Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media

Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media | 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 data-descriptor Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media Prakash Purswani, Anna Herring, Prabhav Borate, Parisa Shokouhi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8349129/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 Subsurface gas storage, particularly the sequestration of CO, continues to remain an active area of research for mitigating atmospheric CO concentrations. However, experimental datasets providing direct, high-resolution measurements of CO₂ transport, saturation, and pore-scale dynamics under realistic reservoir conditions remain limited, due primarily to experimental complexity. In this study, we present a comprehensive dataset from supercritical CO (CO)-brine core-flooding experiments conducted at relevant subsurface conditions, employing a sophisticated core holder system capable of sustaining high-pressure and high-temperature environments within an X-ray microcomputed tomography (µCT) setup. Continuous monitoring of flow rates and system pressures accompanied X-ray imaging performed at equilibrium conditions, capturing fluid saturations with a high spatial resolution of 25 µm. CO-equilibrated brine was utilized to minimize mass-transfer effects, and both drainage and imbibition scenarios are thoroughly documented. The unique dataset includes high-resolution 3D raw and segmented X-ray images detailing the dry and fluid-saturated conditions, complemented by quantitative metrics of fluid saturation, morphological descriptors, and phase connectivity. In addition, dual-quality X-ray image sets of high- and low-noise scans captured at residual CO saturation after imbibition are provided, enabling comparative analysis and advancements in rapid image-acquisition techniques. The detailed pressure histories and segmented morphological data facilitate advanced numerical model validation and serve as a benchmark dataset for image segmentation algorithm development. All data have been curated and uploaded to an open-access repository, promoting broad usability and fostering innovation in subsurface gas storage research. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Understanding and predicting multiphase fluid behavior in subsurface porous media is a central challenge across a wide range of energy, environmental, and storage applications. Whether the goal is to manage the migration of injected gases, optimize working-gas recovery, assess storage security, or model pressure evolution, reliable predictions require a detailed understanding of how immiscible or partially miscible fluids move, redistribute, and become trapped within complex geologic pore structures. 1 – 7 These challenges are shared across systems such as underground hydrogen storage (UHS), geologic carbon sequestration (GCS), compressed air energy storage, geothermal operations, and enhanced recovery processes in hydrocarbon reservoirs. Across these domains, pore-scale displacement dynamics, driven by the interplay of capillary, viscous, and gravitational forces, strongly influence emergent behaviors at core, reservoir, and basin scales. 2 , 5 , 8 – 11 Accurate characterization of these processes is essential for building predictive models that can guide engineering decisions. Numerical reservoir simulations, pore-network models, and data-driven machine-learning frameworks all rely on constitutive relationships and parameters that reflect the underlying pore-scale physics. However, parameterizing these models remains difficult due to the limited availability of high-quality, experimentally validated data acquired under realistic reservoir conditions. Multiphase flow datasets suitable for model calibration, benchmarking, and AI/ML training are particularly scarce, especially those providing synchronized flow and pressure measurements, along with high-resolution images. 12 – 14 As artificial intelligence becomes increasingly central to subsurface characterization, monitoring, and forecasting, the demand for rich, well-documented, high-fidelity datasets continues to rise. 15 Within this broader landscape of subsurface applications, geologic carbon sequestration (GCS) represents a critical strategy for mitigating anthropogenic CO 2 emissions and stabilizing atmospheric greenhouse gas concentrations. 16 – 19 GCS involves the injection of large volumes of CO 2 into deep geologic formations such as saline aquifers or depleted hydrocarbon reservoirs, where long-term storage security depends on the interplay of multiphase displacement, residual trapping, dissolution, and mineralization processes. Reliable prediction of CO 2 fate requires a robust understanding of these mechanisms at the pore scale, where wettability, pore geometry, and grain-scale heterogeneity exert strong control on fluid connectivity and migration pathways. Predictive modeling of CO 2 behavior at the reservoir scale depends heavily on accurate parameterization of rock and fluid properties that reflect these fundamental processes across a wide range of spatial and temporal scales. 1 – 3 , 8 , 20 , 21 In fact, pore-scale insights are often crucial for determining reliable macroscopic flow functions (e.g., relative permeability and capillary pressure) that feed into reservoir-scale simulations. 4 , 22 , 23 A major source of uncertainty in current models stems from the incomplete understanding of multiphase flow dynamics at the pore scale. The heterogeneity of natural geologic formations, coupled with the complex interplay of capillary, viscous, and gravitational forces, introduces variability in CO 2 saturation, preferential flow pathways, and trapping efficiency across the formation. Centimeter- to meter-scale capillary and permeability heterogeneities, which manifest from pore-scale variability in grain size, wettability, and pore geometry, can substantially alter flow and trapping behavior. 5 , 24 While numerical simulations and pore-network models have provided valuable insight into multiphase flow and trapping mechanisms, 3,4 rigorous experimental validation remains essential. However, relevant datasets remain scarce due to the technical and logistical challenges associated with conducting core-scale experiments under high-pressure and high-temperature environments representative of geologic reservoirs. Many existing datasets lack the resolution, documentation, or fail to capture the full drainage-imbibition cycle necessary for understanding hysteresis in fluid flow behavior. 12 , 14 , 25 These limitations impede progress not only in GCS but also in other subsurface energy technologies, including UHS, where similar gas–brine interactions control operational performance and storage reliability. To address this gap, we present a high-resolution imaging dataset of multiphase fluid displacement in sandstone cores subjected to supercritical CO 2 ( sc CO 2 ) and brine core-flooding under controlled laboratory conditions. The primary objective of our study is to generate a reproducible and well-characterized dataset that captures key aspects of sc CO 2 -brine displacement under reservoir-relevant conditions. A synthetic sintered glass sample was used to mimic the pore structure of conventional sandstones while avoiding mineralogical complexity and rock–fluid interactions, ensuring that observed displacement patterns reflect physical processes rather than chemical effects. Specifically, our dataset offers: A comprehensive suite of 3D µCT images representing dry, drainage, and imbibition states; Continuous pressure and flow rate data for model calibration and validation; Segmented datasets with labeled rock and fluid phases for quantitative analysis; Detailed measurements of fluid saturations and morphological descriptors suitable for analyzing phase connectivity, interfacial geometry, and pore-scale flow patterns; Dual-quality image sets (high- and low-noise) at residual CO 2 saturation, enabling development and testing of image denoising and rapid acquisition techniques. Because the dataset captures fundamental multiphase displacement processes under well-constrained boundary conditions, it is relevant not only for GCS but for a broad set of subsurface energy systems where gas–brine displacement governs injectivity, cycling efficiency, and long-term storage behavior. The data are also well suited for reuse across a variety of research domains, including image segmentation algorithm development, digital rock physics, machine learning training sets, and numerical model benchmarking. Moreover, our dataset is one of the few publicly available resources that combine precise experimental control, imaging fidelity, and documentation under GCS-relevant conditions. All data, including raw and processed images, pressure records, and segmentation masks, are hosted on an open-access datacommons@psu repository, 26 in alignment with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. We anticipate that these data will support a broad range of scientific efforts ranging from improving pore-scale modeling techniques and accelerating AI/ML workflows to informing risk assessments and operational strategies for CO 2 injection, hydrogen storage, and other subsurface energy applications. 