Development and characterization of CO2 micro-nano dispersion system for enhanced oil recovery from shale oil

Relative stability characterization of CO₂ nano bubbles

2.4.1

Average size, dispersity, and number concentration are core parameters for characterizing the basic properties of CO₂ nano bubbles [18,19]. This study took pH = 7.0 as the set condition, and systematically carried out the relative stability (nanobubbles can maintain the nanoscale instead of rapidly coalescing into micro/milliscale bubbles) within a certain duration, and whether the attenuation rate of core characteristics (e.g., particle size, number concentration) matches application-oriented requirements. Characterization experiment of CO₂ nano bubbles is carried out in two working conditions: static and flow.

In the static condition test, a CO₂ nano bubble dispersion system with an average particle size of approximately 400 nm was first prepared using the basic parameters of 6 min gas–liquid circulation time and 150 mL/min gas flow rate. Meanwhile, a pH gradient experiment was added, and the same system was prepared synchronously under different pH conditions (1.5, 3.0…9.0, 10.5). Subsequently, the average bubble diameter and polydispersity index (PDI) were obtained via DLS (cumulative method), while the number concentration was measured by nanoparticle tracking analysis (NTA). The ACR from DLS functions exclusively as a relative indicator of the instrument’s scattered signal intensity, and it is not utilized for number concentration conversion [20,21].

To address the flow relative stability issue of nano bubbles in industrial scenarios, a 0–60 min circulating flow experiment was further designed, with two comparative conditions of 10 mL/min (low flow rate) and 20 mL/min (high flow rate). Similarly, a nanoparticle size and zeta potential analyzer was used to explore the dynamic effects of different flow rates on the CO₂ nano bubble system.

Relative stability characterization of CO₂ nano bubbles under the influence of external factors

2.4.2

This section investigates the regulatory mechanisms of inorganic salts and surfactants on CO₂ nano bubble relative stability. For inorganic salt experiments, NaCl and CaCl₂ (0.1–1.0 mol/L) were used. After preparation following Section 2.3, DLS and zeta potential methods from Section 2.4.1 were applied to determine particle size distribution, surface charge, and 0–70 h particle size changes, comparing the electric double layer screening effect differences between Na⁺ and Ca²⁺. Surfactant experiments covered anionic (α-olefin sulfonate [AOS]), cationic (cetyltrimethylammonium bromide [CTAB]), and nonionic (dodecyl/tetradecyl glucoside [APG] and nonylphenol polyoxyethylene ether [NP40]) types with concentrations of 0.1–1 wt% (or 0.01–0.5 critical micelle concentration [CMC]). Through the same preparation and characterization procedures, combined with particle size evolution data, the differences in regulatory mechanisms via interfacial charge or surface tension were analyzed.

Huff-Puff test of CO₂ micro-nano system

2.4.3

This test employed a core displacement device and nanoparticle tracking analyzer to systematically investigate the huff-puff imbibition effects of three systems: pure CO₂ system, CO₂ + LSW-50 binary system, and CO₂ + LSW-50 + nonionic surfactant NP40 (concentrations of 0.01/0.1/0.5 wt%) ternary system. By regulating key parameters such as pressure, gas–liquid ratio, and injection rate, the influence of different experimental conditions on the displacement efficiency of the systems was examined.

Basic characteristics and relative stability of CO₂ nano bubbles under static conditions

3.1.1

Under the experimental conditions of a gas–liquid circulation time of 6 min and a gas flow rate of 150 mL/min, a CO₂ nano bubble dispersion system with an initial average particle size of approximately 177 nm was successfully prepared (Figure 2a). As shown in Figure 2, the research system investigated the evolution of particle size of the CO₂ nano bubble system over a period of 0–75 h, while simultaneously monitoring the dynamic changes in the dispersibility coefficient δ and the ACR.

