Microbubble CO₂ Injection in High- Perm Sandstone: Flow-Rate Effects and Permeability Decay

Microbubble CO₂ Injection in High- Perm Sandstone: Flow-Rate Effects and Permeability Decay | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Microbubble CO₂ Injection in High- Perm Sandstone: Flow-Rate Effects and Permeability Decay Theo Le Gallais, Egi Adrian Pratama, Klaus Regenauer-Lieb, Mohammad Sarmadivaleh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8879243/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Microbubble (MB) CO₂ injection has been proposed to improve sweep efficiency and dissolution trapping, yet its implications for injectivity and near-wellbore integrity in high-permeability formations are not well constrained. We conducted repeated volume-balance core-flooding experiments on high-permeability Berea sandstone (~ 980 mD) under deep saline aquifer conditions (40°C, 10.7 MPa), comparing MB and conventional supercritical CO₂ injections across flow rates of 0.05–0.5 cc/min (Ca : 1.15–11.5 × 10⁻⁹) while monitoring brine permeability. At 0.05 cc/min, MB injection increased average CO₂ saturation by 8.9% relative to conventional flooding due to temporary microbubble-induced blockage of dominant flow channels. This benefit diminished at higher flow rates (0.1–0.5 cc/min), where MB injection consistently yielded lower final CO₂ saturations. Across sequential floods, MB injection caused brine permeability to decline up to four times faster than conventional injection, indicating accelerated near-wellbore damage likely driven by fines mobilisation and enhanced mineral reactions associated with rapid microbubble dissolution. These results demonstrate a clear trade-off in MB CO₂ injection: potential sweep-efficiency gains at low flow rates versus permeability loss and injectivity difficulties at higher flow rates. The results of this study suggest the need for further research under higher flow rates considering practical operation and optimising microbubble-based storage strategies will require careful control of flow rate and consideration of reservoir heterogeneity in high-permeability systems. Geological CO₂ storage Microbubble CO₂ injection High-permeability sandstone Sweep efficiency Permeability decay Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Carbon dioxide is the principal emitted greenhouse gas responsible for unprecedented fast climate change. It is the co-product of every industry sector at the society’s base and more globally, from every main source of energy used by mankind (IPCC, 2023 ). Moderating emissions is a current challenge that will persist in the next decades. Carbon capture, utilization and storage is considered a major actor in the transition to net-zero carbon by 2050 (IEA, 2020 ). Particularly, carbon storage is a major challenge in economic scales: Building a storage project includes many safety considerations with relative uncertainties (Mahjour & Faroughi, 2023 ). Microbubble CO₂ is a new injection method that may be used in all storage settings. It has mainly been studied as displacing liquid for Enhanced Oil Recovery (EOR) (Xue et al., 2018 ). This technology benefits from a higher oil recovery by reducing entry capillary pressure (Li et al., 2024 ). By being able to penetrate smaller pores, CO₂ microbubble also implies a lower injectivity overall. Microbubbles can plug the main pathways, allowing flow through the smallest pores (Yu et al., 2022 ), resulting in a higher ΔP. This injection type has also been shown to be effective in aquifer settings as there is also potential for a more efficient storage. In these particular settings, microbubble injection has been mainly studied in a high salinity environment (Jiang et al., 2019 ; Park et al., 2018 ; Patmonoaji et al., 2019 ; Wang et al., 2022 ; Zhai et al., 2020 ). Overall, microbubble injection has a potential for a higher sweep efficiency, higher dissolution rate and a slower CO₂ plume rising velocity (Li et al., 2023 ). The current state of the art in microbubble injection applied to laboratory-scale core flooding tests performed in deep saline aquifer conditions demonstrates a relative increase in average CO₂ saturation at the steady state. This improvement is attributed to the addition of a microbubble generation filter (Fig. 1 ). All values within sandstone rock samples never go above 20% increase in CO₂ saturation and on average 6.2%. Mainly Berea sandstone is used as test sample in literature floodings. Interestingly, it shows disparate results on the most tested permeability: 100 mD. Samples done in rock cores show an average of 0 to 5% improvement thanks to microbubble injection. Overall, a trend is showing up, where higher permeability samples have more potential to have better results with microbubble injection. This could be explained by the “Jamin effect”, detailed in publications (Dubey & Majumder, 2024 ; Le et al., 2022 ; Li et al., 2024 ; Telmadarreie et al., 2016 ). Jia et al. ( 2023 ) observed on microchips large channels plugged by microbubbles, which allowed smaller pores to be penetrated. A microbubble or a swarm of microbubbles with a larger diameter to the pore can block it and create a local higher pressure. CO₂ can then reach pores that required a higher capillary entry pressure to be swept. In the case of high-permeability sandstone samples, they possess high-diameter channels through which CO₂ can easily transit. Microbubble CO₂ agglomerates can temporarily plug them and allow other smaller channels to be penetrated. From literature results, it can be noted that floodings on cores with a similar permeability may not obtain similar CO₂ saturation results. In fact, the relation between permeability and final CO₂ saturation after drainage is complex and no direct relation exists between them (Zhang & Arif, 2024 ). However, the microbubble effect on sweep efficiency and injectivity appears to depend on permeability, which can be seen from the correlation shown in Fig. 1 . The effectiveness of microbubble injection can vary significantly, as the way microbubbles move through the rock may lead to inconsistent blockage; in addition, microbubbles of different sizes may interact with and block different pore spaces during each injection. Literature results also employed different salinities, ranging from 0.58 (Xue et al., 2013 ) to 187 g/L eqNaCl (Jiang et al., 2019 ; Patmonoaji et al., 2019 ; Zhai et al., 2020 ) which may have an impact on microbubble generation and flood. The physical properties of microbubbles lead to improvements in sweep efficiency, injectivity and dissolution rate, as seen in the literature (Li et al., 2018 ; Park et al., 2018 ; Patmonoaji et al., 2019 ; Ueda et al., 2021 ; Wang et al., 2022 ; Xue, 2021 ; Xue & Matsuoka, 2008 ; Xue et al., 2014 ; Xue et al., 2018 ; Xue et al., 2011 ; Yu et al., 2022 ; Zhai et al., 2020 ). However, other effects of microbubbles could be considered and have the potential to antagonise the previously mentioned mechanisms. In near-wellbore environments, where the rock is exposed to high concentrations of CO₂ during injection, the fast dissolution of microbubbles can cause the surrounding brine to become acidic more quickly. This can accelerate the dissolution of minerals and chemical reactions within the pore spaces of the rock. Moreover, microbubbles negative charges on their boundaries could interact with clay particles and cause swelling. Overall, all these effects could cause fines migration and faster rock decay. Most comparative laboratory tests have relied only on a single flowrate per experiment, which does not reflect real field conditions where the injection rate tends to be variable. Microbubble injection studies on a flowrate comparison point have noticed significant differences in results (Le et al., 2022 ; Wang et al., 2025b ). In the case of Wang et al. ( 2025b ), 0.05 cc/min on a standard syringe pump injection is seen as the most optimal case for microbubble injection. However, this injection flowrate on a closer reservoir is not to be expected but at least a hundred meters from the well in medium-sized projects. Economic viability is also unlikely if microbubbles must be generated at such a low rate, as it is insufficient for the field. Sequential flooding is used in this study to investigate microbubble injection rate sensitivity ; the effects on saturation and global microbubble behaviour are discussed. This study investigates whether microbubble injection improves CO₂ saturation in high-permeability rocks, using CO₂ flooding experiments on Buffi Berea sandstone with a permeability of ~ 1000 mD. The flooding protocol of Zhai et al. ( 2020 ) was replicated at a flow rate of 0.05 cc/min on one sample (BO5). A second sample (BO3) was subjected to sequential CO₂ injections at increasing flow rates (0.05, 0.1, and 0.5 cc/min) to evaluate how changes in injection rate influence steady state saturations relative to conventional injection. The impact of microbubble injection on permeability reduction was investigated by monitoring brine permeability after the initial imbibition, for both conventional and microbubble injection, using sample BO3. To the best of our knowledge, this is the first study to systematically quantify flow-rate–dependent microbubble CO₂ behaviour and permeability decay in high-permeability sandstone under repeated injection cycles. By comparing microbubble and conventional CO₂ injection across sequential flow rates, we capture both efficiency gains and integrity losses. The findings provide insight directly relevant to CO₂ subsurface utilisation and geological storage operations. 2. Materials and Methods Volume balance core flooding is a technique that measures the water volume output from the sample at all times during the CO₂ injection experiment. By subtracting the volume contained in the tubing (dead volume), the sample’s global CO₂ saturation can be estimated. CO₂ saturation calculation from volume change is detailed: $$\:{S}_{g}=\frac{{V}_{observed}-{V}_{dead\:volume}}{{V}_{pore}}*100\:\left(\%\right)$$ $$\:{S}_{g}:\:{CO}_{2}\:gas\:saturation\:\left(\%\right)$$ $$\:{V}_{observed}:Observed\:water\:volume\:in\:cylinder\:\left(ml\right)$$ $$\:{V}_{dead\:volume}:Dead\:volume\:\left(ml\right)$$ $$\:{V}_{pore}:Connected\:pore\:volume\:in\:Core\:\left(supposed\:100\%\:filled\:with\:brine\:after\:saturation\right)\:\left(ml\right)$$ Dead volume was measured previous to the flooding. The core holder is empty, and sleeves are connected directly. Water was injected until the tubing becomes full. Air is then injected to chase the water and recover the corresponding volume. This process has been done 20 times to ensure consistency of the dead volume. Experiments volumes are corrected by the dead volume, and the time is corrected to match zero when the dead volume has been reached. Dead volume and cylinder measurements uncertainties resulted in an absolute uncertainty of 1.39% to 5% in CO₂ saturation depending on the used setup layout at the time of the experiment. It is mainly dependent on the standard deviation obtained through dead volume measurements (Table 1 ). Cylinder readings also introduce a volume measurement error of ± 0.25 ml. For microbubble tests, the filter pore volume was not sufficient to notice a significant dead volume measurement change. Therefore, similar dead volume measurements have been taken for both injection types. In all shown experiments, the mean value and standard deviation have been taken as the output results of a given setting. Table 1 Absolute uncertainty associated with dead volume and measuring cylinder. Test number Absolute uncertainty (%CO₂) 1–2 1.91 3–13 2.01 14–28 4.98 29–33 1.39 These absolute uncertainties are expected to be found on the measured dataset; they are averaged to compute an expected variance and compared to the measured data. Upon discharge from the back-pressure regulator, the brine undergoes two competing volumetric effects: expansion associated with pressure release and contraction associated with cooling. Upper-bound estimates of these effects were evaluated. Isothermal decompression of a 12.5 wt% NaCl brine from 10 MPa to 0.1 MPa at 40°C results in a volumetric expansion of approximately + 0.36%, based on an isothermal compressibility of 3.64 × 10⁻¹⁰ Pa⁻¹. The concurrent cooling of the brine from 40°C to 25°C produces a volumetric contraction of approximately − 0.6%, using an average volumetric thermal expansivity of 4.085 × 10⁻⁴ K⁻¹ over this temperature interval. Values for brine compressibility and thermal expansivity were taken from Rogers and Pitzer ( 1982 ). The combined effect of decompression and cooling therefore corresponds to a net volumetric decrease of approximately 0.24%, equivalent to 0.048 mL for a nominal volume of 20 mL, representing the maximum recoverable volume. This correction is significantly smaller than the uncertainty associated with dead-volume estimation and volumetric cylinder readings. Consequently, no correction for pressure- and temperature-induced volume changes was applied to the measurements. 2.1. Experimental apparatus Core floodings setups are shown in Fig. 2 . A Vinci double syringe pump was providing injection pressure. ISCO pumps were guaranteeing back pressure (260D) and confining pressure (500D). The setup temperature is guaranteed through a circulation model, where temperature is guaranteed by a circulating confining fluid, heated at an accumulator and moving thanks to a circulation pump (Eldex 1021 bb-4-2). Volume measurements are made from a 0.25ml precision water cylinder. Supercritical CO₂ is fed from a Parr reactor where it is prepared to be water-wet at the experimental conditions (1550 psi, 40°C). 2.2. Core Characteristics The porosity and permeability of the Buffi Berea sandstone samples (Fig. 3 ) have been measured using a CoreTest AP-608 Poro Permeameter. Sample BO5 exhibited a porosity of 24.10%, with an air permeability of 985.15 mD and an absolute permeability of 966.97 mD. Its measured pore volume was 20.36 cc. Sample B03 showed a similar porosity of 23.95%, along with air and absolute permeabilities of 982.81 mD and 955.32 mD, respectively, and a pore volume of 20.10 cc. The high porosity and permeability makes the chosen cores suitable for this investigation of the microbubble injection in a high permeability setting. High permeability Berea represent the upper range of permeabilities encountered in saline aquifers, where injectivity and near-wellbore effects are expected to be critical for CO₂ storage operations. 