2. Methods In these experiments, we performed high-pressure, high temperature coreflooding to study the dynamics of CO 2 transport at representative subsurface conditions. The experimental procedure, equipment used, data collection methods, and operating conditions are detailed below. The operating pressure-temperature conditions were maintained such that CO 2 remained in a supercritical state ( sc CO 2 ) throughout all displacement stages. CO 2 -saturated brine was used to minimize mass-transfer effects between the brine and the sc CO 2 phase during individual displacement steps. Both drainage and imbibition cycles were studied to determine initial and residual CO 2 saturations. High-resolution X-ray imaging was coupled with the coreflooding experiments, enabling detailed investigations of fluid saturations and fluid morphological descriptors. 2.1. Experimental setup and image acquisition The experimental setup consisted of the following equipment: X-ray imaging cabinet; high-pressure Quizix pumps; heating elements and jackets; aluminum core holder; thermocouples and temperature reader; pressure transducers; high-pressure stainless-steel flow lines; back-pressure regulator; high-pressure Parr vessel for preparing CO 2 -saturated brine; CO 2 gas cylinder; sodium iodide-doped brine solution for imaging contrast; data acquisition system. A schematic illustration of the experimental setup and a photograph showing the interior of the X-ray chamber and staged experimental setup are provided in Fig. 1 . Flow lines from the top and bottom of the core holder were intentionally kept long and coiled to allow the internal stage within the X-ray chamber to freely rotate during X-ray scans. The X-ray chamber included designed openings for connecting flow lines and pumps located externally. Similarly, the data acquisition setup was situated outside the X-ray chamber. The flow through the sample was directed vertically to facilitate gravity-stable displacement. All experimentation was performed at a fixed injection rate of 1 cc/min and differential pressure through the rock was continuously monitored. X-ray images were acquired at distinct stages during the experiment once equilibrium, indicated by pressure stability, was reached. The images were acquired using the GE v|tome|x L X-ray µCT system at the Center for Quantitative Imaging, a collaborative facility within the Institute of Energy and Environment at Penn State University (Center for Quantitative Imaging | Institute of Energy and the Environment). At these equilibrium conditions, flow was temporarily terminated to allow image acquisition at constant pressure. A dry, synthetic sintered glass cylindrical rock sample acquired from Robu® (ROBU® Glasfilter-Geräte GmbH) was used in this study. The sample was ~ 1 inch in diameter and ~ 3 inches in length with a measured porosity of ~ 24% and brine permeability of ~ 98 mD. The synthetic sintered glass sample was selected because its pore structure and flow properties approximate those of conventional sandstones, while eliminating mineralogical heterogeneity and rock–fluid chemical interactions. The sample was cleaned and dried and installed inside the core holder, sealed in a rubber jacket, and fitted with flow distributor ends to facilitate fluid passage. In addition to pure CO 2 , brine with 1 M NaI was used to provide contrast between the CO 2 and brine phase for easier phase distinction and image processing. Water was used as the confining fluid between the jacket and the interior walls of the core holder, with confining pressure maintained by a dedicated confining pump. 2.2. Experimental procedure The experimental procedure outlined in Fig. 2 comprised the following stages: 1. Vacuum : The sample was subjected to a confining pressure of 300 psi, while a vacuum pump reduced pore pressure to approximately 0.018 psi. This state was maintained for several hours to achieve vacuum conditions within the pore space and flow lines. An X-ray scan was acquired at this stage to capture the internal pore heterogeneity. 2. 100% gCO 2 : CO 2 gas was introduced into the sample to displace residual air from the pore spaces. 3. 100% scCO 2 : The pore pressure within the rock was incrementally increased by steps of 50–100 psi to achieve supercritical conditions, ensuring the confining pressure was consistently maintained 250–300 psi higher than the pore pressure. This stage also involved thorough leak checks to ensure system integrity. 4. Vacuum Saturation with Brine : The system was depressurized, vacuum conditions were reestablished, and brine was introduced into the rock to achieve complete pore saturation. 5. Brine Flow for Permeability Measurement : Brine was flowed through the sample at varying flow rates, and the resulting pressure drop across the sample was measured, enabling permeability estimation (see Figures S1 and S2 in Supplementary Materials). This permeability measurement stage occurred at 500 psi confining pressure. Subsequently, pore pressure was raised in gradual stages to match supercritical CO 2 conditions, followed by an increase in sample temperature to reach experimental conditions. An X-ray scan was acquired at this stage. 6. 100% CO 2 -Saturated Brine : CO 2 -saturated brine, prepared in the high-pressure Parr vessel, was introduced to displace resident brine fully. An X-ray scan was acquired after complete replacement. 7. Initial scCO 2 : Multiphase flow experiments began with injection of sc CO 2 from the bottom of the sample. Flow continued for several hours until equilibrium was reached, establishing initial sc CO 2 saturation. An X-ray scan was performed at the conclusion of this step. 8. Final scCO 2 : Analysis of the previous X-ray scan indicated inefficient brine displacement, characterized by sc CO 2 fingering around the sample rim. To address this, the flow direction was inverted, with sc CO 2 now injected from the top. Following extended injection, another X-ray scan verified successful brine displacement. Detailed saturation profiles are discussed in a subsequent section. 9. Residual scCO 2 : Lastly, CO 2 -saturated brine was injected from the bottom to displace sc CO 2 , continuing through multiple pore volumes until achieving residual sc CO 2 saturation. At this final stage, two types of X-ray scans were conducted, (1) A fast scan at low X-ray exposure, (2) A slow scan at high X-ray exposure. These two scan types facilitated comparative analyses under identical two-phase conditions. All relevant experimental conditions for each stage are summarized in Table 1 . All X-ray images were acquired after allowing time for fluids to stabilize between each experimental stage and ensuring pressure stability in the system. The X-ray power settings were calibrated to a voltage of 220 kV and a current of 110 µA during the initial assembly of the setup with the coreholder installed without flow, and these settings were maintained throughout all scans. Flexible stainless steel high-pressure flow lines were used and were kept longer with a larger dead-volume to allow for the free rotation of the core holder during the scanning process. A wider acrylic stage was custom-built to allow for the coiled flow lines to rest near the bottom injection port of the core holder to aid with the sample rotation. The vacuum and single phase scans were completed in ~ 1.5 hours each, while all multiphase scans were completed in ~ 2.2 hours each. Lastly, an additional low quality scan (fast scan) was completed for the last experimental stage in ~ 20 mins. All acquired image data was at a voxel resolution of 25 µm. 2.3. Image processing Three-dimensional volumes were processed using WebMango, a web-based image processing software developed and supported by the Australian National University. The Vacuum scan was converted to a binary segmentation with every voxel labeled as solid (1) or void (0) phase, utilizing the “converging active contours” (CAC) 27 . To initialize the CAC algorithm, user inputs define lower and upper gray levels beyond which voxels are automatically assigned as phase 0 or phase 1. Voxels with values between the designated gray levels are initially set as “unknown” and are labeled subsequently as phase interfaces grow until disparate regions meet. Interface growth rates for the two phases can be separately controlled. For the Vacuum data set, visual inspection suggested a void:solid growth rate of 0.95 (indicating that void interfaces grow slightly slower than the solid) provided a reasonable binary segmentation. The applied CAC segmentation parameters for all data volumes are provided in the supporting information (see Table S1 ). The Vacuum scan was found to be originally misaligned compared to the subsequent scans owing to minor movement of the sample during fluid injection. To enable three-phase (solid, CO 2 , and brine) voxel labeling, the Vacuum data was co-registered to the saturated scans via rigid translation adjustment 28 based on comparison to the scan acquired at stage 7 of the experiment: Initial scCO 2 flood data. The aligned vacuum solid phase was subsequently used as a mask for saturated-flow experiment scans. Fluid phases were identified by applying additional CAC routines restricted to voxels occupying the void space. In these routines, low-intensity voxels were labeled as sc CO 2 , while high-intensity voxels were labeled as brine. For partially saturated scans, CAC initiation incorporated an additional gradient-based criterion: voxels with gray-scale gradients above a specified threshold were classified as “unknown,” even if their gray values would otherwise indicate automatic classification as sc CO 2 or brine. Applying this gradient threshold mitigates partial-volume effects near solid interfaces, improving segmentation accuracy in regions with steep intensity transitions. As reported in Table S2, similar values for lower and upper gray level thresholds, gradient thresholds, and interface speed ratios were used for all data sets. Minor variations in parameters were utilized for the two scans with the lowest levels of brine present (i.e. the Vacuum and Initial scCO 2 flood volumes). For all data sets, speckle noise removal (i.e. removal of voxels suspected to be falsely labeled as the sc CO 2 phase) was accomplished by converting small sc CO 2 -labeled clusters to the brine phase. A size of 375 voxels was chosen as the noise removal threshold based on a careful inspection of cluster size histograms (see Figure S3 in the supporting information). Quantitative phase volumes and topological metrics were calculated based on these final de-noised segmentations and are discussed in Section 3. 