Figure 2

This study systematically reveals the relative stability regulation law and mechanism of CO₂ nano bubbles: As shown in Figure 2c, CO₂ nano bubbles exhibit a two-stage evolution of “slow growth-fast coarsening” in deionized water: in the first 20 h, the particle size increases from ∼450 nm to 560 nm (24% increase) due to CO₂’s high water solubility buffering the mass transfer rate of Ostwald ripening. After 20 h, liquid-phase CO₂ becomes saturated, and Ostwald ripening plus Brownian motion-induced coalescence jointly drive rapid coarsening, reaching ∼900 nm at 75 h. In contrast, N₂ nano bubbles increase from 350 to 600 nm within 75 h without obvious two-stage behavior (as N₂ has extremely low water solubility, and its evolution relies more on simple coalescence and ripening). CO₂’s high solubility regulates the evolution rhythm via “dissolution-saturation,” making its timeliness more staged [24]. In Figure 2b, the average size of CO₂ nano bubbles shows a sinusoidal change in “increase → decrease → slow increase” with temperature, resulting from the competition between the “coalescence effect of Ostwald ripening” and the “bubble shrinking effect regulated by CO₂ solubility”: the coalescence effect dominates size growth at 5–20°C. The “shrinking effect” dominates size decrease between 20 and 50°C (40°C is the critical balance point of the two effects) as CO₂ solubility decreases with rising temperature. Above 50°C, the shrinking effect moderates and the coalescence effect dominates again, causing slow size increase. The high solubility of CO₂ (1.45 g/kg) amplifies the “solubility-temperature” regulation on size, making it exhibit this unique law (due to low solubility, N₂ nano bubbles rely more on thermal motion-induced coalescence for size change without the intermediate decreasing stage) [25]. The pH regulation experiment found that hundreds of nanometer-sized bubbles can be formed in a wide range from acidic to alkaline (pH 2–12), but under alkaline conditions, they exhibit significantly enhanced relative stability (Figure 2d). On the one hand, based on the experimental results regarding temporal evolution (two-stage “dissolution-saturation buffering”), temperature response (40°C effect balance threshold), and pH adaptation (enhanced charge repulsion under alkaline conditions), these findings clearly elucidate the relative stability mechanism of CO₂ nano bubbles, which centers on “mass transfer buffering mediated by high water solubility + synergistic regulation of interfacial charges.” On the other hand, the revealed temperature control threshold (40°C), pH adaptation range (2–12, with better performance under alkaline conditions), and temporal evolution law provide a quantitative basis for the parameter optimization of CO₂ nano bubble systems in oil and gas extraction (e.g., control of injection temperature, adjustment of reservoir pH adaptation). Particularly for alkaline reservoirs, these findings can directly guide the stability design of injection systems, significantly enhancing the application adaptability and effectiveness of this technology in practical extraction scenarios.

The zeta potential of CO₂ nano bubbles exhibits a notable relative stability decay characteristic over time (Figure 3). Experimental data reveal that within the initial 9 h, the zeta potential remains stable within the range of −18 to −21 mV, indicating good short-term relative stability of the bubble system. However, when the standing time is extended to 24–72 h, the absolute value of the potential decreases significantly, and it is already below 10 mV at 72 h. This potential decay phenomenon originates from changes in the charge characteristics at the gas–liquid interface: due to the significant thermodynamic potential difference between OH⁻ (adsorption energy −446.8 kJ/mol) generated by water molecule ionization and H⁺ (−1,104 kJ/mol), OH⁻ preferentially adsorbs onto the bubble surface, forming a negative charge layer. Over time, this surface charge gradually dissipates, weakening the electrostatic repulsion force and ultimately promoting bubble coalescence. Based on the kinetic analysis of potential decay, it is once again verified that the effective stable time of CO₂ nano bubbles under static conditions is approximately 72 h. This discovery provides important time-dependent parameters for the practical application of nano bubble systems.

Figure 3

Basic characteristics and relative stability of CO₂ nano-bubbles in a flowing state

3.1.2

In practical applications, nano bubbles are often found in complex flow environments. Therefore, focusing on the relative stability of nano bubbles in industrial flow environments, we systematically investigated the dynamic effects of different flow rates on the CO₂ nano bubble system under flowing conditions. By designing a cyclic flow experiment (0–60 min), we compared and analyzed the particle size evolution and zeta potential changes in CO₂ nano bubbles under low flow rate (10 mL/min) and high flow rate (20 mL/min) conditions. This revealed the regulation mechanism of fluid shear action on nano bubble relative stability, providing an experimental basis for the optimal control of nano bubble parameters in industrial applications.

Figure 4 reveals the dynamic evolution characteristics of CO₂ nano bubbles under different flow rates. Experimental data in Figure 4a shows that during the cyclic flow process from 0 to 60 min, the average size of the bubbles increases significantly with the increase in flow rate: the particle size fluctuates within the range of 480–930 nm under low-speed conditions (10 mL/min), while it increases to 700–1,500 nm under high-speed conditions (20 mL/min). The study found that the flow process exhibits a typical “disturbance-equilibrium” dynamic mechanism: in the initial stage, the energy input from the micro-nano bubble generator breaks the gas–liquid dynamic equilibrium and enhances bubble collisions. Subsequently, the system gradually tends toward a new dynamic equilibrium. It is worth noting that the increase in flow rate not only increases the maximum particle size by 35% but also extends the dynamic equilibrium establishment time by about 50%.