2.3. Experiment protocol Volume balance core floodings have been carried out under different settings which have all been compiled in Table 2 . Test numbers are in chronological order. Some numbers are missing as the experiment has been carried out but failed due to a recording or injection issue. Most experiments in this study were conducted at a base flow rate of 0.05 cc/min, matching the conditions used by Zhai et al. ( 2020 ) to investigate microbubble flow away from the injection wellbore. In sequential tests, higher flow rates of 0.1 and 0.5 cc/min were subsequently applied to evaluate the flow-rate sensitivity of microbubble injection. Reference floodings at 0.1 and 0.5 cc/min from full water saturated core were realised to compare with the sequential injection protocol in both injection types, Table 2 Volume balance core flooding experimental tests settings and brine permeability monitoring test indented for both BO5 and BO3 samples. Brine permeability was monitored for the test numbers 20 to 31. Sample name Test number Test type BO5 2–5, and 13–18 Conventional injection 0.05cc/min only 6–9 and 12 Microbubble injection 0.05cc/min only 11 Microbubble injection 0.1cc/min only 10 Microbubble injection 0.5cc/min only BO3 19 Conventional injection 0.5cc/min only 20 Conventional injection 0.1cc/min only 24–28 Microbubble injection Sequential 0.05 ◊ 0.1 ◊ 0.5 cc/min 30–31 Conventional injection Sequential 0.05 ◊ 0.1 ◊ 0.5 cc/min The flow rates used in this study are sufficiently low to maintain a capillary-dominated regime (Ca = 1.15–11.5 × 10⁻⁹) and to avoid inertial effects, while remaining high enough to generate a measurable pressure drop across the ~ 1 D cores. The porous-media Bond number is estimated to be \(\:1.3\times\:{10}^{-7}\) , which is much smaller than unity and demonstrates that buoyancy forces are negligible at the pore scale. As a result, gravity segregation is not expected during the horizontal core-flood experiments, and the observed displacement behaviour is governed by capillary forces rather than density contrasts. In comparison, the mobility ratio is inherently unfavourable: the brine-to-CO₂ viscosity ratio is 16.6, so within the Buckley–Leverett framework the mobility ratio can be expressed as the ratio of relative permeabilities multiplied by this large factor. This qualitatively highlights the strong tendency for CO₂ to be more mobile than brine, implying that any improvement in sweep efficiency or injectivity must arise from reductions in effective gas mobility (e.g., microbubble effects) rather than from favourable viscous or gravitational stability. The injected brine is synthetic, prepared from deionised water. The salinity is only contributed by NaCl at 125 g/L (12.5 wt%). This value has been chosen to remain close to previous work on microbubble injection (Jiang et al., 2019 ; Patmonoaji et al., 2019 ; Zhai et al., 2020 ). For any given flooding setting, the protocol remained similar. The Teflon-jacketed core with a Viton rubber layer was inserted in the core holder. The cell was filled with deionised water with a red colour dye to spot any confining leaks during the flooding. The confining pressure was first set to 750 psi (5.17 MPa). The sample was then put under vacuum for at least 24 hours. The vacuuming process was completed when the pore pressure had dropped to a plateau. Following this, the brine was injected at 5 cc/min until the pore pressure reached 100 psi. Both pore and confinement pressures were then increased at the same rate until the target was reached (pore: 1550 psi (10.7 MPa), confinement: 2175 psi (15 MPa)). From there, for all sequential floodings, a brine permeability test under flooding pressures was performed after the initial brine imbibition: the inlet and outlet pressure transducers recorded their pressures while three flow rates were applied: 10, 20, and 30 cc/min, with short breaks in between to allow the pressure to drop. The pressure difference (ΔP) was then extracted, and brine permeability was calculated using Darcy’s law and sample characteristics. The CO₂, pre-equilibrated with brine, was fed to the pump with the required amount of CO₂ for the experiment (2 pore volumes were estimated to be sufficient to reach breakthrough and recover all the brine, 45 cc was chosen as a higher boundary estimation). Confinement and injection pumps were heated at 40°C and left for one day for the temperature to equilibrate to the target. Once reached, the CO₂ flooding started, the flowrate was set as an input with the required injection amount, and the scale and pressure transducers were set to record until the flooding ended. The pore pressure rose from 1550 psi to 1580 psi (Back pressure regulator cutoff pressure) and the experiment stayed at this pressure until the flooding ended. Upon ending, both confinement and pore pressure were let down progressively to 750 psi and zero respectively. The sample was vacuumed again, and another experiment could then be carried out. For sequential tests, once 45 cc of CO₂ was injected, the new flowrate was set, and 45 more ccs were injected until the three flowrates had been carried out. It should be noted that the core holder was changed for these sequential tests, and dead volume measurements were run again for adjustments. 2.4. Recording To record the output water volume, a camera was installed in front of the recovery cylinder. Photos were being taken every 1 to 2.3 mins and directly stored in the recording computer under its shoot date and time. The confinement pressure was monitored via its own pressure transducers, both in the pump and in the core holder confinement output. The inlet and outlet pressure were recorded by transducers connected to the recording computer. 2.5. Microbubble generation and injection Microbubbles were generated using a filter provided by RITE (The Research Institute of Innovative Technology for the Earth) / Tokyo Gas and placed at the sample inlet. In this study, brine is flowing through the filter, then CO₂ follows. With an average pore size of 4 microns, it created bubbles expected to be in the order of tens of micrometres in size. The filter was also expected to generate an extra pressure drop, caused by both its lower permeability and by fines migration from particles present in the brine. During microbubble tests, these particles could stop at the filter and decrease the overall permeability, likely in a different order of magnitude compared to the core alone. Therefore, quantitative comparison in permeability between conventional and microbubble experiments could not be made. Instead, only the decay rate was compared, as it provided more insights into the impact of microbubble injection on the sample permeability. 2.6. Permeability measurements fit and uncertainties During repeated CO₂ floodings, the rock sample undergoes multiple mechanisms of alteration, which may lead to permeability decay: Fines migration: with a narrow distribution of pore throat sizes ,the case in Berea sandstone, events of clogging lead to exponential decay of open pore throats (Borisova & Adler, 2005 ). Many models of mineral dissolution precipitation are based on exponential laws with asymptotes due to the limited quantity of reactive material and decay in reactive surface (Noiriel, 2015 ). To estimate the characteristic decay time τ associated with the permeability decay of samples, a single exponential with asymptote model is applied to both conventional and microbubble injection decay curves measured for the sample BO3. This curve fit is commonly used in the literature to fit permeability decay data (Hall, 2025 ). The sample BO5 with a before-and-after flooding permeability measurement has undergone a similar decay. The exponential permeability decay curve fit is expressed as follows: $$\:k\left(t\right)={k}_{\infty\:}+({k}_{0}-{k}_{\infty\:})\text{e}\text{x}\text{p}(-\frac{t}{\tau\:})$$ Where: $$\:{K}_{\infty\:}:Asymptotic\:permeability\:\left(mD\right)$$ $$\:{K}_{0}:Fixed\:initial\:permeability$$ $$\:t:Exposure\:time\:\left(days\right)$$ $$\:\tau\::Decay\:time\:constant\:\left(days\right)$$ The global permeability relative uncertainty is up to 6.3%. It is dominated by viscosity as water temperature after flooding may not be consistently up to the desired temperature during the permeability test. It contributes to 80% to the measurement uncertainty). The reading pressures (± 0.1%), flow rates, and sample dimensions barely matter in comparison (less than 2.6% relative uncertainty impact on the measurement). 3. Results 3.1. Replica experiment (0.05 cc/min) Replication experiments with a similar protocol to Zhai et al. ( 2020 ) have been carried out to investigate the microbubble injection potential on high-permeability samples. Microbubble and conventional injection flooding have been carried out the Berea sample BO5. Results are expressed in a violin plot (Fig. 4 ). The mean steady state CO₂ saturation is higher for microbubble injection by 8.89%. Saturation distributions and their error bars overlap substantially. Conventional flooding results are mostly clustered around 25%, whereas microbubble injection tends to show values closer to 45%. As per their respective saturation curves, examples of the ΔP variation along with sample CO₂ saturation from effluent collection are displayed in Fig. 5 . The CO₂ saturations curves are mostly subdivided in two zones: A sharp almost-linear increase and a plateau with little episodic increases. There are a few differences between injection types ; the saturation gradient seems to be slower in the conventional case. The remarkable detail is a ΔP up to 3 times higher in the microbubble than conventional injection. It is partly due to the presence of the filter, which has a significantly lower permeability than the sample itself. 3.2. Sequential flowrate tests Sequential tests have been performed on BO3 sample to test microbubble sensitivity to injection rate. Four tests have been carried out for each injection type. They have been compiled in three violin plots to understand their distribution. The first stage, like replication experiments (Fig. 6 ), shows a clear and drastic distinction of saturations between conventional and microbubble injection. The microbubble saturations are more spread, and in globality always lower than conventional, with a difference of 25.7% CO₂ on average. In the case of the later stages of sequential injection (Fig. 7 ). Distributions are in this case clearly more in favour of conventional injection, where microbubble injection’s mean saturations are lower by 13.43% and 9.98% for 0.1 and 0.5 cc/min respectively. Microbubble saturation performance at higher flowrates has narrowed the gap with conventional injection, the saturation difference at 0.05 cc/min has partially faded. The performed reference floodings show the importance of the flooding protocol on saturations. They show an advantage of microbubbles over a large difference (respectively 31.66 and 13.9% for 0.1 and 0.5 cc/min). 3.3. Sequential tests permeability monitoring Brine Permeability results are shown in Fig. 8 . Data from microbubble injection is up to test 28 as the permeability has been recorded but does not evolve from there. They record the permeability evolution of BO3 during its exposure to CO₂ floodings. Curve fitting equally shows a decay rate difference four times higher for microbubble in comparison to conventional. 4. Discussion 4.1. Filter impact on pressure and global permeability Microbubble floodings are characterized by a significant higher-pressure difference between inlet and outlet. Figure 5 has shown a 3 times higher pressure difference between microbubble and conventional injection. Microbubbles effect on pressure is documented: Their small size or their collection can cause pore plugging (Le et al., 2022 ; Telmadarreie et al., 2016 ). It is important to note that the microbubble experiments employed a filter with permeability far lower than that of the Berea sandstone core. As a result, the pressure drop in the microbubble experiments is dominated by the filter rather than the rock. Therefore, ΔP values between microbubble and conventional injections cannot be directly compared, and the observed higher ΔP in microbubble tests does not reflect primarily microbubble–rock resistance but the hydraulic limitation of the filter. Interpretation of pressure signals must therefore be restricted to within-experiment trends rather than cross-mode comparisons. To allow such comparison, a separated generation device would be required to separate both phenomena. Both conventional and microbubble injection saturation curves are distinguished by their absence of transition zone. Under capillary-dominated conditions (low capillary number), displacement is controlled by pore-scale capillary entry pressures, leading to sharp invasion fronts and saturation gradients that may be unresolved at the experimental scale (Blunt, 2017 ). 4.2. Flow Rate–Dependent Performance of Microbubble Injection Our volume-balance core flooding experiments on high-permeability Berea sandstone (~ 980 mD) reveal a strong dependence of microbubble efficacy on injection flow rate. At the lowest tested rate (0.05 cc/min), microbubble injection increases average CO₂ saturation by 8.89% on average relative to conventional injection, a modest but statistically discernible improvement consistent with prior studies in high-permeability media (Wang et al., 2025b ; Zhai et al., 2020 ). This enhancement is likely due to Jamin effect: microbubbles temporarily block high-permeability pathways, diverting flow into less-swept intermediate pores and improving displacement efficiency. However, this advantage vanishes at higher flow rates (0.1–0.5 cc/min), where conventional outperforms microbubble injection by 14–10% in final saturation. At these rates, the added hydraulic resistance from the microbubble generation filter (which increases ΔP by up to 4 times; Fig. 5 ) may exacerbate preferential flow along dominant channels, worsening sweep uniformity. These findings indicate that the benefits from low-flow laboratory studies may not be directly applicable by extrapolation to field-scale injection scenarios, where near-wellbore flow rates are typically much higher, and suggest the need for further research under higher flow rates considering practical operation. Microbubble injection is significantly affecting the flow, for better or worse. The filter permeability is much smaller than the sample permeability, inducing a stronger ΔP, which induces microbubble smaller saturation results. At the investigated flow rates (0.05–0.5 cc/min), the experiments remain within a capillary-dominated regime. However, in high-permeability samples, the characteristic capillary pressure contrast between large and small pores is small. This reduces the stabilizing effect of capillary forces on the displacement front. Under these conditions, CO₂ invasion becomes highly sensitive to pore-network geometry, connectivity, and experimental layout. Consequently, small differences in sample heterogeneity or injection sequence can lead to markedly different saturation outcomes, as observed between BO3 and BO5. For the sequential injection protocol, microbubble injection offers worse results than conventional. Whereas floodings from full saturation show the opposite trend. CO₂ microbubbles can be hypothesised as being generated on the first injected volumes, as water is available in the filter’s pores. However, It can be inferred that once CO₂ breaks through the filter, the conditions for microbubble generation are no longer met, resulting in few to none being created. This shows the need for CO₂ to be co-injected in the brine to effectively work after filter breakthrough, which has not been done in many publications (Jiang et al., 2019 ; Park et al., 2018 ; Patmonoaji et al., 2019 ; Wang et al., 2022 ; Xue et al., 2014 ; Zhai et al., 2020 ). 