3. Key quantitative metrics from processed data In this section, we summarize key quantitative metrics from image analysis, examining fluid saturations, phase connectivity, and pressure histories across the various experimental stages. By providing these quantitative metrics, we aim to offer a practical benchmark for researchers conducting related investigations using our data sets. 3.1. Fluid saturation and morphological information Figure 3 shows cross-sections of the raw and segmented CT images for the key experimental stages. The images highlight the complexity of the pore structure and the spatial distribution of sc CO 2 within the pore space at different points in the experiment. Analysis of the first multiphase scan, conducted after the initial (upwards) sc CO 2 injection, confirmed that the injection did not sweep the pore space effectively. Strong fingering of the injected sc CO 2 caused the flow to move predominantly along the peripheries of the sample, bypassing the central pore network (see the middle scan in Fig. 3 and the left image in Fig. 4 ). Based on this observation, the injection direction was changed to allow the injection of sc CO 2 from the top of the sample to improve the sweep efficiency. Contrary to our initial expectation that injecting the lighter sc CO 2 from the bottom would provide a gravity-stable displacement, we observed that introducing sc CO 2 from the top of the sample resulted in a more effective sweep. The density and viscosity of CO 2 in its supercritical state are sufficiently high to support a more favorable injection sequence when introduced from above. Following this adjustment, we observed a significant increase in the displacement of sc CO 2 -saturated brine. These findings have important implications for designing injection strategies for subsurface gas storage, especially when unfavorable viscosity ratios lead to unstable displacement. This is particularly relevant for gases such as hydrogen, which can present even more adverse viscosity contrasts than sc CO 2 . 6 In contrast to sc CO 2 injection, brine injection was effective on the first attempt and resulted in relatively high? residual trapping of sc CO 2 . We infer that the trapped sc CO 2 is primarily due to two pore-scale mechanisms at play including bypassing flow of the injected sc CO 2 -saturated brine and snap-off events. Both mechanisms promote the breakup of larger sc CO 2 clusters into smaller disconnected ganglia, which then become immobilized by capillary forces. Over the course of imaging, no remobilization of the trapped sc CO 2 was observed. Although longer rest periods could, in principle, enable processes such as Ostwald ripening to redistribute scCO₂, such effects should remain limited because mass-transfer–driven dissolution had largely equilibrated and the brine was pre-saturated with scCO₂ under the experimental conditions. Lastly, the trapped sc CO 2 was distributed throughout the pore space without evidence of local clusters with significantly larger accumulations. The CAC initiation parameters and denoising value selections impact quantitative results. For the denoised Vacuum data, for universal increases/decreases of 10% in gray level thresholds, porosity values vary by + / − 1–2% (porosity value ranges from 23–26%); void phase Euler characteristic values are more sensitive but still range by < 10% (Table S2 in Supplementary Materials). Noise removal has a more significant impact on topological metrics; 7,25 in the Initial scCO 2 data volume this causes a transition from positive to negative Euler values as small isolated sc CO 2 -labeled voxels are relabeled (Table 2 ). This result emphasizes the conclusions of Huang et al., 25 who state that appropriate noise and/or size exclusion must be carried out to obtain topological metrics relevant to the phase of interest (in this case, sc CO 2 ). Table 2 Small cluster removal was applied to eliminate “speckle” noise arising from mislabeling during the segmentation process. Values are shown for segmented data sets with all sc CO 2 -labeled clusters included, and for data sets with clusters smaller than 375 voxels removed. Before Noise Removal After Noise Removal β 0 β 1 β 2 χ β 0 β 1 β 2 χ Porosity CO 2 Saturation Vacuum 10,955 266,121 2 -255,164 94 266,095 2 -265,999 24.1% scCO 2 saturated brine 162 - - 162 0 0 0 0 0.0% Initial scCO 2 4,792 4,455 1 338 1,732 4,428 1 -2,695 9.7% Final scCO 2 4,074 105,374 1 -101,299 372 105,355 1 -104,982 82.4% Residual scCO 2 56,170 3,121 0 53,049 8,028 2,961 0 5,067 13.8% 3.2. Pressure measurement Omega pressure sensors (digital pressure transducers, PX409 series) were installed upstream and downstream of the rock sample to monitor pore pressures continuously throughout the experiment. Average pore pressures are illustrated in Fig. 5 , clearly delineating each experimental stage. It can be observed that average pore pressures were maintained between ~ 1200 and 1400 psi during all multiphase displacement stages. Similarly, temperature conditions were consistently maintained at ~ 47°C, ensuring the CO 2 remained in a supercritical state 29 . In addition, during the vacuum-saturation stage, differential pressures at varying brine flow rates were recorded to determine rock permeability, resulting in a measured brine permeability of ~ 98 mD. These detailed pressure measurements are provided in the Supporting Information (Figures S1 and S2). While this dataset provides valuable insights into multiphase displacement under controlled conditions, it is important to note certain limitations. First, the experiments were conducted at a single pressure–temperature condition representative of subsurface storage environments; therefore, the findings may not capture variability associated with different reservoir conditions. Second, the image resolution of 25 µm, although sufficient for pore-scale analysis, is relatively low compared to some recent studies employing sub-10 µm voxel sizes. Higher-resolution imaging could reveal additional details of pore connectivity and interfacial geometry. These constraints should be considered when applying the dataset for model development or benchmarking. 4. Data availability The datasets shared in this paper are made publicly available at https://doi.org/10.26208/S97R-HZ89 . The datasets include raw and segmented cross-section images of the key experimental stages (see midway example cross-sections in Fig. 3 ). All raw images were generated by cropping the original X-ray scans using a circular stencil (900 pixel 2 ) and selecting a portion of the sample after removing edge-related X-ray scattering artifacts. Each imaging dataset consists of 1700 slices providing a sample height of 4.25 cm and cross-sectional diameter of 2.25 cm. The raw images remain fully unprocessed besides cropping and were generated from the sinograms of the acquired X-ray images and the GE reconstruction software while the segmented images were processed with the Mango Software (see details in Section 2.3). The detailed methodology for the experiments performed here is expected to guide future research involving multiphase flow and transport in porous media with applications to geologic gas (carbon dioxide, hydrogen, methane) storage and contaminant transport during groundwater remediation. The purpose of these datasets is to enable further investigation and improvements of image processing workflows including image denoising, image segmentation, and quantitative fluid-rock metric estimation. The segmented images and corresponding quantitative metrics extracted in this work are to serve as a comparison to any future investigation in the multiphase image processing domains. Finally, the simultaneous availability of low-quality and high-quality images on the same multiphase will guide the development of novel image processing involving the use of machine learning and artificial intelligence wherein the high-quality image can serve as benchmark and image augmentation methods can allow for data multiplication. If successful, these tools will enable faster image acquisition time while maintaining superior quality in the estimation of quantitative metrics which are critical for multiphase fluid flow characterization. Declarations Competing interests The authors declare no competing financial interest. Funding This work was completed as part of the Science-informed Machine learning to Accelerate Real Time decision making for Carbon Storage (SMART-CS) Initiative (edx.netl.doe.gov/SMART). Support for this initiative was provided by the U.S. Department of Energy’s (DOE) Office of Fossil Energy’s Carbon Storage Research program through the National Energy Technology Laboratory (NETL). Author Contribution PP: Designed and executed the experiment, formal analysis; writing first draft; AH: Image processing; formal analysis; writing first draft; PB: Designed and executed the experiment; review and editing. PS: Experimental design; project supervision; ZK: Experimental design; project supervision; formal analysis, writing first draft, funding acquisition. All co-authors contributed toward writing and editing the complete draft. Acknowledgements The co-authors kindly acknowledge the supporting contributions from the research technologists at the Center for Quantitative Imaging at Penn State University during the execution of the experiment. We gratefully acknowledge the use of Mango (via the web platform WebMango), a software tool for 3D image processing which has been developed at the Australian National University (ANU), in particular the Department of Material Physics. Processing was done on the high performance Fujitsu Primergy cluster managed by National Computational Infrastructure (NCI) and located on the ANU campus. References Li, X., Akbarabadi, M., Karpyn, Z. T., Piri, M. & Bazilevskaya, E. Experimental investigation of carbon dioxide trapping due to capillary retention in saline aquifers. Geofluids 15, 563–576 (2015). Øren, P. E. et al. In-situ pore-scale imaging and image-based modelling of capillary trapping for geological storage of CO2. International Journal of Greenhouse Gas Control 87, 34–43 (2019). Purswani, P., Johns, R. T. & Karpyn, Z. T. Impact of wettability on capillary phase trapping using pore-network modeling. Advances in Water Resources 184, 104606 (2024). Kohanpur, A. 