Figure 4

Experimental data in Figure 4b and c reveal the multiple impacts of flow conditions on the CO₂ nano bubble system: First, the bubble size dispersibility coefficient (δ value) gradually increases with increasing flow rate. Second, dynamic flow enables the bubble concentration to be stably maintained at a relatively high level (90–110 Kcps), which is more than half as high as that under static conditions. This is primarily attributed to the continuous energy input from the micro-nano bubble generator, promoting the processes of bubble formation and regeneration. This high concentration state, in turn, accelerates the dynamics of bubble coalescence, ultimately leading to the formation of larger bubbles. This study quantifies for the first time the coupled mechanism of “high concentration-wide distribution-low relative stability” in industrial flow systems, providing key insights for parameter optimization in practical applications.

Figure 4d reveals the regulation of flow rate on the surface potential of CO₂ nano bubbles. The study shows that under dynamic flow conditions (0–60 min), the potential of CO₂ nano bubbles exhibits significant flow rate dependence: when the flow rate is <10 mL/min, the potential stabilizes at −20 to −15 mV. However, when the flow rate is increased to 20 mL/min, the absolute value of the potential gradually approaches 0 mV. This potential decay phenomenon stems from a dual mechanism: on the one hand, high-speed flow promotes bubble collision and coalescence, leading to an increase in particle size (consistent with the sudden potential change rule of micro-nano bubbles discovered by Pan et al. [26]). On the other hand, the flow shear effect disrupts the double-layer structure, causing surface charges to redistribute. Especially when the bubble radius exceeds 1 μm, changes in the ion concentration distribution at the interface significantly reduce the absolute value of the potential.

DLS and zeta potential measurements indicate that the formation of CO₂ nano bubbles is a dynamic process, with their size and surface charge evolving continuously over time (Figure 5). Under static conditions, the supersaturated CO₂ solution initially forms nanoscale gas clusters (several nanometers) that are stabilized by surface energy and charge interactions. As the gas saturation decreases, these clusters gradually grow into nano bubbles. Due to Brownian motion and weak buoyancy forces, nano bubbles can remain suspended for a long time, but they can coalesce to form larger bubbles and eventually burst. In a flowing state, bubble behavior is regulated by fluid dynamics: at low flow rates, nano bubbles move stably with laminar flow. Increased flow rates intensify bubble collisions, leading to a broader size distribution, but continuous energy input maintains a high bubble concentration. This evolutionary mechanism confirms previous research findings that the essence of nano bubbles is dynamic gas clusters [27].

Figure 5

Impact of inorganic salts on CO₂ nano bubbles

3.2.1

• (1) The influence of salt ions on the relative stability of CO₂ nano bubbles

Figure 7 reveals the regulatory mechanism of electrolytes on the physicochemical properties of CO₂ nano bubbles. Experimental data show that: (1) In terms of particle size evolution, salt ions significantly increase the average size of bubbles. 0.01 wt% NaCl and CaCl_2, respectively, increases the particle size from 400 nm to 468 nm and 504 nm, and the growth-promoting effect of divalent Ca²⁺ is 35% stronger than that of Na⁺. (2) In terms of surface potential, salt ions cause a decrease in the absolute value of zeta potential, and 0.1 wt% CaCl₂ even triggers charge reversal (negative → positive), which is due to the charge neutralization effect between high valence ions and interface OH⁻.

• (2) Changes in CO₂ nano bubbles formed by different types and concentrations of salt particles over time

Figure 7

From the analysis of Figure 8, it can be seen that salt ions accelerate the process of bubble coarsening. The system containing 0.01 wt% NaCl shows a 100% increase in particle size (400–800 nm) within 70 h, while the same concentration of CaCl₂ system only takes 20 h to reach 1μm. In addition, the coarsening rate of Ca²⁺ system is faster than that of Na⁺, which is directly related to the stronger charge neutralization ability of divalent ions.

