Measurement Of The Diffusion Coefficient Of CO2 In Formation Water Under Reservoir Conditions: Implications For CO2 Storage

CO2 diffusion coefficient plays a crucial part in saline aquifers for the CO2 storage and the safety of long-term sequestration. Therefore, it is particularly important to measure the diffusion coefficient accurately. As far as we know, there are currently no CO2 brine diffusion data in real cores under reservoir temperature and pressure conditions. In this paper, a study on the CO2 diffusion coefficient diffused in a brine-saturated Berea core along the radial direction was conducted at temperatures of 313.15 K to 373.15 K and pressures of 8 MPa to 30 MPa. On account of the experimental results, the effect of permeability, NaCl concentration, temperature and pressure on the CO2 diffusivity is analyzed. The results in this study indicate that the diffusion coefficient increases with increasing permeability, pressure and temperature and decreases with increasing NaCl concentration. However, the relationship between pressure and the diffusion coefficient is not linear. As the pressure gradually increases, the effect of pressure will become weak. In addition, an empirical correlation of the relationship between temperature–pressure and the CO2 diffusion coefficient could be obtained based on the experimental data. The data in this paper fill the blank on the study of the CO2 diffusivity in brine under reservoir conditions, which has positive significance for the study of supercritical CO2 diffusion in a brine-saturated core.

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Experimental study of the supercritical CO 2 diffusion coefficient in porous media under reservoir conditions

Royal Society Open Science ◽

10.1098/rsos.181902 ◽

2019 ◽

Vol 6 (6) ◽

pp. 181902 ◽

Cited By ~ 1

Author(s):

Junchen Lv ◽

Yuan Chi ◽

Changzhong Zhao ◽

Yi Zhang ◽

Hailin Mu

Keyword(s):

Porous Media ◽

Diffusion Coefficient ◽

Oil Recovery ◽

Carbon Capture ◽

Carbon Capture And Storage ◽

Elevated Pressure ◽

Experimental Results ◽

Saturated Porous Media ◽

Reservoir Conditions ◽

The Impact

Reliable measurement of the CO 2 diffusion coefficient in consolidated oil-saturated porous media is critical for the design and performance of CO 2 -enhanced oil recovery (EOR) and carbon capture and storage (CCS) projects. A thorough experimental investigation of the supercritical CO 2 diffusion in n -decane-saturated Berea cores with permeabilities of 50 and 100 mD was conducted in this study at elevated pressure (10–25 MPa) and temperature (333.15–373.15 K), which simulated actual reservoir conditions. The supercritical CO 2 diffusion coefficients in the Berea cores were calculated by a model appropriate for diffusion in porous media based on Fick's Law. The results show that the supercritical CO 2 diffusion coefficient increases as the pressure, temperature and permeability increase. The supercritical CO 2 diffusion coefficient first increases slowly at 10 MPa and then grows significantly with increasing pressure. The impact of the pressure decreases at elevated temperature. The effect of permeability remains steady despite the temperature change during the experiments. The effect of gas state and porous media on the supercritical CO 2 diffusion coefficient was further discussed by comparing the results of this study with previous study. Based on the experimental results, an empirical correlation for supercritical CO 2 diffusion coefficient in n -decane-saturated porous media was developed. The experimental results contribute to the study of supercritical CO 2 diffusion in compact porous media.

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CO2 Convective Dissolution in Oil-Saturated Unconsolidated Porous Media at Reservoir Conditions

Energies ◽

10.3390/en14010233 ◽

2021 ◽

Vol 14 (1) ◽

pp. 233

Author(s):

Widuramina Amarasinghe ◽

Ingebret Fjelde ◽

Nils Giske ◽

Ying Guo

Keyword(s):

Porous Media ◽

Crude Oil ◽

Water Solution ◽

Co2 Storage ◽

Bromothymol Blue ◽

Power Relationship ◽

Dimensionless Time ◽

3 Dimensional ◽

Reservoir Conditions ◽

Unconsolidated Porous Media

During CO2 storage, CO2 plume mixes with the water and oil present at the reservoir, initiated by diffusion followed by a density gradient that leads to a convective flow. Studies are available where CO2 convective mixing have been studied in water phase but limited in oil phase. This study was conducted to reach this gap, and experiments were conducted in a vertically packed 3-dimensional column with oil-saturated unconsolidated porous media at 100 bar and 50 °C (representative of reservoir pressure and temperature conditions). N-Decane and crude oil were used as oils, and glass beads as porous media. A bromothymol blue water solution-filled sapphire cell connected at the bottom of the column was used to monitor the CO2 breakthrough. With the increase of the Rayleigh number, the CO2 transport rate in n-decane was found to increase as a function of a second order polynomial. Ra number vs. dimensionless time τ had a power relationship in the form of Ra = c×τ−n. The overall pressure decay was faster in n-decane compared to crude oil for similar permeability (4 D), and the crude oil had a breakthrough time three times slower than in n-decane. The results were compared with similar experiments that have been carried out using water.

