Characteristics and mechanisms of supercritical CO2 flooding under different factors in low-permeability reservoirs

Chen, Zheng; Su, Yuliang; Li, Lei; Meng, Fankun; Zhou, Xiaomei

doi:10.1016/j.petsci.2022.01.016

Cited by 42 publications

(16 citation statements)

References 52 publications

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“…(2) water injection rate of 79 m 3 /day and CO 2 injection rate of 16,000 m 3 /day; (3) water injection rate of 90 m 3 /day and CO 2 injection rate of 20,000 m 3 /day; (4) water injection rate of 100 m 3 /day and CO 2 injection rate of 23,000 m 3 /day; (5) water injection rate of 110 m 3 /day and CO 2 injection rate of 27,000 m 3 /day; (6) water injection rate 120 m 3 /day and CO 2 injection rate of 31,000 m 3 /day. 6 schemes of the water-gas ratio adjustment are set as 0.33, 0.5, 1, 1.5, 2, and 3, respectively.…”

Section: Analysis Of Influence Factors On Co 2 -Wagmentioning

confidence: 99%

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Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Gong

Liu

et al. 2022

Applied Sciences

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In recent years, CO2 flooding has emerged as an efficient method for improving oil recovery. It also has the advantage of storing CO2 underground. As one of the promising types of CO2 enhanced oil recovery (CO2-EOR), CO2 water-alternating-gas injection (CO2-WAG) can suppress CO2 fingering and early breakthrough problems that occur during oil recovery by CO2 flooding. However, the evaluation of CO2-WAG is strongly dependent on the injection parameters, which in turn renders numerical simulations computationally expensive. So, in this work, machine learning is used to help predict how well CO2-WAG will work when different injection parameters are used. A total of 216 models were built by using CMG numerical simulation software to represent CO2-WAG development scenarios of various injection parameters where 70% of them were used as training sets and 30% as testing sets. A random forest regression algorithm was used to predict CO2-WAG performance in terms of oil production, CO2 storage amount, and CO2 storage efficiency. The CO2-WAG period, CO2 injection rate, and water–gas ratio were chosen as the three main characteristics of injection parameters. The prediction results showed that the predicted value of the test set was very close to the true value. The average absolute prediction deviations of cumulative oil production, CO2 storage amount, and CO2 storage efficiency were 1.10%, 3.04%, and 2.24%, respectively. Furthermore, it only takes about 10 s to predict the results of all 216 scenarios by using machine learning methods, while the CMG simulation method spends about 108 min. It demonstrated that the proposed machine-learning method can rapidly predict CO2-WAG performance with high accuracy and high computational efficiency under conditions of various injection parameters. This work gives more insights into the optimization of the injection parameters for CO2-EOR.

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Section: Analysis Of Influence Factors On Co 2 -Wagmentioning

confidence: 99%

“…This results in an unfavorable mobility ratio, which seriously affects the improvement of swept volume [5]. Moreover, due to its low density, CO 2 can easily escape to the upper part of the reservoir, forming a fugitive flow channel [6]. This also constitutes a drawback for CO 2 flooding as it leads to a reduction of the swept volume.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Gong

Liu

et al. 2022

Applied Sciences

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“…The researchers have been investigating ways to reduce or utilize CO 2 for various applications. − CO 2 injection is also considered environmentally conscious. Nevertheless, gas injection techniques for enhanced oil recovery (EOR) encounter several notable disadvantages, including permeability heterogeneity, viscous fingering, channeling, and gravity override. − These challenges reduce the sweep efficiency and accelerate the gas breakthrough.…”

Section: Introductionmentioning

confidence: 99%

Nanoparticle and Surfactant Stabilized Carbonated Water Induced In-Situ CO₂ Foam: An Improved Oil Recovery Approach