Figure 8

Influence of surfactants on CO₂ nano bubbles

3.2.2

• (1) The influence of surfactant type and concentration on the size distribution of CO₂ nano bubbles

This study selected four types of surfactants: anionic AOS (α-olefin sulfonate), cationic CTAB (cetyltrimethylammonium bromide), nonionic APG-1214 (dodecyl/tetradecyl glucoside), and nonionic NP40 (nonylphenol polyoxyethylene ether). Before the generation of CO₂ nanobubbles, they were formulated into 0.1–1 wt% aqueous solutions, and then introduced into a hydraulic cavitation generator together with CO₂ to prepare bubbles, ensuring that the surfactants participate in the formation and stabilization of bubbles throughout the process. The basic properties of the four surfactants are as follows: AOS has a molecular weight of 300–400 g/mol, a CMC of 0.01–0.05 mmol/L, and molecules carry negative charges (–SO₃⁻Na⁺). CTAB has a molecular weight of 364.45 g/mol, a CMC of 0.9–1.1 mmol/L, and molecules carry positive charges (–N⁺(CH₃)₃Br⁻). APG-1214 has a molecular weight of 480–550 g/mol, a CMC of 0.05–0.1 mmol/L, and molecules are electrically neutral. NP40 has a molecular weight of 600–700 g/mol, a CMC of 0.02–0.04 mmol/L, and molecules are electrically neutral. Based on the analysis of Figure 9 (where Figure 9a–d correspond to the particle size distributions of AOS, CTAB, APG-1214, and NP40 systems, respectively), the regulation of surfactants on the size distribution of CO₂ nanobubbles shows significant concentration and type dependence: when the concentration increases from 0.01 CMC to 0.5 CMC, the particle size distribution peaks of the four systems all shift to smaller sizes and the peak widths narrow, with an overall decrease of 60% in the average particle size (due to the increased concentration enhancing interfacial adsorption and inhibiting bubble coalescence). In terms of types, AOS (Figure 9a) shows the most significant left shift of the particle size distribution peak (with the peak center at about 100 nm at 0.5 CMC) because the negatively charged groups enhance the electrostatic repulsion at the gas–liquid interface. CTAB (Figure 9b) causes the particle size distribution peak to shift slightly to larger sizes at low concentrations due to charge neutralization, and only inhibits coalescence through steric hindrance from dense molecular adsorption at high concentrations (>0.5 CMC). Nonionic APG-1214 (Figure 9c) and NP40 (Figure 9d) inhibit coalescence by relying on the steric hindrance effect of 5–8 nm hydration layers formed by hydrophilic groups. Their refining effect is better than that of CTAB but slightly inferior to that of AOS, and the peak shapes and variation trends of their particle size distributions are similar, reflecting a consistent nonionic stabilization mechanism.

Figure 9

Figure 10 presents the effects of surfactants with different types (anionic AOS, cationic CTAB, nonionic APG/NP40) and concentrations on the average particle size and zeta potential of CO₂ bubbles. However, the current way of connecting data points continuously is misleading (as different surfactants belong to independent systems rather than continuous concentration changes of the same system). In the follow-up, it will be optimized to subfigures (plotting by surfactant type, respectively) or grouped scatter plots to improve the clarity of data presentation. In terms of the trends, as the concentration of anionic AOS increases, the negative charge at the gas–liquid interface (the absolute value of the negative zeta potential) gradually enhances, and the bubbles continuously refine due to electrostatic repulsion (decreasing from 420 nm to 140 nm). The zeta potential of cationic CTAB gradually reverses from negative to positive with increasing concentration, and at low concentrations, the electrostatic stabilization ability may be weakened due to charge neutralization, resulting in local coalescence of bubbles (with the particle size showing an increasing trend at low concentrations). The zeta potentials of nonionic APG and NP40 fluctuate slightly in the range of −20∼0 mV, and the bubbles rapidly refine to around 80 nm and remain stable. The similarity in their effects on nanobubbles arises because both rely on the hydration layers formed by hydrophilic groups to generate steric hindrance for inhibiting bubble coalescence, and the stabilization mechanism dominated by steric hindrance at the molecular level is consistent.

Figure 10

Figure 11 illustrates the time evolution of the average particle size of CO₂ bubbles in deionized water and surfactant solutions with different types and concentrations. The bubble size in deionized water increases continuously over time, consistent with the coarsening feature driven by Ostwald ripening. After adding surfactants, the growth of particle size is inhibited, and there is a dependence on both surfactant type and concentration. The higher the concentration of anionic AOS (0.01–0.5%), the slower the particle size growth, which is presumed to relate to the electrostatic repulsion caused by the enhanced interfacial negative charge. For cationic CTAB, the particle size grows faster initially at a low concentration (0.01%), possibly because charge neutralization weakens electrostatic stabilization, while the inhibition effect rebounds at high concentrations (the mechanism may involve micellar interfacial adsorption). Nonionic surfactants (APG, NP40) can significantly delay particle size growth even at a low concentration (0.1%), with smaller fluctuations within 70 h compared to ionic systems. It is inferred that the steric hindrance generated by the hydration layer formed by their molecules at the gas–liquid interface is the core of stabilization, and the steady-state particle size is significantly smaller than that in anionic systems.