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Role of "Formation Water" and Its Importance for Geochemical Trapping in an Open Aquifer CO2 Storage

Journal of Geography (Chigaku Zasshi) ◽

10.5026/jgeography.117.768 ◽

2008 ◽

Vol 117 (4) ◽

pp. 768-781 ◽

Cited By ~ 8

Author(s):

Yasuko OKUYAMA ◽

Munetake SASAKI ◽

Hirofumi MURAOKA ◽

Nobuyuki KANEKO ◽

Masao SORAI

Keyword(s):

Co2 Storage ◽

Formation Water

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A new prediction model of CO2 diffusion coefficient in crude oil under reservoir conditions based on BP neural network

Energy ◽

10.1016/j.energy.2021.122286 ◽

2021 ◽

pp. 122286

Author(s):

Hao Chen ◽

Yu Wang ◽

Mingsheng Zuo ◽

Chao Zhang ◽

Ninghong Jia ◽

...

Keyword(s):

Neural Network ◽

Diffusion Coefficient ◽

Prediction Model ◽

Crude Oil ◽

Bp Neural Network ◽

Co2 Diffusion ◽

Reservoir Conditions

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Estimation of CO2 Diffusivity in Brine by Use of the Genetic Algorithm and Mixed Kernels-Based Support Vector Machine Model

Journal of Energy Resources Technology ◽

10.1115/1.4041724 ◽

2018 ◽

Vol 141 (4) ◽

Cited By ~ 4

Author(s):

Qihong Feng ◽

Ronghao Cui ◽

Sen Wang ◽

Jin Zhang ◽

Zhe Jiang

Keyword(s):

Genetic Algorithm ◽

Support Vector Machine ◽

Diffusion Coefficient ◽

Co2 Storage ◽

Co2 Injection ◽

Support Vector ◽

Hybrid Technique ◽

Machine Model ◽

Proposed Model ◽

Wide Range

Diffusion coefficient of carbon dioxide (CO2), a significant parameter describing the mass transfer process, exerts a profound influence on the safety of CO2 storage in depleted reservoirs, saline aquifers, and marine ecosystems. However, experimental determination of diffusion coefficient in CO2-brine system is time-consuming and complex because the procedure requires sophisticated laboratory equipment and reasonable interpretation methods. To facilitate the acquisition of more accurate values, an intelligent model, termed MKSVM-GA, is developed using a hybrid technique of support vector machine (SVM), mixed kernels (MK), and genetic algorithm (GA). Confirmed by the statistical evaluation indicators, our proposed model exhibits excellent performance with high accuracy and strong robustness in a wide range of temperatures (273–473.15 K), pressures (0.1–49.3 MPa), and viscosities (0.139–1.950 mPa·s). Our results show that the proposed model is more applicable than the artificial neural network (ANN) model at this sample size, which is superior to four commonly used traditional empirical correlations. The technique presented in this study can provide a fast and precise prediction of CO2 diffusivity in brine at reservoir conditions for the engineering design and the technical risk assessment during the process of CO2 injection.

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Chemistry of Reservoir Fluids in the Aspect of CO2 Injection for Selected Oil Reservoirs in Poland

Energies ◽

10.3390/en13236456 ◽

2020 ◽

Vol 13 (23) ◽

pp. 6456

Author(s):

Ewa Knapik ◽

Katarzyna Chruszcz-Lipska

Keyword(s):

Oil Recovery ◽

Carbon Capture ◽

Co2 Storage ◽

Carbon Capture And Storage ◽

Oil Reservoirs ◽

Co2 Injection ◽

Oil Composition ◽

Co2 Solubility ◽

Geological Co2 Storage ◽

Reservoir Conditions

Worldwide experiences related to geological CO2 storage show that the process of the injection of carbon dioxide into depleted oil reservoirs (CCS-EOR, Carbon Capture and Storage—Enhanced Oil Recovery) is highly profitable. The injection of CO2 will allow an increasing recovery factor (thus increasing CCS process profitability) and revitalize mature reservoirs, which may lead to oil spills due to pressure buildups. In Poland, such a solution has not yet been implemented in the industry. This work provides additional data for analysis of the possibility of the CCS-EOR method’s implementation for three potential clusters of Polish oil reservoirs located at a short distance one from another. The aim of the work was to examine the properties of reservoir fluids for these selected oil reservoirs in order to assure a better understanding of the physicochemical phenomena that accompany the gas injection process. The chemical composition of oils was determined by gas chromatography. All tested oils represent a medium black oil type with the density ranging from 795 to 843 g/L and the viscosity at 313 K, varying from 1.95 to 5.04 mm/s. The content of heavier components C25+ is up to 17 wt. %. CO2–oil MMP (Minimum Miscibility Pressure) was calculated in a CHEMCAD simulator using the Soave–Redlich–Kwong equation of state (SRK EoS). The oil composition was defined as a mixture of n-alkanes. Relatively low MMP values (ca. 8.3 MPa for all tested oils at 313 K) indicate a high potential of the EOR method, and make this geological CO2 storage form more attractive to the industry. For reservoir brines, the content of the main ions was experimentally measured and CO2 solubility under reservoir conditions was calculated. The reservoir brines showed a significant variation in properties with total dissolved solids contents varying from 17.5 to 378 g/L. CO2 solubility in brines depends on reservoir conditions and brine chemistry. The highest calculated CO2 solubility is 1.79 mol/kg, which suggest possible CO2 storage in aquifers.

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