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Ejehu, O., Moghanloo, R. & Nashed, S. Predictive Modeling and Simulation of CO2 Trapping Mechanisms: Insights into Efficiency and Long-Term Sequestration Strategies. Energies 18, 4071 (2025). Purswani, P., Tawfik, M. S., Karpyn, Z. T. & Johns, R. T. On the development of a relative permeability equation of state. Comput Geosci 24, 807–818 (2020). Purswani, P., Johns, R. T., Karpyn, Z. T. & Blunt, M. Predictive Modeling of Relative Permeability Using a Generalized Equation of State. SPE Journal 26, 191–205 (2021). Krevor, S. et al. Subsurface carbon dioxide and hydrogen storage for a sustainable energy future. Nat Rev Earth Environ 4, 102–118 (2023). Huang, R., Herring, A. L. & Sheppard, A. Effect of Saturation and Image Resolution on Representative Elementary Volume and Topological Quantification: An Experimental Study on Bentheimer Sandstone Using Micro-CT. Transp Porous Med 137, 489–518 (2021). Purswani, P., Karpyn, Z., Herring, A., Borate, P. & Shokouhi, P. Pore-Scale CO₂-Brine Coreflood X-Ray CT Dataset (CO2XCT). DataCommons@PSU https://doi.org/10.26208/S97R-HZ89 (2025). Sheppard, A. P., Sok, R. M. & Averdunk, H. Techniques for image enhancement and segmentation of tomographic images of porous materials. Physica A: Statistical Mechanics and its Applications 339, 145–151 (2004). Latham, S. J., Varslot, T. & Sheppard, A. Automated registration for augmenting micro-CT 3D images. ANZIAMJ 50, 534 (2008). Freund, P., Bachu, S., Simbeck, D., Thambimuthu, K. & Gupta, M. Annex I: Properties of CO2 and Carbon-Based Fuels . (2005). Additional Declarations No competing interests reported. Supplementary Files PurswaniNatSciDataSI.docx GA.png 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. 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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-8349129","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"data-descriptor","associatedPublications":[],"authors":[{"id":572162752,"identity":"de4991b2-1722-457d-af64-7e5203908ade","order_by":0,"name":"Prakash Purswani","email":"","orcid":"","institution":"The Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Prakash","middleName":"","lastName":"Purswani","suffix":""},{"id":572162753,"identity":"b9be2985-e98d-4f89-a8a6-378bef8b53d4","order_by":1,"name":"Anna Herring","email":"","orcid":"","institution":"The University of Tennessee","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Herring","suffix":""},{"id":572162754,"identity":"73efcce1-a2e9-482b-88d4-10fc8a4a0a96","order_by":2,"name":"Prabhav Borate","email":"","orcid":"","institution":"The Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Prabhav","middleName":"","lastName":"Borate","suffix":""},{"id":572162755,"identity":"bd10beda-2354-4df6-b756-bbb58fbdb118","order_by":3,"name":"Parisa Shokouhi","email":"","orcid":"","institution":"The Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Parisa","middleName":"","lastName":"Shokouhi","suffix":""},{"id":572162756,"identity":"f9f495ed-4748-4b7f-9399-17c7bb0ec25c","order_by":4,"name":"Zuleima Karpyn","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYBAC+xkJYFoOwmUjQgvjjANg2pgELTMbwHRiA9FamKWZn30ubLuTvp3/jAHDh7LDhLWwybEZz57Z9ix354wcA8YZ54jQwiPHYMzM23Y4d8MNHgMQg7AWCWn2zyCV6Qbnzxgw/yVGi4FkD9iWBIMDOQbMjERpkThTzAz0guHOGWkFB3vOpRPWYj8jfTNzQdlheXP+wxsf/CizJqwFBJgZgdFhAGQcIE49SAvDH4iWUTAKRsEoGAVYAQAOHjlPCyXAmAAAAABJRU5ErkJggg==","orcid":"","institution":"The Pennsylvania State University","correspondingAuthor":true,"prefix":"","firstName":"Zuleima","middleName":"","lastName":"Karpyn","suffix":""}],"badges":[],"createdAt":"2025-12-12 22:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8349129/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8349129/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100126822,"identity":"c21297af-081e-4bf2-8c72-19a010c376d9","added_by":"auto","created_at":"2026-01-13 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07:57:14","extension":"xml","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89700,"visible":true,"origin":"","legend":"","description":"","filename":"2f9fb52a2ee7459a91369758d31be6251structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/6dea40cc2a4109219fc7806c.xml"},{"id":100366231,"identity":"6daaf688-e7ed-49a1-bd46-a74e7f0c5175","added_by":"auto","created_at":"2026-01-16 07:56:08","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":104149,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/b278110d2a95641541fb6ba8.html"},{"id":100365987,"identity":"f1af5e0c-897f-4f3d-96ec-673153439a50","added_by":"auto","created_at":"2026-01-16 07:55:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":376193,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the experimental setup and a photograph of the core holder and critical experimental components inside of the X-ray CT cabinet\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/885618457c4c2cdf6b6de0bc.png"},{"id":100366072,"identity":"c2279706-6df4-43eb-b9d1-91255fc22e22","added_by":"auto","created_at":"2026-01-16 07:55:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":133581,"visible":true,"origin":"","legend":"\u003cp\u003eKey stages of the coreflooding experiment highlighting direction of flow as well as stages of image acquisition\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/5c8f9a4868c96956351ee0cd.png"},{"id":100126812,"identity":"5ff4a326-f23c-4c4d-80a9-f3267bb4d6d5","added_by":"auto","created_at":"2026-01-13 09:25:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":452331,"visible":true,"origin":"","legend":"\u003cp\u003eMidway horizontal cross-section raw gray scale images (top row) and corresponding segmented images (bottom row) at selected experimental conditions. Gray and bright white regions represent the solid phase; black and darker regions inside the rock represent the gas phase; and darker gray regions inside the rock represent the brine phase.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/c657cfcd4289aa231fff539e.png"},{"id":100366159,"identity":"066eafdb-8fa8-4acb-89f9-5e02db8d72fa","added_by":"auto","created_at":"2026-01-16 07:56:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":976938,"visible":true,"origin":"","legend":"\u003cp\u003e3D pore occupancy of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e at three key experimental stages, with corresponding \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e saturation values\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/80c8ab8c89d2d68dc29178a7.png"},{"id":100365858,"identity":"88f2fad4-f61f-4cf5-964a-098f884fc754","added_by":"auto","created_at":"2026-01-16 07:55:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":97405,"visible":true,"origin":"","legend":"\u003cp\u003eAverage pore pressure versus time graph illustrating pressure stability and evolution during the various stages of the experiment\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/80d84f9b84e68270d7728489.png"},{"id":100366115,"identity":"276c4d19-c59c-41bd-9f13-32c304e8266c","added_by":"auto","created_at":"2026-01-16 07:55:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1871952,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/13ca7b35-f82d-45bb-87e5-835fd0a0bc7d.pdf"},{"id":100365932,"identity":"d4645e21-7b51-426f-ace7-10d9f7007902","added_by":"auto","created_at":"2026-01-16 07:55:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":527648,"visible":true,"origin":"","legend":"","description":"","filename":"PurswaniNatSciDataSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/0a11c070958f4f5a5699ea70.docx"},{"id":100365948,"identity":"7404b4a4-27b4-4f9f-ad22-3de9598b52d2","added_by":"auto","created_at":"2026-01-16 07:55:46","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":976938,"visible":true,"origin":"","legend":"","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-8349129/v1/c11135ea08d56185bdb01469.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eUnderstanding and predicting multiphase fluid behavior in subsurface porous media is a central challenge across a wide range of energy, environmental, and storage applications. Whether the goal is to manage the migration of injected gases, optimize working-gas recovery, assess storage security, or model pressure evolution, reliable predictions require a detailed understanding of how immiscible or partially miscible fluids move, redistribute, and become trapped within complex geologic pore structures.