced oil recovery

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