Xiaofei Sun

Dr. Xiaofei Sun

School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 March 2017 in Energies
Verified
Journal Article
Open access
PDF file
Xiaofei SunXiaofei Sun
Xiaofei Sun
Yanyu ZhangYanyu Zhang
Yanyu Zhang
GCGuangpeng Chen
Guangpeng Chen
ZGZhiyong Gai
Zhiyong Gai
The injected fluids in secondary processes supplement the natural energy present in the reservoir to displace oil. The recovery efficiency mainly depends on the mechanism of pressure maintenance. However, the injected fluids in tertiary or enhanced oil recovery (EOR) processes interact with the reservoir rock/oil system. Thus, EOR techniques are receiving substantial attention worldwide as the available oil resources are declining. However, some challenges, such as low sweep efficiency, high costs and potential formation damage, still hinder the further application of these EOR technologies. Current studies on nanoparticles are seen as potential solutions to most of the challenges associated with these traditional EOR techniques. This paper provides an overview of the latest studies about the use of nanoparticles to enhance oil recovery and paves the way for researchers who are interested in the integration of these progresses. The first part of this paper addresses studies about the major EOR mechanisms of nanoparticles used in the forms of nanofluids, nanoemulsions and nanocatalysts, including disjoining pressure, viscosity increase of injection fluids, preventing asphaltene precipitation, wettability alteration and interfacial tension reduction. This part is followed by a review of the most important research regarding various novel nano-assisted EOR methods where nanoparticles are used to target various existing thermal, chemical and gas methods. Finally, this review identifies the challenges and opportunities for future study regarding application of nanoparticles in EOR processes.

1 January 2023
Verified
Conference Paper
Open access
PDF file
Xiaofei SunXiaofei Sun
Xiaofei Sun
XLXiaoya Li
Xiaoya Li
JLJiwei Li
Jiwei Li
FWFei Wu
Fei Wu
SGShangwei Guo
Shangwei Guo
GWGuoyin Wang
Guoyin Wang
Xiaofei Sun, Xiaoya Li, Jiwei Li, Fei Wu, Shangwei Guo, Tianwei Zhang, Guoyin Wang. Findings of the Association for Computational Linguistics: EMNLP 2023. 2023.

14 May 2020 in Petroleum Science
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Journal Article
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Xiaofei SunXiaofei Sun
Xiaofei Sun
ZSZhao-Yao Song
Zhao-Yao Song
LCLin-Feng Cai
Lin-Feng Cai
YZYan-Yu Zhang
Yan-Yu Zhang
PLPeng Li
Peng Li
A novel experimental procedure was proposed to investigate the phase behavior of a solvent mixture (SM) (64 mol% CH4, 8 mol% CO2, and 28 mol% C3H8) with heavy oil. Then, a theoretical methodology was employed to estimate the phase behavior of the heavy oil–solvent mixture (HO–SM) systems with various mole fractions of SM. The experimental results show that as the mole fraction of SM increases, the saturation pressures and swelling factors of the HO–SM systems considerably increase, and the viscosities and densities of the HO–SM systems decrease. The heavy oil is upgraded in situ via asphaltene precipitation and SM dissolution. Therefore, the solvent-enriched oil phase at the top layer of reservoirs can easily be produced from the reservoir. The aforementioned results indicate that the SM has promising application potential for enhanced heavy oil recovery via solvent-based processes. The theoretical methodology can accurately predict the saturation pressures, swelling factors, and densities of HO–SM systems with various mole fractions of SM, with average error percentages of 1.77% for saturation pressures, 0.07% for swelling factors, and 0.07% for densities.

25 September 2018 in Energy & Fuels
Verified
Journal Article
Closed access
Xiaofei SunXiaofei Sun
Xiaofei Sun
YZYanyu Zhang
Yanyu Zhang
GCGuangpeng Chen
Guangpeng Chen
TLTailin Liu
Tailin Liu
DRDounan Ren
Dounan Ren
SKSabrina Karwani
Sabrina Karwani

22 August 2023 in Resources Policy
Verified
Journal Article
Closed access
LPLijun Pan
Lijun Pan
YWYangjie Wang
Yangjie Wang
Xiaofei SunXiaofei Sun
Xiaofei Sun
MSMuhammad Sadiq
Muhammad Sadiq
Abd Alwahed DagestaniAbd Alwahed Dagestani
Abd Alwahed Dagestani

1 January 2021
Verified
Conference Paper
Open access
PDF file
CFChun Fan
Chun Fan
JLJiwei Li
Jiwei Li
TZTianwei Zhang
Tianwei Zhang
XAXiang Ao
Xiang Ao
FWFei Wu
Fei Wu
Xiaofei SunXiaofei Sun
Xiaofei Sun
Chun Fan, Jiwei Li, Tianwei Zhang, Xiang Ao, Fei Wu, Yuxian Meng, Xiaofei Sun. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 2021.