4.3 Saturation Variability and Sample History Effects Saturation distributions show a widespread distribution, going above the expected variance by 3.24% for conventional and 4.28% for microbubble injection on average. Microbubble having a larger variance due to experimental setup, one cannot conclude on a higher variability caused by microbubble injection itself. The permeability monitored sample (BO3) shows a gradual permeability decay which suggests a high pore space alteration due to chemical reactions or other mechanical effects (Fig. 8 ). The saturation results spread could be caused by several mechanisms in action in these experiments: The use of high-permeability samples, where their flow dynamics can be very variable from one flooding to another due to potential channelling effects (Tawiah et al., 2021 ). Progressive geochemical alteration of the core due to repeated CO₂ exposure. Even after brine re-saturation between floods, residual acidic brine and dissolved CO₂ may persist in pore spaces, altering wettability or precipitating secondary minerals (Zhao et al., 2015 ). Over successive cycles, this can reduce effective porosity and shift capillary pressure curves, leading to inconsistent displacement behaviour. Heterogeneity in microbubble generation and transport. The mechanical filter produces a polydisperse bubble population whose size distribution may vary slightly between runs. In high-permeability media, where pore-throat sizes exceed typical microbubble diameters (1–50 µm), minor changes in bubble size or concentration can significantly affect plugging dynamics and sweep pathways. Overall, these observations highlight the value of repeated-flood laboratory studies in capturing cumulative effects that may not be apparent in single-injection experiments, but which are likely to play an important role during prolonged CO₂ injection under field-scale operating conditions. 4.4 Sample alteration Brine permeability monitoring shows a different aspect of the multiple flooding cycles dynamic: The decay of the BO3 sample follows a single exponential with asymptote model. When identifying the decay time constant, microbubble injection has a higher value compared to conventional (≈ 4 times higher), showing a potentially higher reactivity and sample decay. Microbubbles have a larger surface area and can dissolve in the brine at a faster rate (Xue et al., 2011 ). While dissolution can initially increase porosity, it often leads to pore collapse, fines mobilisation, or clay swelling, ultimately reducing permeability (Bhuvankar et al., 2023 ; Xu et al., 2004 ). On a field scale, prolongated injection can cause injectivity issues due to CO₂-brine rock interactions altering the pore structures to diminish the pore throat radius (Zhao et al., 2015 ). Critically, this effect is most pronounced in the near-wellbore region, where CO₂ concentration and contact time are highest, which is precisely the zone governing injectivity in field operations. Thus, while microbubble injection may improve storage efficiency in the far field, a potential challenge is the long-term maintenance of well injectivity. A multiple flooding approach with monitoring of permeability allows for a better estimation of the field expected saturation, as well as its potential to decay in permeability due to the presence of CO₂. Nonchemical microbubble injection is a technique that presents an economical interest in applying it to large scale due to its simple generation and reliance on self-stability. 4.3 Study limitations This study suffers from several limitations: The Buffi Berea sandstone studied here has high permeability which has a few comparison points with current literature on microbubble injection. The large gap between variance and absolute uncertainty for CO₂ saturations given for each flowrate makes it difficult to conclude on a definite number. The pressure drop between conventional and microbubble injection is not perfectly understood and comparable. The current setup is not able to separate the action of the filter and the microbubble flow on the ΔP. The pressure difference curves are influenced by the back pressure regulator behaviour. It creates artifacts, mainly pressure bumps, caused by the difficulty of the regulator to stabilise CO₂-brine flow. The data given by low flowrate (0.05cc/min) sequential tests (on sample BO3) does not match previous data on replication floodings (BO5), which can reveal a sample dependency on results. The BO3 core experienced several consecutive CO₂ floods, so the observed permeability decay accumulates over time and cannot be attributed uniquely to the injection mode. The fitted decay time constant appears higher during microbubble injection; this should not be taken as a definite proof of enhanced chemical reactivity driven specifically by microbubbles. The microbubble filter may introduce hydraulic resistance or host geochemical alteration, adding uncertainty to the decay trend. The apparent difference in decay rates suggests only a possible tendency rather than a microbubble-specific mechanism. Further tests on fresh cores without filters are necessary to draw mechanistic conclusions. 5. Conclusion Microbubble CO₂ injection is an emerging injection technique, predominantly investigated through mechanical generation using microporous filters at different injection rate protocols. Conclusions are listed below: The replication experiments (0.05cc/min) show disparate results between samples. Microbubble injection is likely to perform better on average, shown by a mean of 37.00% in comparison to 28.11% for conventional on the BO5 sample. However, the BO3 sample shows an opposite trend, where conventional is advantaged by 25.72% in CO₂ saturation compared to microbubble injection. Overall, many factors such as the high permeability, sample heterogeneity and sample gradual change during experiments might explain these results. Higher injection flowrates in sequential injection are globally advantageous to conventional injection. Reference floodings done from complete water saturation (reference floodings) show an opposite trend to sequential injection, where conventional performs less than microbubble. This could be explained by the need of a water phase for microbubbles to be generated. This supports the need for co-injection on the field scale. All tests are affected by an important standard deviation in comparison to the expected variance, in particular with microbubble injection (conventional: 3.24%, microbubble: 4.28%). The difference is however not large enough to be conclusive. The optimal flowrate and ratio for microbubble injection are still to be found and optimised. The sample BO3 brine permeability has been monitored before every flooding. The permeability has drastically decreased along all the observed floodings from 955.318 mD to 288.2 mD. Single exponential with asymptote fits on separated conventional and microbubble injection data shows a much higher characteristic decay time τ for microbubble injection. A higher permeability decay for microbubble injection warrants further investigation. Finally, these results support the broader conclusion of the study: while previous work on microbubble CO₂ largely focused on low-permeability formations has shown consistent improvements in sweep and trapping, our experiments demonstrate that in high-permeability systems, MB CO₂ behaviour is strongly rate-dependent and may lead to injectivity difficulties under certain conditions. Sequential flooding allows us to capture cumulative and rate-sensitive effects, providing realistic insight into potential trade-offs for CCS deployment. While microbubble CO₂ is beneficial in low-rate or far-field regions, it may pose near-wellbore injectivity difficulties. These findings underscored the need for further research under higher flow rates considering practical operation, and emphasising the need for careful rate optimisation, injection design, and long-term integrity assessment. Declarations Consent to publish Not applicable Consent to Participate Not applicable Competing Interests Theo Le Gallais reports that financial support was provided by Tokyo Gas Australia Pty Ltd. His tuition fees for PhD candidacy have been off-set by Curtin University.The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding declaration The research included in this paper was funded by Tokyo Gas Australia Pty Ltd. Curtin University has off-set the tuition fees of PhD candidates involved in the project. Author Contribution Theo Le Gallais : Conceptualization, methodology, investigation, data curation, formal analysis, writing - original draftEgi Adrian Pratama: Investigation, formal analysis, writing - review & editingKlaus Regenauer-Lieb, Mohammad Sarmadivaleh : Writing - review & editing, supervisionAli Saeedi: Methodology, supervision, review & editingQuan Xie: Writing - review & editingHideto Kurokawa: Writing - review & editing Acknowledgement The authors would like to deeply thank the contribution of Tokyo Gas and RITE for their continuous support and also in providing the microbubble generation filters used in this study. Data Availability The data that support the findings of this study are available from the corresponding authors upon reasonable request. References Aizawa Y, Baba Y, Xue Z. (2021). Microbubble CO2 Injection for Geological Sequestration in Tight Sandstone Reservoirs. Proceedings of the 15th Greenhouse Gas Control Technologies Conference 15–18 March 2021 . https://ssrn.com/abstract=3811393 Bhuvankar P, Cihan A, Birkholzer JT. (2023). Pore-Scale Analysis of the Permeability Damage and Recovery during Cyclic Freshwater and Brine Injection in Porous Media Containing Non-Swelling Clays. Energies, 16 (22). Blunt MJ. Multiphase Flow in Permeable Media: A Pore-Scale Perspective. Cambridge University Press; 2017. https://doi.org/DOI. Borisova EA, Adler PM. Deposition in porous media and clogging on the field scale. Phys Rev E. 2005;71(1):016311. https://doi.org/10.1103/PhysRevE.71.016311 . Dubey S, Majumder SK. (2024). Stability analysis of CO2 microbubble for CO2 sequestration and mobility control in enhanced oil recovery. Chemical Engineering Journal , 500 . https://doi.org/10.1016/j.cej.2024.156595 Hall C. (2025). Reactive transport in cement-based materials (Hall’s Notes and Queries, Issue. https://blogs.ed.ac.uk/christopherhall/wp-content/uploads/sites/6693/2025/09/NQ11.pdf IEA. (2020). Energy Technology Perspectives 2020 . IPCC. (2023). Climate Change 2023: Synthesis Report. IPCC . https://doi.org/https://dx.doi.org /10.59327/IPCC/AR6-9789291691647.001 Jia H, Yu H, Wang S, Shi J, Xie F, Wang S, Lu J, Wang Y, Zhang F. Investigation of CO2 microbubble assisted carbon sequestration and gravity-induced microbubble ripening in low permeability reservoirs. Appl Energy. 2024;373. https://doi.org/10.1016/j.apenergy.2024.123954 . Jia H, Yu H, Xie F, Yuan Z, Xu K, Wang Y, RESEARCH ON CO2 MICROBUBBLE DISSOLUTION KINETICS AND ENHANCED OIL RECOVERY MECHANISMS. Chin J Theoretical Appl Mech. 2023;55(3):755–64. https://doi.org/https://doi.org/10.6052/0459-1879-22-507 . Jiang L, Xue Z, Park H. Enhancement of CO2 dissolution and sweep efficiency in saline aquifer by micro bubble CO2 injection. Int J Heat Mass Transf. 2019;138:1211–21. https://doi.org/10.1016/j.ijheatmasstransfer.2019.04.139 . Le NNH, Sugai Y, Vo-Thanh H, Nguele R, Ssebadduka R, Wei N. Experimental investigation on plugging performance of CO2 microbubbles in porous media. J Petrol Sci Eng. 2022;211. https://doi.org/10.1016/j.petrol.2022.110187 . Li S, Wang X, Wang S, Zhang Y, Chen C, Jiang L, Wang L, Liang F, Sun H, Song Y. Optimizing oil recovery with CO2 microbubbles: A study of gas composition. Energy. 2024;302. https://doi.org/10.1016/j.energy.2024.131836 . Li X, Peng B, Liu Q, Liu J, Shang L. Micro and nanobubbles technologies as a new horizon for CO2-EOR and CO2 geological storage techniques: A review. Fuel 341. 2023. https://doi.org/10.1016/j.fuel.2023.127661 . Li X, Wang Y, Zeng B, Li Y, Tan H, Zandvliet HJW, Zhang X, Lohse D. Entrapment and Dissolution of Microbubbles Inside Microwells. Langmuir. 2018;34(36):10659–67. https://doi.org/10.1021/acs.langmuir.8b02173 . Mahjour SK, Faroughi SA. (2023). Risks and uncertainties in carbon capture, transport, and storage projects: A comprehensive review. Gas Science and Engineering , 119 . https://doi.org/10.1016/j.jgsce.2023.205117 Noiriel C. Resolving Time-dependent Evolution of Pore-Scale Structure, Permeability and Reactivity using X-ray Microtomography. Rev Mineral Geochem. 2015;80(1):247–85. https://doi.org/10.2138/rmg.2015.80.08 . Park H, Jiang L, Kiyama T, Xue Z. Experimental Study of Microbubble CO2 Flooding in Heterogeneous Sedimentary Rock. SSRN Electron J. 2018. https://doi.org/10.2139/ssrn.3365701 . Patmonoaji A, Zhang Y, Xue Z, Park H, Suekane T. Experimental and numerical simulation of supercritical CO2 microbubble injection into a brine-saturated porous medium. Int J Greenhouse Gas Control. 2019;91. https://doi.org/10.1016/j.ijggc.2019.102830 . Rogers PSZ, Pitzer KS. Volumetric Properties of Aqueous Sodium Chloride Solutions. J Phys Chem Ref Data. 1982;11(1):15–81. https://doi.org/10.1063/1.555663 . Tawiah P, Wang H, Bryant SL, Dong M, Larter S, Duer J. Effects of temperature and CO2/Brine cycles on CO2 drainage endpoint phase mobility – implications for CO2 injectivity in deep saline aquifers. Int J Greenhouse Gas Control. 