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e These challenges are shared across systems such as underground hydrogen storage (UHS), geologic carbon sequestration (GCS), compressed air energy storage, geothermal operations, and enhanced recovery processes in hydrocarbon reservoirs. Across these domains, pore-scale displacement dynamics, driven by the interplay of capillary, viscous, and gravitational forces, strongly influence emergent behaviors at core, reservoir, and basin scales.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccurate characterization of these processes is essential for building predictive models that can guide engineering decisions. Numerical reservoir simulations, pore-network models, and data-driven machine-learning frameworks all rely on constitutive relationships and parameters that reflect the underlying pore-scale physics. However, parameterizing these models remains difficult due to the limited availability of high-quality, experimentally validated data acquired under realistic reservoir conditions. Multiphase flow datasets suitable for model calibration, benchmarking, and AI/ML training are particularly scarce, especially those providing synchronized flow and pressure measurements, along with high-resolution images.\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e As artificial intelligence becomes increasingly central to subsurface characterization, monitoring, and forecasting, the demand for rich, well-documented, high-fidelity datasets continues to rise.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWithin this broader landscape of subsurface applications, geologic carbon sequestration (GCS) represents a critical strategy for mitigating anthropogenic CO\u003csub\u003e2\u003c/sub\u003e emissions and stabilizing atmospheric greenhouse gas concentrations.\u003csup\u003e\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e GCS involves the injection of large volumes of CO\u003csub\u003e2\u003c/sub\u003e into deep geologic formations such as saline aquifers or depleted hydrocarbon reservoirs, where long-term storage security depends on the interplay of multiphase displacement, residual trapping, dissolution, and mineralization processes. Reliable prediction of CO\u003csub\u003e2\u003c/sub\u003e fate requires a robust understanding of these mechanisms at the pore scale, where wettability, pore geometry, and grain-scale heterogeneity exert strong control on fluid connectivity and migration pathways.\u003c/p\u003e \u003cp\u003ePredictive modeling of CO\u003csub\u003e2\u003c/sub\u003e behavior at the reservoir scale depends heavily on accurate parameterization of rock and fluid properties that reflect these fundamental processes across a wide range of spatial and temporal scales.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e In fact, pore-scale insights are often crucial for determining reliable macroscopic flow functions (e.g., relative permeability and capillary pressure) that feed into reservoir-scale simulations.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e A major source of uncertainty in current models stems from the incomplete understanding of multiphase flow dynamics at the pore scale. The heterogeneity of natural geologic formations, coupled with the complex interplay of capillary, viscous, and gravitational forces, introduces variability in CO\u003csub\u003e2\u003c/sub\u003e saturation, preferential flow pathways, and trapping efficiency across the formation. Centimeter- to meter-scale capillary and permeability heterogeneities, which manifest from pore-scale variability in grain size, wettability, and pore geometry, can substantially alter flow and trapping behavior.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhile numerical simulations and pore-network models have provided valuable insight into multiphase flow and trapping mechanisms,\u003csup\u003e3,4\u003c/sup\u003e rigorous experimental validation remains essential. However, relevant datasets remain scarce due to the technical and logistical challenges associated with conducting core-scale experiments under high-pressure and high-temperature environments representative of geologic reservoirs. Many existing datasets lack the resolution, documentation, or fail to capture the full drainage-imbibition cycle necessary for understanding hysteresis in fluid flow behavior.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e These limitations impede progress not only in GCS but also in other subsurface energy technologies, including UHS, where similar gas\u0026ndash;brine interactions control operational performance and storage reliability.\u003c/p\u003e \u003cp\u003eTo address this gap, we present a high-resolution imaging dataset of multiphase fluid displacement in sandstone cores subjected to supercritical CO\u003csub\u003e2\u003c/sub\u003e (\u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e) and brine core-flooding under controlled laboratory conditions.\u003c/p\u003e \u003cp\u003eThe primary objective of our study is to generate a reproducible and well-characterized dataset that captures key aspects of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-brine displacement under reservoir-relevant conditions. A synthetic sintered glass sample was used to mimic the pore structure of conventional sandstones while avoiding mineralogical complexity and rock\u0026ndash;fluid interactions, ensuring that observed displacement patterns reflect physical processes rather than chemical effects. Specifically, our dataset offers:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eA comprehensive suite of 3D \u0026micro;CT images representing dry, drainage, and imbibition states;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eContinuous pressure and flow rate data for model calibration and validation;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSegmented datasets with labeled rock and fluid phases for quantitative analysis;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDetailed measurements of fluid saturations and morphological descriptors suitable for analyzing phase connectivity, interfacial geometry, and pore-scale flow patterns;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDual-quality image sets (high- and low-noise) at residual CO\u003csub\u003e2\u003c/sub\u003e saturation, enabling development and testing of image denoising and rapid acquisition techniques.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eBecause the dataset captures fundamental multiphase displacement processes under well-constrained boundary conditions, it is relevant not only for GCS but for a broad set of subsurface energy systems where gas\u0026ndash;brine displacement governs injectivity, cycling efficiency, and long-term storage behavior. The data are also well suited for reuse across a variety of research domains, including image segmentation algorithm development, digital rock physics, machine learning training sets, and numerical model benchmarking.\u003c/p\u003e \u003cp\u003eMoreover, our dataset is one of the few publicly available resources that combine precise experimental control, imaging fidelity, and documentation under GCS-relevant conditions. All data, including raw and processed images, pressure records, and segmentation masks, are hosted on an open-access datacommons@psu repository,\u003csup\u003e26\u003c/sup\u003e in alignment with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. We anticipate that these data will support a broad range of scientific efforts ranging from improving pore-scale modeling techniques and accelerating AI/ML workflows to informing risk assessments and operational strategies for CO\u003csub\u003e2\u003c/sub\u003e injection, hydrogen storage, and other subsurface energy applications.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eIn these experiments, we performed high-pressure, high temperature coreflooding to study the dynamics of CO\u003csub\u003e2\u003c/sub\u003e transport at representative subsurface conditions. The experimental procedure, equipment used, data collection methods, and operating conditions are detailed below. The operating pressure-temperature conditions were maintained such that CO\u003csub\u003e2\u003c/sub\u003e remained in a supercritical state (\u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e) throughout all displacement stages. CO\u003csub\u003e2\u003c/sub\u003e-saturated brine was used to minimize mass-transfer effects between the brine and the \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e phase during individual displacement steps. Both drainage and imbibition cycles were studied to determine initial and residual CO\u003csub\u003e2\u003c/sub\u003e saturations. High-resolution X-ray imaging was coupled with the coreflooding experiments, enabling detailed investigations of fluid saturations and fluid morphological descriptors.