Mechanisms of asphaltene deposition and formation damage during CO2 flooding at the reservoir scale

沉积(地质) 磁导率 沥青质 多孔性 多孔介质 石油工程 化学工程 相对渗透率 分数(化学) 降水 摩尔分数 土壤科学 体积流量
作者
Shun Chen,Pingchuan Dong,Youheng Zhang,Lili Li
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:38 (5)
标识
DOI:10.1063/5.0332781
摘要

During CO2 flooding in deep reservoirs, changes in reservoir fluid properties may induce asphaltene precipitation and deposition, leading to porosity–permeability impairment. While most previous studies rely on core-scale experiments or digital rock simulations, reservoir-scale investigations of deposition distribution and associated damage remain limited. In this work, a reservoir-scale CO2 flooding model coupled with asphaltene deposition was developed using actual temperature–pressure conditions and calibrated fluid properties from a deep reservoir. The model was validated against the analytical solution of infinite-acting radial flow. The effects of reservoir heterogeneity, CO2 mole fraction, injection rate, formation permeability, and well pattern on CO2 storage, deposition rate, and porosity–permeability damage were systematically analyzed. Results show that increasing the CO2 mole fraction from 0.2 to 0.8 increases the deposition rate by 19.56%, accompanied by porosity and permeability damage increments of 29.69% and 46.91%, respectively. Increasing the injection rate from 2 × 104 to 8 × 104 m3/day reduces the deposition rate by 16.83% and significantly mitigates formation damage. Higher formation permeability also suppresses deposition and associated impairment. The inverted nine-spot well pattern provides the highest CO2 storage and the lowest damage. Gray relational analysis indicates that formation permeability most strongly controls deposition rate, whereas well pattern dominates storage efficiency and formation impairment. These results clarify the coupled mechanisms of CO2 storage and asphaltene-induced damage in deep reservoirs.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
奇怪发布了新的文献求助10
1秒前
田様应助hj木秀于林采纳,获得10
1秒前
1秒前
1秒前
灰原发布了新的文献求助10
2秒前
大模型应助xingyong采纳,获得10
2秒前
2秒前
卓延恶完成签到,获得积分10
2秒前
pathway发布了新的文献求助10
2秒前
倪倪发布了新的文献求助10
2秒前
李健应助小汉文采纳,获得10
3秒前
3秒前
3秒前
啦啦啦完成签到,获得积分10
4秒前
李健的小迷弟应助敏静采纳,获得10
4秒前
4秒前
学习完成签到,获得积分10
4秒前
JamesPei应助伶俐的老黑采纳,获得10
5秒前
八九发布了新的文献求助10
5秒前
guohuameike完成签到,获得积分10
5秒前
明亮寻绿发布了新的文献求助10
6秒前
深情安青应助朱琳采纳,获得10
6秒前
6秒前
混个毕业发布了新的文献求助10
6秒前
刘泽丰完成签到,获得积分10
7秒前
磊磊磊发布了新的文献求助10
8秒前
英吉利25发布了新的文献求助10
8秒前
8秒前
8秒前
忧虑的胜发布了新的文献求助10
9秒前
Jasper应助YOLO采纳,获得10
9秒前
可知完成签到,获得积分10
9秒前
9秒前
大梦想家发布了新的文献求助10
10秒前
李兴雅发布了新的文献求助10
10秒前
11秒前
思源应助Leo采纳,获得30
11秒前
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7623131
求助须知:如何正确求助?哪些是违规求助? 9198534
关于积分的说明 19719102
捐赠科研通 7194465
什么是DOI,文献DOI怎么找? 3273138
关于科研通互助平台的介绍 2435521
邀请新用户注册赠送积分活动 2268720