2021;112. https://doi.org/10.1016/j.ijggc.2021.103491 . Telmadarreie A, Doda A, Trivedi JJ, Kuru E, Choi P. CO2 microbubbles – A potential fluid for enhanced oil recovery: Bulk and porous media studies. J Petrol Sci Eng. 2016;138:160–73. https://doi.org/10.1016/j.petrol.2015.10.035 . Ueda R, Nakano M, Xue Z. The efforts for the application of micro bubble technology to CCS and EOR. J Japanese Association Petroleum Technol. 2021;86(2):94–104. https://doi.org/10.3720/japt.86.94 . Wang D, Fan J, Xue Z. Hydrodynamic Analysis of CO2 Migration in Heterogeneous Rocks: Conventional and Micro-Bubble CO2 Flooding Experiments and Pore‐Scale Numerical Simulations. Water Resour Res. 2022;58(5). https://doi.org/10.1029/2021wr031874 . Wang S, Zhang G, Lv P, Wang Z, Jiang L, Zhu L, Song Y. Accelerating CO2 Dissolution Trapping in Deep Saline Aquifers through a Microbubble Injection Strategy. Energy Fuels. 2025b;39:3217–25. https://doi.org/https://doi.org/10.1021/acs.energyfuels.4 . c05889?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as. Xu T, Apps JA, Pruess K. Numerical simulation of CO2 disposal by mineral trapping in deep aquifers. Appl Geochem. 2004;19(6):917–36. https://doi.org/https://doi.org/10.1016/j.apgeochem.2003.11.003 . Xue Z. Field Application of Microbubble CO2 Injection for Enhanced Storage Efficiency in a Tight Sandstone Reservoir. SSRN Electron J. 2021. https://doi.org/10.2139/ssrn.3811983 . Xue Z, Matsuoka T. Lessons from the First Japanese Pilot Project on Saline Aquifer CO2 Storage. Chigaku Zasshi (Jounal Geography). 2008;117(4):734–52. https://doi.org/10.5026/jgeography.117.734 . Xue Z, Nishio S, Hagiwara N, Matsuoka T. Microbubble Carbon Dioxide Injection for Enhanced Dissolution in Geological Sequestration and Improved Oil Recovery. Energy Procedia. 2014;63:7939–46. https://doi.org/10.1016/j.egypro.2014.11.828 . Xue Z, Park H, Ueda R, Nakano M, Nishii T, Inagaki S. Microbubble CO2 Injection for Enhanced Oil Recovery and Geological Sequestration in Heterogeneous and Low Permeability Reservoirs. SSRN Electron J. 2018. https://doi.org/10.2139/ssrn.3366428 . Xue Z, Tsuji S, Kameyama H, Nishio S, Matsuoka T. Development of Carbon Dioxide Microbubble Sequestration into Saline Aquifer and CO2-EOR Reservoirs. Energy Procedia. 2013;37:4628–34. https://doi.org/https://doi.org/10.1016/j.egypro.2013.06.371 . Xue Z, Yamada T, Matsuoka T, Kameyama H, Nishio S. Carbon dioxide microbubble injection–Enhanced dissolution in geological sequestration. Energy Procedia. 2011;4:4307–13. https://doi.org/10.1016/j.egypro.2011.02.381 . Yu Y, Beddoe C, Xue Z, Chakhmakhchev A, Hamling J, Smith S, Kurz B. (2022). Experimental evaluation of enhanced tight oil recovery performance by microbubble CO2 and microbubble rich gas in North Dakota plays. Unconventional Resources Technology Conference, 20–22 June 2022 . https://doi.org/https://doi.org/10.15530/urtec-2022-3694645 Zhai H, Xue Z, Park H, Aizawa Y, Baba Y, Zhang Y. Migration characteristics of supercritical CO2 microbubble flow in the Berea sandstone revealed by voxel-based X-ray computed tomography imaging analysis. J Nat Gas Sci Eng. 2020;77. https://doi.org/10.1016/j.jngse.2020.103233 . Zhang H, Arif M. Residual trapping capacity of subsurface systems for geological storage of CO2: Measurement techniques, meta-analysis of influencing factors, and future outlook. Earth Sci Rev. 2024;252. https://doi.org/10.1016/j.earscirev.2024.104764 . Zhao DF, Liao XW, Yin DD. An experimental study for the effect of CO2-brine-rock interaction on reservoir physical properties. J Energy Inst. 2015;88(1):27–35. https://doi.org/10.1016/j.joei.2014.05.001 . Additional Declarations Competing interest reported. Theo Le Gallais reports that financial support was provided by Tokyo Gas Australia Pty Ltd. His tuition fees for PhD candidacy have been off-set by Curtin University.The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8879243","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600435316,"identity":"67b8ab37-17da-41f8-93f8-ad2b1d1d4b7e","order_by":0,"name":"Theo Le Gallais","email":"data:image/png;base64,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","orcid":"","institution":"Curtin University","correspondingAuthor":true,"prefix":"","firstName":"Theo","middleName":"Le","lastName":"Gallais","suffix":""},{"id":600435317,"identity":"61860d79-e1fb-4968-b9a5-c000b140766b","order_by":1,"name":"Egi Adrian Pratama","email":"","orcid":"","institution":"Curtin University","correspondingAuthor":false,"prefix":"","firstName":"Egi","middleName":"Adrian","lastName":"Pratama","suffix":""},{"id":600435318,"identity":"a6e405cb-79b6-4f30-a2a3-cf5d1965d689","order_by":2,"name":"Klaus Regenauer-Lieb","email":"","orcid":"","institution":"Curtin University","correspondingAuthor":false,"prefix":"","firstName":"Klaus","middleName":"","lastName":"Regenauer-Lieb","suffix":""},{"id":600435319,"identity":"96740e41-fc39-4f21-b87a-03aee57371c2","order_by":3,"name":"Mohammad Sarmadivaleh","email":"","orcid":"","institution":"Curtin University","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Sarmadivaleh","suffix":""},{"id":600435320,"identity":"babd85ee-ae66-4fae-bae4-be704f8793fb","order_by":4,"name":"Ali Saeedi","email":"","orcid":"","institution":"Curtin University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Saeedi","suffix":""},{"id":600435321,"identity":"ff6f02c9-7d0a-4fb1-bc31-1af4e35a2c5e","order_by":5,"name":"Quan Xie","email":"","orcid":"","institution":"Curtin University","correspondingAuthor":false,"prefix":"","firstName":"Quan","middleName":"","lastName":"Xie","suffix":""},{"id":600435322,"identity":"f2d8710c-c853-40f6-b3b4-66ee486b34fd","order_by":6,"name":"Hideto Kurokawa","email":"","orcid":"","institution":"Tokyo Gas (Australia)","correspondingAuthor":false,"prefix":"","firstName":"Hideto","middleName":"","lastName":"Kurokawa","suffix":""}],"badges":[],"createdAt":"2026-02-14 10:38:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8879243/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8879243/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104062932,"identity":"75581562-21e2-4d55-ae6f-429921dbbf17","added_by":"auto","created_at":"2026-03-06 10:03:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29279,"visible":true,"origin":"","legend":"\u003cp\u003eMean post flood steady state saturation difference (microbubble saturation improvement) over studied sample permeability observed among current flooding studies of microbubble CO₂ injection on sandstone samples in the literature. Triangles: Literature. Diamond: This study. Literature references used : Aizawa et al. (2021); Jia et al. (2024); Jiang et al. (2019); Park et al. (2018); Patmonoaji et al. (2019); Wang et al. (2022); Wang et al. (2025b); Xue et al. (2014); Xue et al. (2018); Xue et al. (2013); Zhai et al. (2020). Xue et al. (2014) and Xue et al. (2013). Aizawa et al. (2021) reports a difference between microbubble and conventional injection to be within 5%, which has been assumed in favour of microbubbles and overall, 2.5% displayed on the graph. The shaded region highlights the trend of greater MB efficacy in high-permeability media.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/5f4c156b906ab35952a5d222.png"},{"id":104062931,"identity":"926e6cd7-8eda-46bb-91e5-a175dd8ba547","added_by":"auto","created_at":"2026-03-06 10:03:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1010607,"visible":true,"origin":"","legend":"\u003cp\u003eVolume balance core flooding setup. a) Setup diagram. b) Setup photo: A-B) Vinci double pump. C) Confining pressure pump. D) Back pressure pump. d-e) Accumulator and heating tape. f) Circulation pump. g)pressure transducer (back pressure showed). h) Back pressure regulator.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/c5c4d62a301e5b3b018e7699.png"},{"id":104403003,"identity":"e17cd1cf-86fe-4d84-9896-7cf4717ec77f","added_by":"auto","created_at":"2026-03-11 12:17:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1355858,"visible":true,"origin":"","legend":"\u003cp\u003eHigh-permeability Berea sandstone core samples photo. a) BO3. b)BO5.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/8c00eda2bf6f736b97db2c46.png"},{"id":104402408,"identity":"c6ac712f-14d6-4104-b007-507e113d65b8","added_by":"auto","created_at":"2026-03-11 12:15:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":63261,"visible":true,"origin":"","legend":"\u003cp\u003eViolin plots of CO₂ saturation results from replica experiments of Zhai et al. (2020)protocol (0.05cc/min) based on 5 floodings for each injection type. The mean, standard deviation and expected variance of each dataset is in black. Diamonds: data points. White line: median. Microbubble yields an average saturation 8.89% higher than conventional.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/72844f1c649f699588216d6b.png"},{"id":104403064,"identity":"64876ffb-3409-41b1-a78d-d5581e3892e7","added_by":"auto","created_at":"2026-03-11 12:17:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":99977,"visible":true,"origin":"","legend":"\u003cp\u003eΔP and saturation curve examples in the volume balance core flooding replicas of Zhai et al. (2020). Orange dots: CO₂ saturation (%). Blue curve: Sample pressure difference (psi). Test no 5 is showing conventional injection trend. Test 7 is showing microbubbles injection trend.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/26739839ab892d9f3093bd5b.png"},{"id":104403326,"identity":"b3f17048-b2cc-40e9-96e1-fb7bcc1b3011","added_by":"auto","created_at":"2026-03-11 12:18:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":119298,"visible":true,"origin":"","legend":"\u003cp\u003eViolin plots of CO₂ saturation results for the BO3 sample from the first stage of sequential injection (0.05cc/min). The mean, standard deviation and expected variance of each dataset is in black. Diamonds: data points.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/97f8fd8fc54fc8a1565a6915.png"},{"id":104403315,"identity":"10edcbbc-25b6-486d-aaa4-064440c1833f","added_by":"auto","created_at":"2026-03-11 12:18:01","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110109,"visible":true,"origin":"","legend":"\u003cp\u003eViolin plot of CO₂ saturation results at 0.1 and 0.5 cc/min CO₂ for conventional and microbubble injection. The mean, standard deviation and expected variance of each dataset is in black. Black hollow diamonds: Reference floodings from zero. Blue and orange diamonds: data points.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/2436e3700b4a43ba0ea7afa4.png"},{"id":104062936,"identity":"f841440d-f21c-49e6-b9ec-71a5017ee5c2","added_by":"auto","created_at":"2026-03-06 10:03:48","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":60509,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of brine permeability in Berea sample B03 over sequential CO₂ floods. Microbubble injection causes a fourfold faster permeability decline than conventional injection, fitted with a single exponential with asymptote model.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/48d7c84a2e40d7979d737204.png"},{"id":108602622,"identity":"e29142bf-10dc-4cf6-9858-d46a7bb4272f","added_by":"auto","created_at":"2026-05-06 11:43:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3254772,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8879243/v1/e2a4b537-4ae1-411d-bf4a-9aa1aa5b1f90.pdf"}],"financialInterests":"Competing interest reported. Theo Le Gallais reports that financial support was provided by Tokyo Gas Australia Pty Ltd. His tuition fees for PhD candidacy have been off-set by Curtin University.The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","formattedTitle":"Microbubble CO₂ Injection in High- Perm Sandstone: Flow-Rate Effects and Permeability Decay","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCarbon dioxide is the principal emitted greenhouse gas responsible for unprecedented fast climate change. It is the co-product of every industry sector at the society\u0026rsquo;s base and more globally, from every main source of energy used by mankind (IPCC, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moderating emissions is a current challenge that will persist in the next decades. Carbon capture, utilization and storage is considered a major actor in the transition to net-zero carbon by 2050 (IEA, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Particularly, carbon storage is a major challenge in economic scales: Building a storage project includes many safety considerations with relative uncertainties (Mahjour \u0026amp; Faroughi, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicrobubble CO₂ is a new injection method that may be used in all storage settings. It has mainly been studied as displacing liquid for Enhanced Oil Recovery (EOR) (Xue et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This technology benefits from a higher oil recovery by reducing entry capillary pressure (Li et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). By being able to penetrate smaller pores, CO₂ microbubble also implies a lower injectivity overall. Microbubbles can plug the main pathways, allowing flow through the smallest pores (Yu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), resulting in a higher ΔP. This injection type has also been shown to be effective in aquifer settings as there is also potential for a more efficient storage. In these particular settings, microbubble injection has been mainly studied in a high salinity environment (Jiang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Patmonoaji et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Overall, microbubble injection has a potential for a higher sweep efficiency, higher dissolution rate and a slower CO₂ plume rising velocity (Li et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe current state of the art in microbubble injection applied to laboratory-scale core flooding tests performed in deep saline aquifer conditions demonstrates a relative increase in average CO₂ saturation at the steady state. This improvement is attributed to the addition of a microbubble generation filter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All values within sandstone rock samples never go above 20% increase in CO₂ saturation and on average 6.2%. Mainly Berea sandstone is used as test sample in literature floodings. Interestingly, it shows disparate results on the most tested permeability: 100 mD. Samples done in rock cores show an average of 0 to 5% improvement thanks to microbubble injection.