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Updated: Jun 5, 2026

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography
Published on: February 25, 2015
Multi-Stage X-Ray Imaging Dataset of Phase Trapping in Porous Media
Prakash Purswani1,2, Anna Herring3, Prabhav Borate4
1John and Willie Leone Family Department of Energy and Mineral Engineering and the EMS Energy Institute, The Pennsylvania State University, University Park, PA, 16802, USA.
Abstract:
Subsurface gas storage, particularly the sequestration of CO2, continues to remain an active area of research for mitigating atmospheric CO2 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 CO2 (scCO2)-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. scCO2-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 scCO2 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.
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