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental setup and image acquisition\u003c/h2\u003e \u003cp\u003eThe experimental setup consisted of the following equipment: X-ray imaging cabinet; high-pressure Quizix pumps; heating elements and jackets; aluminum core holder; thermocouples and temperature reader; pressure transducers; high-pressure stainless-steel flow lines; back-pressure regulator; high-pressure Parr vessel for preparing CO\u003csub\u003e2\u003c/sub\u003e-saturated brine; CO\u003csub\u003e2\u003c/sub\u003e gas cylinder; sodium iodide-doped brine solution for imaging contrast; data acquisition system. A schematic illustration of the experimental setup and a photograph showing the interior of the X-ray chamber and staged experimental setup are provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFlow lines from the top and bottom of the core holder were intentionally kept long and coiled to allow the internal stage within the X-ray chamber to freely rotate during X-ray scans. The X-ray chamber included designed openings for connecting flow lines and pumps located externally. Similarly, the data acquisition setup was situated outside the X-ray chamber. The flow through the sample was directed vertically to facilitate gravity-stable displacement. All experimentation was performed at a fixed injection rate of 1 cc/min and differential pressure through the rock was continuously monitored.\u003c/p\u003e \u003cp\u003eX-ray images were acquired at distinct stages during the experiment once equilibrium, indicated by pressure stability, was reached. The images were acquired using the GE v|tome|x L X-ray \u0026micro;CT system at the Center for Quantitative Imaging, a collaborative facility within the Institute of Energy and Environment at Penn State University (Center for Quantitative Imaging | Institute of Energy and the Environment). At these equilibrium conditions, flow was temporarily terminated to allow image acquisition at constant pressure.\u003c/p\u003e \u003cp\u003eA dry, synthetic sintered glass cylindrical rock sample acquired from Robu\u0026reg; (ROBU\u0026reg; Glasfilter-Ger\u0026auml;te GmbH) was used in this study. The sample was ~\u0026thinsp;1 inch in diameter and ~\u0026thinsp;3 inches in length with a measured porosity of ~\u0026thinsp;24% and brine permeability of ~\u0026thinsp;98 mD. The synthetic sintered glass sample was selected because its pore structure and flow properties approximate those of conventional sandstones, while eliminating mineralogical heterogeneity and rock\u0026ndash;fluid chemical interactions. The sample was cleaned and dried and installed inside the core holder, sealed in a rubber jacket, and fitted with flow distributor ends to facilitate fluid passage. In addition to pure CO\u003csub\u003e2\u003c/sub\u003e, brine with 1 M NaI was used to provide contrast between the CO\u003csub\u003e2\u003c/sub\u003e and brine phase for easier phase distinction and image processing. Water was used as the confining fluid between the jacket and the interior walls of the core holder, with confining pressure maintained by a dedicated confining pump.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Experimental procedure\u003c/h2\u003e \u003cp\u003eThe experimental procedure outlined in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e comprised the following stages:\u003c/p\u003e \u003cp\u003e1. \u003cem\u003eVacuum\u003c/em\u003e: The sample was subjected to a confining pressure of 300 psi, while a vacuum pump reduced pore pressure to approximately 0.018 psi. This state was maintained for several hours to achieve vacuum conditions within the pore space and flow lines. An X-ray scan was acquired at this stage to capture the internal pore heterogeneity.\u003c/p\u003e \u003cp\u003e2. \u003cem\u003e100% gCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e: CO\u003csub\u003e2\u003c/sub\u003e gas was introduced into the sample to displace residual air from the pore spaces.\u003c/p\u003e \u003cp\u003e3. \u003cem\u003e100% scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e: The pore pressure within the rock was incrementally increased by steps of 50\u0026ndash;100 psi to achieve supercritical conditions, ensuring the confining pressure was consistently maintained 250\u0026ndash;300 psi higher than the pore pressure. This stage also involved thorough leak checks to ensure system integrity.\u003c/p\u003e \u003cp\u003e4. \u003cem\u003eVacuum Saturation with Brine\u003c/em\u003e: The system was depressurized, vacuum conditions were reestablished, and brine was introduced into the rock to achieve complete pore saturation.\u003c/p\u003e \u003cp\u003e5. \u003cem\u003eBrine Flow for Permeability Measurement\u003c/em\u003e: Brine was flowed through the sample at varying flow rates, and the resulting pressure drop across the sample was measured, enabling permeability estimation (see Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2 in Supplementary Materials). This permeability measurement stage occurred at 500 psi confining pressure. Subsequently, pore pressure was raised in gradual stages to match supercritical CO\u003csub\u003e2\u003c/sub\u003e conditions, followed by an increase in sample temperature to reach experimental conditions. An X-ray scan was acquired at this stage.\u003c/p\u003e \u003cp\u003e6. \u003cem\u003e100% CO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e-Saturated Brine\u003c/em\u003e: CO\u003csub\u003e2\u003c/sub\u003e-saturated brine, prepared in the high-pressure Parr vessel, was introduced to displace resident brine fully. An X-ray scan was acquired after complete replacement.\u003c/p\u003e \u003cp\u003e7. \u003cem\u003eInitial scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e: Multiphase flow experiments began with injection of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e from the bottom of the sample. Flow continued for several hours until equilibrium was reached, establishing initial \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e saturation. An X-ray scan was performed at the conclusion of this step.\u003c/p\u003e \u003cp\u003e8. \u003cem\u003eFinal scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e: Analysis of the previous X-ray scan indicated inefficient brine displacement, characterized by \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e fingering around the sample rim. To address this, the flow direction was inverted, with \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e now injected from the top. Following extended injection, another X-ray scan verified successful brine displacement. Detailed saturation profiles are discussed in a subsequent section.\u003c/p\u003e \u003cp\u003e9. \u003cem\u003eResidual scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e: Lastly, CO\u003csub\u003e2\u003c/sub\u003e-saturated brine was injected from the bottom to displace \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e, continuing through multiple pore volumes until achieving residual \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e saturation. At this final stage, two types of X-ray scans were conducted, (1) A fast scan at low X-ray exposure, (2) A slow scan at high X-ray exposure. These two scan types facilitated comparative analyses under identical two-phase conditions.\u003c/p\u003e \u003cp\u003eAll relevant experimental conditions for each stage are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"609\" height=\"186\"\u003e\u003c/p\u003e \u003cp\u003eAll X-ray images were acquired after allowing time for fluids to stabilize between each experimental stage and ensuring pressure stability in the system. The X-ray power settings were calibrated to a voltage of 220 kV and a current of 110 \u0026micro;A during the initial assembly of the setup with the coreholder installed without flow, and these settings were maintained throughout all scans. Flexible stainless steel high-pressure flow lines were used and were kept longer with a larger dead-volume to allow for the free rotation of the core holder during the scanning process. A wider acrylic stage was custom-built to allow for the coiled flow lines to rest near the bottom injection port of the core holder to aid with the sample rotation. The vacuum and single phase scans were completed in ~\u0026thinsp;1.5 hours each, while all multiphase scans were completed in ~\u0026thinsp;2.2 hours each. Lastly, an additional low quality scan (fast scan) was completed for the last experimental stage in ~\u0026thinsp;20 mins. All acquired image data was at a voxel resolution of 25 \u0026micro;m.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Image processing\u003c/h2\u003e \u003cp\u003eThree-dimensional volumes were processed using WebMango, a web-based image processing software developed and supported by the Australian National University.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eVacuum\u003c/em\u003e scan was converted to a binary segmentation with every voxel labeled as solid (1) or void (0) phase, utilizing the \u0026ldquo;converging active contours\u0026rdquo; (CAC)\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. To initialize the CAC algorithm, user inputs define lower and upper gray levels beyond which voxels are automatically assigned as phase 0 or phase 1. Voxels with values between the designated gray levels are initially set as \u0026ldquo;unknown\u0026rdquo; and are labeled subsequently as phase interfaces grow until disparate regions meet. Interface growth rates for the two phases can be separately controlled. For the \u003cem\u003eVacuum\u003c/em\u003e data set, visual inspection suggested a void:solid growth rate of 0.95 (indicating that void interfaces grow slightly slower than the solid) provided a reasonable binary segmentation. The applied CAC segmentation parameters for all data volumes are provided in the supporting information (see Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eVacuum\u003c/em\u003e scan was found to be originally misaligned compared to the subsequent scans owing to minor movement of the sample during fluid injection. To enable three-phase (solid, CO\u003csub\u003e2\u003c/sub\u003e, and brine) voxel labeling, the \u003cem\u003eVacuum\u003c/em\u003e data was co-registered to the saturated scans via rigid translation adjustment\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e based on comparison to the scan acquired at stage 7 of the experiment: \u003cem\u003eInitial scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e \u003cem\u003eflood\u003c/em\u003e data. The aligned vacuum solid phase was subsequently used as a mask for saturated-flow experiment scans. Fluid phases were identified by applying additional CAC routines restricted to voxels occupying the void space. In these routines, low-intensity voxels were labeled as \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e, while high-intensity voxels were labeled as brine.