\u003c/p\u003e \u003cp\u003eOverall, a trend is showing up, where higher permeability samples have more potential to have better results with microbubble injection. This could be explained by the \u0026ldquo;Jamin effect\u0026rdquo;, detailed in publications (Dubey \u0026amp; Majumder, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Le et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Telmadarreie et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Jia et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) observed on microchips large channels plugged by microbubbles, which allowed smaller pores to be penetrated. A microbubble or a swarm of microbubbles with a larger diameter to the pore can block it and create a local higher pressure. CO₂ can then reach pores that required a higher capillary entry pressure to be swept. In the case of high-permeability sandstone samples, they possess high-diameter channels through which CO₂ can easily transit. Microbubble CO₂ agglomerates can temporarily plug them and allow other smaller channels to be penetrated.\u003c/p\u003e \u003cp\u003eFrom literature results, it can be noted that floodings on cores with a similar permeability may not obtain similar CO₂ saturation results. In fact, the relation between permeability and final CO₂ saturation after drainage is complex and no direct relation exists between them (Zhang \u0026amp; Arif, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the microbubble effect on sweep efficiency and injectivity appears to depend on permeability, which can be seen from the correlation shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The effectiveness of microbubble injection can vary significantly, as the way microbubbles move through the rock may lead to inconsistent blockage; in addition, microbubbles of different sizes may interact with and block different pore spaces during each injection. Literature results also employed different salinities, ranging from 0.58 (Xue et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) to 187 g/L eqNaCl (Jiang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Patmonoaji et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) which may have an impact on microbubble generation and flood.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe physical properties of microbubbles lead to improvements in sweep efficiency, injectivity and dissolution rate, as seen in the literature (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Patmonoaji et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ueda et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Xue, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xue \u0026amp; Matsuoka, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Xue et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Xue et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Xue et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, other effects of microbubbles could be considered and have the potential to antagonise the previously mentioned mechanisms. In near-wellbore environments, where the rock is exposed to high concentrations of CO₂ during injection, the fast dissolution of microbubbles can cause the surrounding brine to become acidic more quickly. This can accelerate the dissolution of minerals and chemical reactions within the pore spaces of the rock. Moreover, microbubbles negative charges on their boundaries could interact with clay particles and cause swelling. Overall, all these effects could cause fines migration and faster rock decay.\u003c/p\u003e \u003cp\u003eMost comparative laboratory tests have relied only on a single flowrate per experiment, which does not reflect real field conditions where the injection rate tends to be variable. Microbubble injection studies on a flowrate comparison point have noticed significant differences in results (Le et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). In the case of Wang et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e), 0.05 cc/min on a standard syringe pump injection is seen as the most optimal case for microbubble injection. However, this injection flowrate on a closer reservoir is not to be expected but at least a hundred meters from the well in medium-sized projects. Economic viability is also unlikely if microbubbles must be generated at such a low rate, as it is insufficient for the field. Sequential flooding is used in this study to investigate microbubble injection rate sensitivity ; the effects on saturation and global microbubble behaviour are discussed.\u003c/p\u003e \u003cp\u003eThis study investigates whether microbubble injection improves CO₂ saturation in high-permeability rocks, using CO₂ flooding experiments on Buffi Berea sandstone with a permeability of ~\u0026thinsp;1000 mD. The flooding protocol of Zhai et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) was replicated at a flow rate of 0.05 cc/min on one sample (BO5). A second sample (BO3) was subjected to sequential CO₂ injections at increasing flow rates (0.05, 0.1, and 0.5 cc/min) to evaluate how changes in injection rate influence steady state saturations relative to conventional injection. The impact of microbubble injection on permeability reduction was investigated by monitoring brine permeability after the initial imbibition, for both conventional and microbubble injection, using sample BO3. To the best of our knowledge, this is the first study to systematically quantify flow-rate\u0026ndash;dependent microbubble CO₂ behaviour and permeability decay in high-permeability sandstone under repeated injection cycles. By comparing microbubble and conventional CO₂ injection across sequential flow rates, we capture both efficiency gains and integrity losses. The findings provide insight directly relevant to CO₂ subsurface utilisation and geological storage operations.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eVolume balance core flooding is a technique that measures the water volume output from the sample at all times during the CO₂ injection experiment. By subtracting the volume contained in the tubing (dead volume), the sample\u0026rsquo;s global CO₂ saturation can be estimated. CO₂ saturation calculation from volume change is detailed:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{S}_{g}=\\frac{{V}_{observed}-{V}_{dead\\:volume}}{{V}_{pore}}*100\\:\\left(\\%\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{S}_{g}:\\:{CO}_{2}\\:gas\\:saturation\\:\\left(\\%\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{V}_{observed}:Observed\\:water\\:volume\\:in\\:cylinder\\:\\left(ml\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:{V}_{dead\\:volume}:Dead\\:volume\\:\\left(ml\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$\\:{V}_{pore}:Connected\\:pore\\:volume\\:in\\:Core\\:\\left(supposed\\:100\\%\\:filled\\:with\\:brine\\:after\\:saturation\\right)\\:\\left(ml\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eDead volume was measured previous to the flooding. The core holder is empty, and sleeves are connected directly. Water was injected until the tubing becomes full. Air is then injected to chase the water and recover the corresponding volume. This process has been done 20 times to ensure consistency of the dead volume. Experiments volumes are corrected by the dead volume, and the time is corrected to match zero when the dead volume has been reached.\u003c/p\u003e \u003cp\u003eDead volume and cylinder measurements uncertainties resulted in an absolute uncertainty of 1.39% to 5% in CO₂ saturation depending on the used setup layout at the time of the experiment. It is mainly dependent on the standard deviation obtained through dead volume measurements (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Cylinder readings also introduce a volume measurement error of \u0026plusmn;\u0026thinsp;0.25 ml. For microbubble tests, the filter pore volume was not sufficient to notice a significant dead volume measurement change. Therefore, similar dead volume measurements have been taken for both injection types. In all shown experiments, the mean value and standard deviation have been taken as the output results of a given setting.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAbsolute uncertainty associated with dead volume and measuring cylinder.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsolute uncertainty (%CO₂)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u0026ndash;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u0026ndash;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese absolute uncertainties are expected to be found on the measured dataset; they are averaged to compute an expected variance and compared to the measured data.\u003c/p\u003e \u003cp\u003eUpon discharge from the back-pressure regulator, the brine undergoes two competing volumetric effects: expansion associated with pressure release and contraction associated with cooling. Upper-bound estimates of these effects were evaluated. Isothermal decompression of a 12.5 wt% NaCl brine from 10 MPa to 0.1 MPa at 40\u0026deg;C results in a volumetric expansion of approximately\u0026thinsp;+\u0026thinsp;0.36%, based on an isothermal compressibility of 3.64 \u0026times; 10⁻\u0026sup1;⁰ Pa⁻\u0026sup1;. The concurrent cooling of the brine from 40\u0026deg;C to 25\u0026deg;C produces a volumetric contraction of approximately\u0026thinsp;\u0026minus;\u0026thinsp;0.6%, using an average volumetric thermal expansivity of 4.085 \u0026times; 10⁻⁴ K⁻\u0026sup1; over this temperature interval. Values for brine compressibility and thermal expansivity were taken from Rogers and Pitzer (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1982\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe combined effect of decompression and cooling therefore corresponds to a net volumetric decrease of approximately 0.24%, equivalent to 0.048 mL for a nominal volume of 20 mL, representing the maximum recoverable volume. This correction is significantly smaller than the uncertainty associated with dead-volume estimation and volumetric cylinder readings. Consequently, no correction for pressure- and temperature-induced volume changes was applied to the measurements.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental apparatus\u003c/h2\u003e \u003cp\u003eCore floodings setups are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A Vinci double syringe pump was providing injection pressure. ISCO pumps were guaranteeing back pressure (260D) and confining pressure (500D). The setup temperature is guaranteed through a circulation model, where temperature is guaranteed by a circulating confining fluid, heated at an accumulator and moving thanks to a circulation pump (Eldex 1021 bb-4-2). Volume measurements are made from a 0.25ml precision water cylinder. Supercritical CO₂ is fed from a Parr reactor where it is prepared to be water-wet at the experimental conditions (1550 psi, 40\u0026deg;C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Core Characteristics\u003c/h2\u003e \u003cp\u003eThe porosity and permeability of the Buffi Berea sandstone samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) have been measured using a CoreTest AP-608 Poro Permeameter. Sample BO5 exhibited a porosity of 24.10%, with an air permeability of 985.15 mD and an absolute permeability of 966.97 mD. Its measured pore volume was 20.36 cc. Sample B03 showed a similar porosity of 23.95%, along with air and absolute permeabilities of 982.81 mD and 955.32 mD, respectively, and a pore volume of 20.10 cc. The high porosity and permeability makes the chosen cores suitable for this investigation of the microbubble injection in a high permeability setting. High permeability Berea represent the upper range of permeabilities encountered in saline aquifers, where injectivity and near-wellbore effects are expected to be critical for CO₂ storage operations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Experiment protocol\u003c/h2\u003e \u003cp\u003eVolume balance core floodings have been carried out under different settings which have all been compiled in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Test numbers are in chronological order. Some numbers are missing as the experiment has been carried out but failed due to a recording or injection issue. Most experiments in this study were conducted at a base flow rate of 0.05 cc/min, matching the conditions used by Zhai et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to investigate microbubble flow away from the injection wellbore. In sequential tests, higher flow rates of 0.1 and 0.5 cc/min were subsequently applied to evaluate the flow-rate sensitivity of microbubble injection. Reference floodings at 0.1 and 0.5 cc/min from full water saturated core were realised to compare with the sequential injection protocol in both injection types,\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVolume balance core flooding experimental tests settings and brine permeability monitoring test indented for both BO5 and BO3 samples. Brine permeability was monitored for the test numbers 20 to 31.