Halari,

Yadav,

Kesarwani

et al. 2024

Energy Fuels

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The enhanced oil recovery techniques are everevolving to cater to the need for increased oil demand. To improve the EOR efficiency, the new approach combines chemical additives such as nanoparticles and surfactants with carbonated water to address the issues of reduced mobility control, gravity segregation, and early breakout encountered in CO 2 flooding. The in situgenerated CO 2 foams are unstable structures depending upon additional additives to strengthen their lamella and improve their stability, which ZnO nanoparticles (NPs) provide in the current study. This research investigates the synergistic impact of sodium dodecyl sulfate (SDS) and ZnO NPs on the CO 2 foam generated from carbonated water. The carbonated water flooding tests were conducted using optimal SDS and ZnO concentrations of 2500 ppm and 0.01 wt %, respectively. The processes underlying the synergistic action of SDS and ZnO are altering nanoparticle adsorption sites on the CO 2 and liquid interface, enhancing the CO 2 foam's interfacial characteristics, and lowering its liquid discharge and coarsening. Further, four flooding procedures were utilized on two sandstone cores with contrasting petrophysical characteristics to study the effect of foam-assisted carbonated water flooding. The oil recovery was influenced and increased by SDS and ZnO NPs. The outcomes show that CO 2 foam flooding (nanoparticles included) generated using carbonated slug illustrates effective conformance control and enhances oil recovery from sandstone. It has been observed that nanosurfactant-added carbonated slug flooding gives a 50.00% and 194.72% recovery enhancement compared to regular carbonated water flooding for sandstone-1 and sandstone-2, respectively.

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“…With the continuous growth of global oil demand and the common goal of carbon peaking and carbon neutrality, CO 2 -enhanced oil recovery (CO 2 -IOR) and storage technologies have gradually become a primary or potential technology for oilfield development. − They not only take advantage of the characteristics of CO 2 to increase the mobility of crude oil to enhance oil recovery but also can store CO 2 , a greenhouse gas, in oil reservoirs, − that is, to use CO 2 to replace the crude oil in reservoir. − However, there are obvious differences in the mobility and density of CO 2 compared with fluids such as crude oil and formation water in oil reservoirs. − Therefore, in a short period, after CO 2 is injected into the reservoir, CO 2 usually escapes along the production well. , …”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation of Combined Plugging System for CO₂-Improved Oil Recovery and Storage

Chen

et al. 2023

Energy Fuels

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High-performance CO 2 -improved oil recovery (IOR) and storage technology is one of the most promising measures for global oilfield companies to achieve zero carbon targets. Due to the severe heterogeneity of most petroleum reservoirs and the significant density difference between CO 2 and reservoir fluid, the efficiency of CO 2 -IOR and storage is usually limited. In this paper, a hightemperature and high-pressure 30 cm core displacement experiment was used to study the CO 2 conformance control performance of both the single-and the combined plugging system in long sandstone cores. The single systems evaluated included polymer gels, CO 2 foams, and CO 2 -responsive thickening polymer (CO 2 -RTP) systems. The combined systems were pairwise combinations of the three of them. Results show that the pressure rise and maximum breakthrough pressure of the gel system were the highest among three single-plugging systems. Its plugging efficiency was the highest, reaching 86.13%. At the same time, its gas production reduction rate was also the highest, reaching 95.71%. In the parallel 30 cm core plugging experiments, three combined plugging systems all showed excellent plugging and CO 2 conformance improvement performance. Among them, the combined plugging systems containing polymer gels had larger plugging efficiency, and their gas production reduction ratios reached about 90%. Compared with single systems, the combined plugging systems had the advantages of easy injection and in-depth propagation, which can significantly improve CO 2 conformance and oil recovery. The research results of this study can provide the experimental understanding and theoretical guidance for the current tricky oilfield problems of CO 2 channeling.

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Characteristics and mechanisms of supercritical CO2 flooding under different factors in low-permeability reservoirs

Cited by 42 publications

References 52 publications

Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Nanoparticle and Surfactant Stabilized Carbonated Water Induced In-Situ CO₂ Foam: An Improved Oil Recovery Approach

Experimental Evaluation of Combined Plugging System for CO₂-Improved Oil Recovery and Storage

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Characteristics and mechanisms of supercritical CO2 flooding under different factors in low-permeability reservoirs

Cited by 42 publications

References 52 publications

Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)

Nanoparticle and Surfactant Stabilized Carbonated Water Induced In-Situ CO2 Foam: An Improved Oil Recovery Approach

Experimental Evaluation of Combined Plugging System for CO2-Improved Oil Recovery and Storage

Contact Info

Product

Resources

About

Nanoparticle and Surfactant Stabilized Carbonated Water Induced In-Situ CO₂ Foam: An Improved Oil Recovery Approach

Experimental Evaluation of Combined Plugging System for CO₂-Improved Oil Recovery and Storage