Figure 11

Figure 12 reveals the differences in the mechanisms by which surfactants stabilize CO₂ nano bubbles. In deionized water, bubbles are maintained stable by a negative charge layer (−20 mV) formed by surface OH⁻. Ionic surfactants achieve relative stability through a dual action (reducing surface tension to 30 mN/m, while regulating charge to −60 mV for anions and +56 mV for cations). Nonionic materials, on the other hand, generate entropy repulsion by forming a 5–8 nm thick hydration layer and retain some negative charges (−30 to −35 mV), exhibiting a unique spatial electrostatic synergistic stabilization mechanism.

Figure 12

Assisted stimulation test of CO₂ micro-nano system

3.3.1

Imbibition experiments were conducted using CO₂, CO₂/LSW, and CO₂/LSW/surfactant solution, as shown in Figure 13.

Figure 13

The experiment compared the throughput and imbibition effects of three systems: pure CO₂, CO₂/low salinity water, and CO₂/low salinity water/surfactant. The experimental results show that the CO₂/low salinity water/surfactant composite system has the best oil displacement effect, with a recovery rate (43.6–52.5%) significantly higher than that of pure CO₂ (36.8%) and CO₂/low salinity water system (32.5%). Especially in the initial 30 h, the micro-nano dispersion system exhibits a faster oil recovery rate, and the concentration of surfactants is positively correlated with the recovery rate. This advantage stems from a triple synergistic effect: low salinity water improves wettability, surfactants reduce interfacial tension and form emulsions, and CO₂ promotes crude oil flow through dissolution, expansion, and extraction effects, collectively enhancing the imbibition throughput effect.

Analysis of factors affecting the CO₂ micro-nano dispersed system stimulation test

3.3.2

• (1) The impact of injection pressure, gas–liquid ratio, and injection rate on the huff and puff effect

The experiment investigated the impact of different injection pressures (5 MPa, 10 MPa, 15 MPa, 20 MPa) on the stimulation effect of the CO₂/LSW-50/NP40 micro-nano dispersed system. By adjusting the CO₂ injection volume, the study explored the influence of various gas–liquid ratios on the stimulation effect of the CO₂/LSW-50/NP40 micro-nano dispersed system. Additionally, by adjusting the gas injection rate, the experiment examined its impact on the stimulation effect of the CO₂/LSW-50/NP40 micro-nano dispersed system.

Figure 14 shows that when the injection pressure of CO₂ exceeds 10 MPa, the oil recovery rate significantly increases, mainly due to the synergistic effect of high pressure promoting CO₂ dissolution and diffusion, and low salinity water/surfactant. The optimal recovery rate is achieved when the gas–liquid ratio is 2:1, and the effect of excessive CO₂ injection is limited. Increasing the gas injection rate can increase the concentration of micro-nano bubbles, expand the contact area, promote the adsorption of surfactants and the transformation of rock wettability, thereby significantly improving the recovery rate. Comprehensive optimization of injection parameters (pressure >10 MPa, gas–liquid ratio of 2:1, higher injection rate) can maximize the oil displacement efficiency of CO₂ micro-nano dispersion system.

Figure 14

Oil displacement mechanism of CO₂ micro-nano system

3.3.3

The complete huff-and-puff oil recovery mechanism of the CO₂/LSW/surfactant micro-nano dispersion system is as follows: In the high-pressure injection stage, the system moves rapidly, relying on the fracture network characteristics of shale reservoirs, laying a spatial foundation for subsequent processes. After entering the soaking period, it undergoes three key stages of action in sequence (Figure 15). During the initial stage, micro-nano bubbles burst to release active components, which, combined with the wettability regulation effect, promote the wettability alteration of the matrix surface and improve the contact condition between crude oil and the system. In the middle stage, CO₂ realizes crude oil viscosity reduction and light component extraction by virtue of its molecular diffusion property, while surfactants and LSW synergistically exert the imbibition displacement effect to enhance the stripping driving force between crude oil and pore matrix. In the later stage, under the synergistic action of the above multiple mechanisms, crude oil continuously detaches from nano-pores. Finally, entering the flowback stage, the activated crude oil converges along the fracture network to the wellbore for production. This process innovatively integrates the dual advantages of physical driving forces (CO₂ diffusion, bubble movement) and chemical imbibition (wettability alteration, imbibition displacement). It not only specifically addresses the defect of easy channeling along fractures in single CO₂ flooding, but also significantly improves the oil production efficiency in the matrix through the synergy of multiple mechanisms.

Figure 15