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTest type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBO5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;5, and 13\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConventional injection\u003c/p\u003e \u003cp\u003e0.05cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;9 and 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicrobubble injection\u003c/p\u003e \u003cp\u003e0.05cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicrobubble injection\u003c/p\u003e \u003cp\u003e0.1cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicrobubble injection\u003c/p\u003e \u003cp\u003e0.5cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBO3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConventional injection\u003c/p\u003e \u003cp\u003e0.5cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConventional injection\u003c/p\u003e \u003cp\u003e0.1cc/min only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u0026ndash;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicrobubble injection\u003c/p\u003e \u003cp\u003eSequential\u003c/p\u003e \u003cp\u003e0.05 \u0026loz; 0.1 \u0026loz; 0.5 cc/min\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConventional injection\u003c/p\u003e \u003cp\u003eSequential\u003c/p\u003e \u003cp\u003e0.05 \u0026loz; 0.1 \u0026loz; 0.5 cc/min\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe flow rates used in this study are sufficiently low to maintain a capillary-dominated regime (Ca\u0026thinsp;=\u0026thinsp;1.15\u0026ndash;11.5 \u0026times; 10⁻⁹) and to avoid inertial effects, while remaining high enough to generate a measurable pressure drop across the ~\u0026thinsp;1 D cores. The porous-media Bond number is estimated to be \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.3\\times\\:{10}^{-7}\\)\u003c/span\u003e\u003c/span\u003e, which is much smaller than unity and demonstrates that buoyancy forces are negligible at the pore scale. As a result, gravity segregation is not expected during the horizontal core-flood experiments, and the observed displacement behaviour is governed by capillary forces rather than density contrasts. In comparison, the mobility ratio is inherently unfavourable: the brine-to-CO₂ viscosity ratio is 16.6, so within the Buckley\u0026ndash;Leverett framework the mobility ratio can be expressed as the ratio of relative permeabilities multiplied by this large factor. This qualitatively highlights the strong tendency for CO₂ to be more mobile than brine, implying that any improvement in sweep efficiency or injectivity must arise from reductions in effective gas mobility (e.g., microbubble effects) rather than from favourable viscous or gravitational stability.\u003c/p\u003e \u003cp\u003eThe injected brine is synthetic, prepared from deionised water. The salinity is only contributed by NaCl at 125 g/L (12.5 wt%). This value has been chosen to remain close to previous work on microbubble injection (Jiang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Patmonoaji et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor any given flooding setting, the protocol remained similar. The Teflon-jacketed core with a Viton rubber layer was inserted in the core holder. The cell was filled with deionised water with a red colour dye to spot any confining leaks during the flooding. The confining pressure was first set to 750 psi (5.17 MPa). The sample was then put under vacuum for at least 24 hours. The vacuuming process was completed when the pore pressure had dropped to a plateau. Following this, the brine was injected at 5 cc/min until the pore pressure reached 100 psi. Both pore and confinement pressures were then increased at the same rate until the target was reached (pore: 1550 psi (10.7 MPa), confinement: 2175 psi (15 MPa)).\u003c/p\u003e \u003cp\u003eFrom there, for all sequential floodings, a brine permeability test under flooding pressures was performed after the initial brine imbibition: the inlet and outlet pressure transducers recorded their pressures while three flow rates were applied: 10, 20, and 30 cc/min, with short breaks in between to allow the pressure to drop. The pressure difference (ΔP) was then extracted, and brine permeability was calculated using Darcy\u0026rsquo;s law and sample characteristics.\u003c/p\u003e \u003cp\u003eThe CO₂, pre-equilibrated with brine, was fed to the pump with the required amount of CO₂ for the experiment (2 pore volumes were estimated to be sufficient to reach breakthrough and recover all the brine, 45 cc was chosen as a higher boundary estimation). Confinement and injection pumps were heated at 40\u0026deg;C and left for one day for the temperature to equilibrate to the target. Once reached, the CO₂ flooding started, the flowrate was set as an input with the required injection amount, and the scale and pressure transducers were set to record until the flooding ended. The pore pressure rose from 1550 psi to 1580 psi (Back pressure regulator cutoff pressure) and the experiment stayed at this pressure until the flooding ended.\u003c/p\u003e \u003cp\u003eUpon ending, both confinement and pore pressure were let down progressively to 750 psi and zero respectively. The sample was vacuumed again, and another experiment could then be carried out.\u003c/p\u003e \u003cp\u003eFor sequential tests, once 45 cc of CO₂ was injected, the new flowrate was set, and 45 more ccs were injected until the three flowrates had been carried out. It should be noted that the core holder was changed for these sequential tests, and dead volume measurements were run again for adjustments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Recording\u003c/h2\u003e \u003cp\u003eTo record the output water volume, a camera was installed in front of the recovery cylinder. Photos were being taken every 1 to 2.3 mins and directly stored in the recording computer under its shoot date and time. The confinement pressure was monitored via its own pressure transducers, both in the pump and in the core holder confinement output. The inlet and outlet pressure were recorded by transducers connected to the recording computer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Microbubble generation and injection\u003c/h2\u003e \u003cp\u003eMicrobubbles were generated using a filter provided by RITE (The Research Institute of Innovative Technology for the Earth) / Tokyo Gas and placed at the sample inlet. In this study, brine is flowing through the filter, then CO₂ follows. With an average pore size of 4 microns, it created bubbles expected to be in the order of tens of micrometres in size.\u003c/p\u003e \u003cp\u003eThe filter was also expected to generate an extra pressure drop, caused by both its lower permeability and by fines migration from particles present in the brine. During microbubble tests, these particles could stop at the filter and decrease the overall permeability, likely in a different order of magnitude compared to the core alone. Therefore, quantitative comparison in permeability between conventional and microbubble experiments could not be made. Instead, only the decay rate was compared, as it provided more insights into the impact of microbubble injection on the sample permeability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Permeability measurements fit and uncertainties\u003c/h2\u003e \u003cp\u003eDuring repeated CO₂ floodings, the rock sample undergoes multiple mechanisms of alteration, which may lead to permeability decay:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFines migration: with a narrow distribution of pore throat sizes ,the case in Berea sandstone, events of clogging lead to exponential decay of open pore throats (Borisova \u0026amp; Adler, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMany models of mineral dissolution precipitation are based on exponential laws with asymptotes due to the limited quantity of reactive material and decay in reactive surface (Noiriel, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTo estimate the characteristic decay time τ associated with the permeability decay of samples, a single exponential with asymptote model is applied to both conventional and microbubble injection decay curves measured for the sample BO3. This curve fit is commonly used in the literature to fit permeability decay data (Hall, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The sample BO5 with a before-and-after flooding permeability measurement has undergone a similar decay. The exponential permeability decay curve fit is expressed as follows:\u003cdiv id=\"Equf\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equf\" name=\"EquationSource\"\u003e\n$$\\:k\\left(t\\right)={k}_{\\infty\\:}+({k}_{0}-{k}_{\\infty\\:})\\text{e}\\text{x}\\text{p}(-\\frac{t}{\\tau\\:})$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003cdiv id=\"Equg\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equg\" name=\"EquationSource\"\u003e\n$$\\:{K}_{\\infty\\:}:Asymptotic\\:permeability\\:\\left(mD\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equh\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equh\" name=\"EquationSource\"\u003e\n$$\\:{K}_{0}:Fixed\\:initial\\:permeability$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equi\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equi\" name=\"EquationSource\"\u003e\n$$\\:t:Exposure\\:time\\:\\left(days\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equj\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equj\" name=\"EquationSource\"\u003e\n$$\\:\\tau\\::Decay\\:time\\:constant\\:\\left(days\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe global permeability relative uncertainty is up to 6.3%. It is dominated by viscosity as water temperature after flooding may not be consistently up to the desired temperature during the permeability test. It contributes to 80% to the measurement uncertainty). The reading pressures (\u0026plusmn;\u0026thinsp;0.1%), flow rates, and sample dimensions barely matter in comparison (less than 2.6% relative uncertainty impact on the measurement).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Replica experiment (0.05 cc/min)\u003c/h2\u003e \u003cp\u003eReplication experiments with a similar protocol to Zhai et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have been carried out to investigate the microbubble injection potential on high-permeability samples. Microbubble and conventional injection flooding have been carried out the Berea sample BO5. Results are expressed in a violin plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The mean steady state CO₂ saturation is higher for microbubble injection by 8.89%. Saturation distributions and their error bars overlap substantially. Conventional flooding results are mostly clustered around 25%, whereas microbubble injection tends to show values closer to 45%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs per their respective saturation curves, examples of the ΔP variation along with sample CO₂ saturation from effluent collection are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The CO₂ saturations curves are mostly subdivided in two zones: A sharp almost-linear increase and a plateau with little episodic increases. There are a few differences between injection types ; the saturation gradient seems to be slower in the conventional case. The remarkable detail is a ΔP up to 3 times higher in the microbubble than conventional injection. It is partly due to the presence of the filter, which has a significantly lower permeability than the sample itself.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Sequential flowrate tests\u003c/h2\u003e \u003cp\u003eSequential tests have been performed on BO3 sample to test microbubble sensitivity to injection rate. Four tests have been carried out for each injection type. They have been compiled in three violin plots to understand their distribution. The first stage, like replication experiments (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), shows a clear and drastic distinction of saturations between conventional and microbubble injection. The microbubble saturations are more spread, and in globality always lower than conventional, with a difference of 25.7% CO₂ on average.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the case of the later stages of sequential injection (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Distributions are in this case clearly more in favour of conventional injection, where microbubble injection\u0026rsquo;s mean saturations are lower by 13.43% and 9.98% for 0.1 and 0.5 cc/min respectively. Microbubble saturation performance at higher flowrates has narrowed the gap with conventional injection, the saturation difference at 0.05 cc/min has partially faded.\u003c/p\u003e \u003cp\u003eThe performed reference floodings show the importance of the flooding protocol on saturations. They show an advantage of microbubbles over a large difference (respectively 31.66 and 13.9% for 0.1 and 0.5 cc/min).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Sequential tests permeability monitoring\u003c/h2\u003e \u003cp\u003eBrine Permeability results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Data from microbubble injection is up to test 28 as the permeability has been recorded but does not evolve from there. They record the permeability evolution of BO3 during its exposure to CO₂ floodings. Curve fitting equally shows a decay rate difference four times higher for microbubble in comparison to conventional.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Filter impact on pressure and global permeability\u003c/h2\u003e \u003cp\u003eMicrobubble floodings are characterized by a significant higher-pressure difference between inlet and outlet. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e has shown a 3 times higher pressure difference between microbubble and conventional injection. Microbubbles effect on pressure is documented: Their small size or their collection can cause pore plugging (Le et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Telmadarreie et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is important to note that the microbubble experiments employed a filter with permeability far lower than that of the Berea sandstone core. As a result, the pressure drop in the microbubble experiments is dominated by the filter rather than the rock. Therefore, ΔP values between microbubble and conventional injections cannot be directly compared, and the observed higher ΔP in microbubble tests does not reflect primarily microbubble\u0026ndash;rock resistance but the hydraulic limitation of the filter. Interpretation of pressure signals must therefore be restricted to within-experiment trends rather than cross-mode comparisons. To allow such comparison, a separated generation device would be required to separate both phenomena.\u003c/p\u003e \u003cp\u003eBoth conventional and microbubble injection saturation curves are distinguished by their absence of transition zone. Under capillary-dominated conditions (low capillary number), displacement is controlled by pore-scale capillary entry pressures, leading to sharp invasion fronts and saturation gradients that may be unresolved at the experimental scale (Blunt, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Flow Rate\u0026ndash;Dependent Performance of Microbubble Injection\u003c/h2\u003e \u003cp\u003eOur volume-balance core flooding experiments on high-permeability Berea sandstone (~\u0026thinsp;980 mD) reveal a strong dependence of microbubble efficacy on injection flow rate. At the lowest tested rate (0.05 cc/min), microbubble injection increases average CO₂ saturation by 8.89% on average relative to conventional injection, a modest but statistically discernible improvement consistent with prior studies in high-permeability media (Wang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This enhancement is likely due to Jamin effect: microbubbles temporarily block high-permeability pathways, diverting flow into less-swept intermediate pores and improving displacement efficiency.