\u003c/p\u003e \u003cp\u003eFor partially saturated scans, CAC initiation incorporated an additional gradient-based criterion: voxels with gray-scale gradients above a specified threshold were classified as \u0026ldquo;unknown,\u0026rdquo; even if their gray values would otherwise indicate automatic classification as \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e or brine. Applying this gradient threshold mitigates partial-volume effects near solid interfaces, improving segmentation accuracy in regions with steep intensity transitions. As reported in Table S2, similar values for lower and upper gray level thresholds, gradient thresholds, and interface speed ratios were used for all data sets. Minor variations in parameters were utilized for the two scans with the lowest levels of brine present (i.e. the \u003cem\u003eVacuum\u003c/em\u003e and \u003cem\u003eInitial scCO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e \u003cem\u003eflood\u003c/em\u003e volumes).\u003c/p\u003e \u003cp\u003eFor all data sets, speckle noise removal (i.e. removal of voxels suspected to be falsely labeled as the \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e phase) was accomplished by converting small \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-labeled clusters to the brine phase. A size of 375 voxels was chosen as the noise removal threshold based on a careful inspection of cluster size histograms (see Figure S3 in the supporting information). Quantitative phase volumes and topological metrics were calculated based on these final de-noised segmentations and are discussed in Section 3.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Key quantitative metrics from processed data","content":"\u003cp\u003eIn this section, we summarize key quantitative metrics from image analysis, examining fluid saturations, phase connectivity, and pressure histories across the various experimental stages. By providing these quantitative metrics, we aim to offer a practical benchmark for researchers conducting related investigations using our data sets.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Fluid saturation and morphological information\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows cross-sections of the raw and segmented CT images for the key experimental stages. The images highlight the complexity of the pore structure and the spatial distribution of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e within the pore space at different points in the experiment. Analysis of the first multiphase scan, conducted after the initial (upwards) \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e injection, confirmed that the injection did not sweep the pore space effectively. Strong fingering of the injected \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e caused the flow to move predominantly along the peripheries of the sample, bypassing the central pore network (see the middle scan in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and the left image in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Based on this observation, the injection direction was changed to allow the injection of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e from the top of the sample to improve the sweep efficiency. Contrary to our initial expectation that injecting the lighter \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e from the bottom would provide a gravity-stable displacement, we observed that introducing \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e from the top of the sample resulted in a more effective sweep. The density and viscosity of CO\u003csub\u003e2\u003c/sub\u003e in its supercritical state are sufficiently high to support a more favorable injection sequence when introduced from above.\u003c/p\u003e \u003cp\u003eFollowing this adjustment, we observed a significant increase in the displacement of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-saturated brine. These findings have important implications for designing injection strategies for subsurface gas storage, especially when unfavorable viscosity ratios lead to unstable displacement. This is particularly relevant for gases such as hydrogen, which can present even more adverse viscosity contrasts than \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast to \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e injection, brine injection was effective on the first attempt and resulted in relatively high? residual trapping of \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e. We infer that the trapped \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e is primarily due to two pore-scale mechanisms at play including bypassing flow of the injected \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-saturated brine and snap-off events. Both mechanisms promote the breakup of larger \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e clusters into smaller disconnected ganglia, which then become immobilized by capillary forces. Over the course of imaging, no remobilization of the trapped \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e was observed. Although longer rest periods could, in principle, enable processes such as Ostwald ripening to redistribute scCO₂, such effects should remain limited because mass-transfer\u0026ndash;driven dissolution had largely equilibrated and the brine was pre-saturated with scCO₂ under the experimental conditions. Lastly, the trapped \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e was distributed throughout the pore space without evidence of local clusters with significantly larger accumulations.\u003c/p\u003e \u003cp\u003eThe CAC initiation parameters and denoising value selections impact quantitative results. For the denoised \u003cem\u003eVacuum\u003c/em\u003e data, for universal increases/decreases of 10% in gray level thresholds, porosity values vary by \u003csup\u003e+\u003c/sup\u003e/\u003csub\u003e\u0026minus;\u003c/sub\u003e1\u0026ndash;2% (porosity value ranges from 23\u0026ndash;26%); void phase Euler characteristic values are more sensitive but still range by \u0026lt;\u0026thinsp;10% (Table S2 in Supplementary Materials). Noise removal has a more significant impact on topological metrics;\u003csup\u003e7,25\u003c/sup\u003e in the Initial scCO\u003csub\u003e2\u003c/sub\u003e data volume this causes a transition from positive to negative Euler values as small isolated \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-labeled voxels are relabeled (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This result emphasizes the conclusions of Huang et al.,\u003csup\u003e25\u003c/sup\u003e who state that appropriate noise and/or size exclusion must be carried out to obtain topological metrics relevant to the phase of interest (in this case, \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e).\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\u003eSmall cluster removal was applied to eliminate \u0026ldquo;speckle\u0026rdquo; noise arising from mislabeling during the segmentation process. Values are shown for segmented data sets with all \u003cem\u003esc\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e-labeled clusters included, and for data sets with clusters smaller than 375 voxels removed.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBefore Noise Removal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c11\" namest=\"c6\"\u003e \u003cp\u003eAfter Noise Removal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eβ\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eβ\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eχ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePorosity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eSaturation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVacuum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e266,121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-255,164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e266,095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-265,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e24.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003escCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003esaturated brine\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial scCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4,428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2,695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFinal scCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105,374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-101,299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e105,355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-104,982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e82.