\u003c/p\u003e \u003cp\u003eHowever, this advantage vanishes at higher flow rates (0.1\u0026ndash;0.5 cc/min), where conventional outperforms microbubble injection by 14\u0026ndash;10% in final saturation. At these rates, the added hydraulic resistance from the microbubble generation filter (which increases ΔP by up to 4 times; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) may exacerbate preferential flow along dominant channels, worsening sweep uniformity. These findings indicate that the benefits from low-flow laboratory studies may not be directly applicable by extrapolation to field-scale injection scenarios, where near-wellbore flow rates are typically much higher, and suggest the need for further research under higher flow rates considering practical operation. Microbubble injection is significantly affecting the flow, for better or worse. The filter permeability is much smaller than the sample permeability, inducing a stronger ΔP, which induces microbubble smaller saturation results.\u003c/p\u003e \u003cp\u003eAt the investigated flow rates (0.05\u0026ndash;0.5 cc/min), the experiments remain within a capillary-dominated regime. However, in high-permeability samples, the characteristic capillary pressure contrast between large and small pores is small. This reduces the stabilizing effect of capillary forces on the displacement front. Under these conditions, CO₂ invasion becomes highly sensitive to pore-network geometry, connectivity, and experimental layout. Consequently, small differences in sample heterogeneity or injection sequence can lead to markedly different saturation outcomes, as observed between BO3 and BO5.\u003c/p\u003e \u003cp\u003eFor the sequential injection protocol, microbubble injection offers worse results than conventional. Whereas floodings from full saturation show the opposite trend. CO₂ microbubbles can be hypothesised as being generated on the first injected volumes, as water is available in the filter\u0026rsquo;s pores. However, It can be inferred that once CO₂ breaks through the filter, the conditions for microbubble generation are no longer met, resulting in few to none being created. This shows the need for CO₂ to be co-injected in the brine to effectively work after filter breakthrough, which has not been done in many publications (Jiang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Patmonoaji et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Xue et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Saturation Variability and Sample History Effects\u003c/h2\u003e \u003cp\u003eSaturation distributions show a widespread distribution, going above the expected variance by 3.24% for conventional and 4.28% for microbubble injection on average. Microbubble having a larger variance due to experimental setup, one cannot conclude on a higher variability caused by microbubble injection itself. The permeability monitored sample (BO3) shows a gradual permeability decay which suggests a high pore space alteration due to chemical reactions or other mechanical effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The saturation results spread could be caused by several mechanisms in action in these experiments:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe use of high-permeability samples, where their flow dynamics can be very variable from one flooding to another due to potential channelling effects (Tawiah et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProgressive geochemical alteration of the core due to repeated CO₂ exposure. Even after brine re-saturation between floods, residual acidic brine and dissolved CO₂ may persist in pore spaces, altering wettability or precipitating secondary minerals (Zhao et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Over successive cycles, this can reduce effective porosity and shift capillary pressure curves, leading to inconsistent displacement behaviour.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHeterogeneity in microbubble generation and transport. The mechanical filter produces a polydisperse bubble population whose size distribution may vary slightly between runs. In high-permeability media, where pore-throat sizes exceed typical microbubble diameters (1\u0026ndash;50 \u0026micro;m), minor changes in bubble size or concentration can significantly affect plugging dynamics and sweep pathways.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eOverall, these observations highlight the value of repeated-flood laboratory studies in capturing cumulative effects that may not be apparent in single-injection experiments, but which are likely to play an important role during prolonged CO₂ injection under field-scale operating conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Sample alteration\u003c/h2\u003e \u003cp\u003eBrine permeability monitoring shows a different aspect of the multiple flooding cycles dynamic: The decay of the BO3 sample follows a single exponential with asymptote model. When identifying the decay time constant, microbubble injection has a higher value compared to conventional (\u0026asymp;\u0026thinsp;4 times higher), showing a potentially higher reactivity and sample decay. Microbubbles have a larger surface area and can dissolve in the brine at a faster rate (Xue et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). While dissolution can initially increase porosity, it often leads to pore collapse, fines mobilisation, or clay swelling, ultimately reducing permeability (Bhuvankar et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn a field scale, prolongated injection can cause injectivity issues due to CO₂-brine rock interactions altering the pore structures to diminish the pore throat radius (Zhao et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Critically, this effect is most pronounced in the near-wellbore region, where CO₂ concentration and contact time are highest, which is precisely the zone governing injectivity in field operations. Thus, while microbubble injection may improve storage efficiency in the far field, a potential challenge is the long-term maintenance of well injectivity.\u003c/p\u003e \u003cp\u003eA multiple flooding approach with monitoring of permeability allows for a better estimation of the field expected saturation, as well as its potential to decay in permeability due to the presence of CO₂. Nonchemical microbubble injection is a technique that presents an economical interest in applying it to large scale due to its simple generation and reliance on self-stability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Study limitations\u003c/h2\u003e \u003cp\u003eThis study suffers from several limitations:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe Buffi Berea sandstone studied here has high permeability which has a few comparison points with current literature on microbubble injection.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe large gap between variance and absolute uncertainty for CO₂ saturations given for each flowrate makes it difficult to conclude on a definite number.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe pressure drop between conventional and microbubble injection is not perfectly understood and comparable. The current setup is not able to separate the action of the filter and the microbubble flow on the ΔP.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe pressure difference curves are influenced by the back pressure regulator behaviour. It creates artifacts, mainly pressure bumps, caused by the difficulty of the regulator to stabilise CO₂-brine flow.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe data given by low flowrate (0.05cc/min) sequential tests (on sample BO3) does not match previous data on replication floodings (BO5), which can reveal a sample dependency on results.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe BO3 core experienced several consecutive CO₂ floods, so the observed permeability decay accumulates over time and cannot be attributed uniquely to the injection mode. The fitted decay time constant appears higher during microbubble injection; this should not be taken as a definite proof of enhanced chemical reactivity driven specifically by microbubbles. The microbubble filter may introduce hydraulic resistance or host geochemical alteration, adding uncertainty to the decay trend. The apparent difference in decay rates suggests only a possible tendency rather than a microbubble-specific mechanism. Further tests on fresh cores without filters are necessary to draw mechanistic conclusions.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eMicrobubble CO₂ injection is an emerging injection technique, predominantly investigated through mechanical generation using microporous filters at different injection rate protocols. Conclusions are listed below:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe replication experiments (0.05cc/min) show disparate results between samples. Microbubble injection is likely to perform better on average, shown by a mean of 37.00% in comparison to 28.11% for conventional on the BO5 sample. However, the BO3 sample shows an opposite trend, where conventional is advantaged by 25.72% in CO₂ saturation compared to microbubble injection. Overall, many factors such as the high permeability, sample heterogeneity and sample gradual change during experiments might explain these results.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHigher injection flowrates in sequential injection are globally advantageous to conventional injection. Reference floodings done from complete water saturation (reference floodings) show an opposite trend to sequential injection, where conventional performs less than microbubble. This could be explained by the need of a water phase for microbubbles to be generated. This supports the need for co-injection on the field scale.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAll tests are affected by an important standard deviation in comparison to the expected variance, in particular with microbubble injection (conventional: 3.24%, microbubble: 4.28%). The difference is however not large enough to be conclusive. The optimal flowrate and ratio for microbubble injection are still to be found and optimised.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe sample BO3 brine permeability has been monitored before every flooding. The permeability has drastically decreased along all the observed floodings from 955.318 mD to 288.2 mD. Single exponential with asymptote fits on separated conventional and microbubble injection data shows a much higher characteristic decay time τ for microbubble injection. A higher permeability decay for microbubble injection warrants further investigation.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eFinally, these results support the broader conclusion of the study: while previous work on microbubble CO₂ largely focused on low-permeability formations has shown consistent improvements in sweep and trapping, our experiments demonstrate that in high-permeability systems, MB CO₂ behaviour is strongly rate-dependent and may lead to injectivity difficulties under certain conditions.\u003c/p\u003e \u003cp\u003eSequential flooding allows us to capture cumulative and rate-sensitive effects, providing realistic insight into potential trade-offs for CCS deployment. While microbubble CO₂ is beneficial in low-rate or far-field regions, it may pose near-wellbore injectivity difficulties. These findings underscored the need for further research under higher flow rates considering practical operation, and emphasising the need for careful rate optimisation, injection design, and long-term integrity assessment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConsent to publish\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eTheo Le Gallais reports that financial support was provided by Tokyo Gas Australia Pty Ltd. His tuition fees for PhD candidacy have been off-set by Curtin University.The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding declaration\u003c/h2\u003e \u003cp\u003eThe research included in this paper was funded by Tokyo Gas Australia Pty Ltd. Curtin University has off-set the tuition fees of PhD candidates involved in the project.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTheo Le Gallais : Conceptualization, methodology, investigation, data curation, formal analysis, writing - original draftEgi Adrian Pratama: Investigation, formal analysis, writing - review \u0026amp;amp; editingKlaus Regenauer-Lieb, Mohammad Sarmadivaleh : Writing - review \u0026amp;amp; editing, supervisionAli Saeedi: Methodology, supervision, review \u0026amp;amp; editingQuan Xie: Writing - review \u0026amp;amp; editingHideto Kurokawa: Writing - review \u0026amp;amp; editing\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to deeply thank the contribution of Tokyo Gas and RITE for their continuous support and also in providing the microbubble generation filters used in this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding authors upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAizawa Y, Baba Y, Xue Z. (2021). Microbubble CO2 Injection for Geological Sequestration in Tight Sandstone Reservoirs. \u003cem\u003eProceedings of the 15th Greenhouse Gas Control Technologies Conference 15\u0026ndash;18 March 2021\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ssrn.com/abstract=3811393\u003c/span\u003e\u003cspan address=\"https://ssrn.com/abstract=3811393\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhuvankar P, Cihan A, Birkholzer JT. (2023). Pore-Scale Analysis of the Permeability Damage and Recovery during Cyclic Freshwater and Brine Injection in Porous Media Containing Non-Swelling Clays. Energies, \u003cem\u003e16\u003c/em\u003e(22).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlunt MJ. Multiphase Flow in Permeable Media: A Pore-Scale Perspective. Cambridge University Press; 2017. https://doi.org/DOI.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorisova EA, Adler PM. Deposition in porous media and clogging on the field scale. Phys Rev E. 2005;71(1):016311. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1103/PhysRevE.71.016311\u003c/span\u003e\u003cspan address=\"10.1103/PhysRevE.71.016311\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubey S, Majumder SK. (2024). Stability analysis of CO2 microbubble for CO2 sequestration and mobility control in enhanced oil recovery. \u003cem\u003eChemical Engineering Journal\u003c/em\u003e, \u003cem\u003e500\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cej.2024.156595\u003c/span\u003e\u003cspan address=\"10.1016/j.cej.2024.156595\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHall C. (2025). \u003cem\u003eReactive transport in cement-based materials\u003c/em\u003e (Hall\u0026rsquo;s Notes and Queries, Issue. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://blogs.ed.ac.uk/christopherhall/wp-content/uploads/sites/6693/2025/09/NQ11.pdf\u003c/span\u003e\u003cspan address=\"https://blogs.ed.ac.uk/christopherhall/wp-content/uploads/sites/6693/2025/09/NQ11.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIEA. (2020). \u003cem\u003eEnergy Technology Perspectives 2020\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIPCC. (2023). Climate Change 2023: Synthesis Report. \u003cem\u003eIPCC\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://dx.doi.org\u003c/span\u003e\u003cspan address=\"https://doi.org/https://dx.doi.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e/10.59327/IPCC/AR6-9789291691647.001\u003c/span\u003e\u003cspan address=\"/10.59327/IPCC/AR6-9789291691647.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJia H, Yu H, Wang S, Shi J, Xie F, Wang S, Lu J, Wang Y, Zhang F. Investigation of CO2 microbubble assisted carbon sequestration and gravity-induced microbubble ripening in low permeability reservoirs. Appl Energy. 2024;373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apenergy.2024.123954\u003c/span\u003e\u003cspan address=\"10.1016/j.apenergy.2024.123954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJia H, Yu H, Xie F, Yuan Z, Xu K, Wang Y, RESEARCH ON CO2 MICROBUBBLE DISSOLUTION KINETICS AND ENHANCED OIL RECOVERY MECHANISMS. Chin J Theoretical Appl Mech. 2023;55(3):755\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.6052/0459-1879-22-507\u003c/span\u003e\u003cspan address=\"10.6052/0459-1879-22-507\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang L, Xue Z, Park H. Enhancement of CO2 dissolution and sweep efficiency in saline aquifer by micro bubble CO2 injection. Int J Heat Mass Transf. 2019;138:1211\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheatmasstransfer.2019.04.139\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheatmasstransfer.2019.04.139\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe NNH, Sugai Y, Vo-Thanh H, Nguele R, Ssebadduka R, Wei N. Experimental investigation on plugging performance of CO2 microbubbles in porous media. J Petrol Sci Eng. 2022;211. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.petrol.2022.110187\u003c/span\u003e\u003cspan address=\"10.1016/j.petrol.2022.110187\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi S, Wang X, Wang S, Zhang Y, Chen C, Jiang L, Wang L, Liang F, Sun H, Song Y. Optimizing oil recovery with CO2 microbubbles: A study of gas composition. Energy. 2024;302. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.energy.2024.131836\u003c/span\u003e\u003cspan address=\"10.1016/j.energy.2024.131836\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Peng B, Liu Q, Liu J, Shang L. Micro and nanobubbles technologies as a new horizon for CO2-EOR and CO2 geological storage techniques: A review. Fuel 341. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fuel.2023.127661\u003c/span\u003e\u003cspan address=\"10.1016/j.fuel.2023.127661\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Wang Y, Zeng B, Li Y, Tan H, Zandvliet HJW, Zhang X, Lohse D. Entrapment and Dissolution of Microbubbles Inside Microwells. Langmuir. 2018;34(36):10659\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.langmuir.8b02173\u003c/span\u003e\u003cspan address=\"10.1021/acs.langmuir.8b02173\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahjour SK, Faroughi SA. (2023). Risks and uncertainties in carbon capture, transport, and storage projects: A comprehensive review. \u003cem\u003eGas Science and Engineering\u003c/em\u003e, \u003cem\u003e119\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jgsce.2023.205117\u003c/span\u003e\u003cspan address=\"10.1016/j.jgsce.2023.205117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoiriel C. Resolving Time-dependent Evolution of Pore-Scale Structure, Permeability and Reactivity using X-ray Microtomography. Rev Mineral Geochem. 2015;80(1):247\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2138/rmg.2015.80.08\u003c/span\u003e\u003cspan address=\"10.2138/rmg.2015.80.08\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark H, Jiang L, Kiyama T, Xue Z. Experimental Study of Microbubble CO2 Flooding in Heterogeneous Sedimentary Rock. SSRN Electron J. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2139/ssrn.3365701\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.3365701\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatmonoaji A, Zhang Y, Xue Z, Park H, Suekane T. Experimental and numerical simulation of supercritical CO2 microbubble injection into a brine-saturated porous medium. Int J Greenhouse Gas Control. 2019;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijggc.2019.102830\u003c/span\u003e\u003cspan address=\"10.1016/j.ijggc.2019.102830\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRogers PSZ, Pitzer KS. Volumetric Properties of Aqueous Sodium Chloride Solutions. J Phys Chem Ref Data. 1982;11(1):15\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1063/1.555663\u003c/span\u003e\u003cspan address=\"10.1063/1.555663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTawiah P, Wang H, Bryant SL, Dong M, Larter S, Duer J. Effects of temperature and CO2/Brine cycles on CO2 drainage endpoint phase mobility \u0026ndash; implications for CO2 injectivity in deep saline aquifers. Int J Greenhouse Gas Control. 2021;112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijggc.2021.103491\u003c/span\u003e\u003cspan address=\"10.1016/j.ijggc.2021.103491\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTelmadarreie A, Doda A, Trivedi JJ, Kuru E, Choi P. CO2 microbubbles \u0026ndash; A potential fluid for enhanced oil recovery: Bulk and porous media studies. J Petrol Sci Eng. 2016;138:160\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.petrol.2015.10.035\u003c/span\u003e\u003cspan address=\"10.1016/j.petrol.2015.10.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUeda R, Nakano M, Xue Z. The efforts for the application of micro bubble technology to CCS and EOR. J Japanese Association Petroleum Technol. 2021;86(2):94\u0026ndash;104. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3720/japt.86.94\u003c/span\u003e\u003cspan address=\"10.3720/japt.86.94\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang D, Fan J, Xue Z. Hydrodynamic Analysis of CO2 Migration in Heterogeneous Rocks: Conventional and Micro-Bubble CO2 Flooding Experiments and Pore‐Scale Numerical Simulations. Water Resour Res. 2022;58(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2021wr031874\u003c/span\u003e\u003cspan address=\"10.1029/2021wr031874\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang S, Zhang G, Lv P, Wang Z, Jiang L, Zhu L, Song Y. Accelerating CO2 Dissolution Trapping in Deep Saline Aquifers through a Microbubble Injection Strategy. Energy Fuels. 2025b;39:3217\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1021/acs.energyfuels.4\u003c/span\u003e\u003cspan address=\"10.1021/acs.energyfuels.4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. c05889?urlappend=%3Fref%3DPDF\u0026amp;jav=VoR\u0026amp;rel=cite-as.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu T, Apps JA, Pruess K. Numerical simulation of CO2 disposal by mineral trapping in deep aquifers. Appl Geochem. 2004;19(6):917\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.apgeochem.2003.11.003\u003c/span\u003e\u003cspan address=\"10.1016/j.apgeochem.2003.11.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z. Field Application of Microbubble CO2 Injection for Enhanced Storage Efficiency in a Tight Sandstone Reservoir. SSRN Electron J. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2139/ssrn.3811983\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.3811983\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z, Matsuoka T. Lessons from the First Japanese Pilot Project on Saline Aquifer CO2 Storage. Chigaku Zasshi (Jounal Geography). 2008;117(4):734\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5026/jgeography.117.734\u003c/span\u003e\u003cspan address=\"10.5026/jgeography.117.734\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z, Nishio S, Hagiwara N, Matsuoka T. Microbubble Carbon Dioxide Injection for Enhanced Dissolution in Geological Sequestration and Improved Oil Recovery. Energy Procedia. 2014;63:7939\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.egypro.2014.11.828\u003c/span\u003e\u003cspan address=\"10.1016/j.egypro.2014.11.828\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z, Park H, Ueda R, Nakano M, Nishii T, Inagaki S. Microbubble CO2 Injection for Enhanced Oil Recovery and Geological Sequestration in Heterogeneous and Low Permeability Reservoirs. SSRN Electron J. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2139/ssrn.3366428\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.3366428\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z, Tsuji S, Kameyama H, Nishio S, Matsuoka T. Development of Carbon Dioxide Microbubble Sequestration into Saline Aquifer and CO2-EOR Reservoirs. Energy Procedia. 2013;37:4628\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.egypro.2013.06.371\u003c/span\u003e\u003cspan address=\"10.1016/j.egypro.2013.06.371\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Z, Yamada T, Matsuoka T, Kameyama H, Nishio S. Carbon dioxide microbubble injection\u0026ndash;Enhanced dissolution in geological sequestration. Energy Procedia. 2011;4:4307\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.egypro.2011.02.381\u003c/span\u003e\u003cspan address=\"10.1016/j.egypro.2011.02.381\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu Y, Beddoe C, Xue Z, Chakhmakhchev A, Hamling J, Smith S, Kurz B. (2022). Experimental evaluation of enhanced tight oil recovery performance by microbubble CO2 and microbubble rich gas in North Dakota plays. \u003cem\u003eUnconventional Resources Technology Conference, 20\u0026ndash;22 June 2022\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.15530/urtec-2022-3694645\u003c/span\u003e\u003cspan address=\"10.15530/urtec-2022-3694645\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhai H, Xue Z, Park H, Aizawa Y, Baba Y, Zhang Y. Migration characteristics of supercritical CO2 microbubble flow in the Berea sandstone revealed by voxel-based X-ray computed tomography imaging analysis. J Nat Gas Sci Eng. 2020;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jngse.2020.103233\u003c/span\u003e\u003cspan address=\"10.1016/j.jngse.2020.103233\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Arif M. Residual trapping capacity of subsurface systems for geological storage of CO2: Measurement techniques, meta-analysis of influencing factors, and future outlook. Earth Sci Rev. 2024;252. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.earscirev.2024.104764\u003c/span\u003e\u003cspan address=\"10.1016/j.earscirev.2024.104764\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao DF, Liao XW, Yin DD. An experimental study for the effect of CO2-brine-rock interaction on reservoir physical properties. J Energy Inst. 2015;88(1):27\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.joei.2014.05.001\u003c/span\u003e\u003cspan address=\"10.1016/j.joei.2014.05.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Geological CO₂ storage, Microbubble CO₂ injection, High-permeability sandstone, Sweep efficiency, Permeability decay","lastPublishedDoi":"10.21203/rs.3.rs-8879243/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8879243/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicrobubble (MB) CO₂ injection has been proposed to improve sweep efficiency and dissolution trapping, yet its implications for injectivity and near-wellbore integrity in high-permeability formations are not well constrained. We conducted repeated volume-balance core-flooding experiments on high-permeability Berea sandstone (~\u0026thinsp;980 mD) under deep saline aquifer conditions (40\u0026deg;C, 10.7 MPa), comparing MB and conventional supercritical CO₂ injections across flow rates of 0.05\u0026ndash;0.5 cc/min (Ca : 1.15\u0026ndash;11.5 \u0026times; 10⁻⁹) while monitoring brine permeability.\u003c/p\u003e \u003cp\u003eAt 0.05 cc/min, MB injection increased average CO₂ saturation by 8.9% relative to conventional flooding due to temporary microbubble-induced blockage of dominant flow channels. This benefit diminished at higher flow rates (0.1\u0026ndash;0.5 cc/min), where MB injection consistently yielded lower final CO₂ saturations. Across sequential floods, MB injection caused brine permeability to decline up to four times faster than conventional injection, indicating accelerated near-wellbore damage likely driven by fines mobilisation and enhanced mineral reactions associated with rapid microbubble dissolution.\u003c/p\u003e \u003cp\u003eThese results demonstrate a clear trade-off in MB CO₂ injection: potential sweep-efficiency gains at low flow rates versus permeability loss and injectivity difficulties at higher flow rates. The results of this study suggest the need for further research under higher flow rates considering practical operation and optimising microbubble-based storage strategies will require careful control of flow rate and consideration of reservoir heterogeneity in high-permeability systems.\u003c/p\u003e","manuscriptTitle":"Microbubble CO₂ Injection in High- Perm Sandstone: Flow-Rate Effects and Permeability Decay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-06 10:03:43","doi":"10.21203/rs.3.rs-8879243/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d671fa3-f373-4ad2-bc2e-6d2c845ae49a","owner":[],"postedDate":"March 6th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Withdrawn","date":"2026-05-06T11:28:53+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T11:42:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-06 10:03:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8879243","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8879243","identity":"rs-8879243","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}