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidual scCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56,170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8,028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2,961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5,067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e13.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Pressure measurement\u003c/h2\u003e \u003cp\u003eOmega pressure sensors (digital pressure transducers, PX409 series) were installed upstream and downstream of the rock sample to monitor pore pressures continuously throughout the experiment. Average pore pressures are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, clearly delineating each experimental stage. It can be observed that average pore pressures were maintained between ~\u0026thinsp;1200 and 1400 psi during all multiphase displacement stages. Similarly, temperature conditions were consistently maintained at ~\u0026thinsp;47\u0026deg;C, ensuring the CO\u003csub\u003e2\u003c/sub\u003e remained in a supercritical state\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In addition, during the vacuum-saturation stage, differential pressures at varying brine flow rates were recorded to determine rock permeability, resulting in a measured brine permeability of ~\u0026thinsp;98 mD. These detailed pressure measurements are provided in the Supporting Information (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWhile this dataset provides valuable insights into multiphase displacement under controlled conditions, it is important to note certain limitations. First, the experiments were conducted at a single pressure\u0026ndash;temperature condition representative of subsurface storage environments; therefore, the findings may not capture variability associated with different reservoir conditions. Second, the image resolution of 25 \u0026micro;m, although sufficient for pore-scale analysis, is relatively low compared to some recent studies employing sub-10 \u0026micro;m voxel sizes. Higher-resolution imaging could reveal additional details of pore connectivity and interfacial geometry. These constraints should be considered when applying the dataset for model development or benchmarking.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Data availability","content":"\u003cp\u003eThe datasets shared in this paper are made publicly available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.26208/S97R-HZ89\u003c/span\u003e\u003cspan address=\"10.26208/S97R-HZ89\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The datasets include raw and segmented cross-section images of the key experimental stages (see midway example cross-sections in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). All raw images were generated by cropping the original X-ray scans using a circular stencil (900 pixel\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) and selecting a portion of the sample after removing edge-related X-ray scattering artifacts. Each imaging dataset consists of 1700 slices providing a sample height of 4.25 cm and cross-sectional diameter of 2.25 cm. The raw images remain fully unprocessed besides cropping and were generated from the sinograms of the acquired X-ray images and the GE reconstruction software while the segmented images were processed with the Mango Software (see details in Section 2.3).\u003c/p\u003e \u003cp\u003eThe detailed methodology for the experiments performed here is expected to guide future research involving multiphase flow and transport in porous media with applications to geologic gas (carbon dioxide, hydrogen, methane) storage and contaminant transport during groundwater remediation. The purpose of these datasets is to enable further investigation and improvements of image processing workflows including image denoising, image segmentation, and quantitative fluid-rock metric estimation. The segmented images and corresponding quantitative metrics extracted in this work are to serve as a comparison to any future investigation in the multiphase image processing domains. Finally, the simultaneous availability of low-quality and high-quality images on the same multiphase will guide the development of novel image processing involving the use of machine learning and artificial intelligence wherein the high-quality image can serve as benchmark and image augmentation methods can allow for data multiplication. If successful, these tools will enable faster image acquisition time while maintaining superior quality in the estimation of quantitative metrics which are critical for multiphase fluid flow characterization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing financial interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was completed as part of the Science-informed Machine learning to Accelerate Real Time decision making for Carbon Storage (SMART-CS) Initiative (edx.netl.doe.gov/SMART). Support for this initiative was provided by the U.S. Department of Energy\u0026rsquo;s (DOE) Office of Fossil Energy\u0026rsquo;s Carbon Storage Research program through the National Energy Technology Laboratory (NETL).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003ePP: Designed and executed the experiment, formal analysis; writing first draft; AH: Image processing; formal analysis; writing first draft; PB: Designed and executed the experiment; review and editing. PS: Experimental design; project supervision; ZK: Experimental design; project supervision; formal analysis, writing first draft, funding acquisition. All co-authors contributed toward writing and editing the complete draft.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe co-authors kindly acknowledge the supporting contributions from the research technologists at the Center for Quantitative Imaging at Penn State University during the execution of the experiment. We gratefully acknowledge the use of Mango (via the web platform WebMango), a software tool for 3D image processing which has been developed at the Australian National University (ANU), in particular the Department of Material Physics. Processing was done on the high performance Fujitsu Primergy cluster managed by National Computational Infrastructure (NCI) and located on the ANU campus.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi, X., Akbarabadi, M., Karpyn, Z. T., Piri, M. \u0026amp; Bazilevskaya, E. Experimental investigation of carbon dioxide trapping due to capillary retention in saline aquifers. \u003cem\u003eGeofluids\u003c/em\u003e 15, 563\u0026ndash;576 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Oslash;ren, P. 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Automated registration for augmenting micro-CT 3D images. \u003cem\u003eANZIAMJ\u003c/em\u003e 50, 534 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreund, P., Bachu, S., Simbeck, D., Thambimuthu, K. \u0026amp; Gupta, M. \u003cem\u003eAnnex I: Properties of CO2 and Carbon-Based Fuels\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.ipcc.ch/site/assets/uploads/2018/03/srccs_annex1-1.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\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":"","lastPublishedDoi":"10.21203/rs.3.rs-8349129/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8349129/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Subsurface gas storage, particularly the sequestration of CO, continues to remain an active area of research for mitigating atmospheric CO concentrations. However, experimental datasets providing direct, high-resolution measurements of CO₂ transport, saturation, and pore-scale dynamics under realistic reservoir conditions remain limited, due primarily to experimental complexity. In this study, we present a comprehensive dataset from supercritical CO (CO)-brine core-flooding experiments conducted at relevant subsurface conditions, employing a sophisticated core holder system capable of sustaining high-pressure and high-temperature environments within an X-ray microcomputed tomography (\u0026micro;CT) setup. Continuous monitoring of flow rates and system pressures accompanied X-ray imaging performed at equilibrium conditions, capturing fluid saturations with a high spatial resolution of 25 \u0026micro;m. CO-equilibrated brine was utilized to minimize mass-transfer effects, and both drainage and imbibition scenarios are thoroughly documented. The unique dataset includes high-resolution 3D raw and segmented X-ray images detailing the dry and fluid-saturated conditions, complemented by quantitative metrics of fluid saturation, morphological descriptors, and phase connectivity. In addition, dual-quality X-ray image sets of high- and low-noise scans captured at residual CO saturation after imbibition are provided, enabling comparative analysis and advancements in rapid image-acquisition techniques. The detailed pressure histories and segmented morphological data facilitate advanced numerical model validation and serve as a benchmark dataset for image segmentation algorithm development. All data have been curated and uploaded to an open-access repository, promoting broad usability and fostering innovation in subsurface gas storage research.","manuscriptTitle":"Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 09:25:53","doi":"10.21203/rs.3.rs-8349129/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":"e8e5887e-743f-4acf-8dbb-681ff4c078a0","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T23:53:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 09:25:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8349129","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8349129","identity":"rs-8349129","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}