A laboratory µ-CT scanner was used to image the dissolution of Ketton, Estaillades, and Portland limestones in the presence of CO2-acidified brine at reservoir conditions (10 MPa and 50 °C) at two injected acid strengths for a period of 4 h. Each sample was scanned between 6 and 10 times at ~4 µm resolution and multiple effluent samples were extracted. See also paper: H.P. Menke et al. Geochimica et Cosmochimica Acta 204 (2017) 267-285. https://doi.org/10.1016/j.gca.2017.01.053.

Grant: ACT ELEGANCY, Project No 271498. This repository includes CMG simulation input and output files, processed micro-CT data, figure 3 data and plot, pore network modeling sensitivity examples

The datasets contains two sets of three dimensional images of Ketton carbonate core of size 5 mm in diameter and 11 mm in length scanned at 7.97µm voxel resolution using Versa XRM-500 X-ray Microscope. The first set includes 3D dataset of dry (reference) Ketton carbonate. The second set includes 3D dataset of reacted Ketton carbonate using hydrochloric acid.

The datasets contain FIB-SEM and X-ray micro-tomographic images of a wettability-altered carbonate rock sample before and after dissolution with reactive CO2-saturated brine at reservoir pressure and temperature conditions. The data were acquired with the aim of investigating CO2 storage in depleted oil fields that have oil-wet or mixed-wet conditions. Our novel procedure of injecting oil after reactive transport has revealed previously unidentified (ghost) regions of partially-dissolved rock grains that were difficult to identify in X-ray tomographic images after dissolution from single fluid phase experiments. The details of image files and imaging parameters are described in readme file.

The datasets contain time-resolved synchrotron X-ray micro-tomographic images (grey-scale and segmented) of multiphase (brine-oil) fluid flow (during drainage and imbibition) in a carbonate rock sample at reservoir pressure conditions. The tomographic images were acquired at a voxel-resolution of 3.28 µm and time-resolution of 38 s. The data were collected at beamline I13 of Diamond Light Source, U.K., with the aim of investigating pore-scale processes during immiscible fluid displacement under a capillary-controlled flow regime. Understanding the pore-scale dynamics is important in many natural and industrial processes such as water infiltration in soils, oil recovery from reservoir rocks, geo-sequestration of supercritical CO2 to address global warming, and subsurface non-aqueous phase liquid contaminant transport. Further details of the sample preparation and fluid injection strategy can be found in Singh et al. (2017). These time-resolved tomographic images can be used for validating various pore-scale displacement models such as direct simulations, pore-network and neural network models, as well as for investigating flow mechanisms related to the displacement and trapping of the non-wetting phase in the pore space.

The datasets contain 5 stitched X-ray micro-tomographic images (grey-scale, doped, difference, segmented porespace and segmented micro-porespace with porespace) and 3 X-ray nano-tomographic images of a region of microporous porespace in Estaillades Limestone. The x-ray tomographic images were acquired at a voxel-resolution of 3.9676 µm using a Zeiss Versa XRM-510 flat-panel detector at 70 kV, 6W, and 85 µA with an exposure time of 0.037s and 64 frames. The X-ray nano-tomographic images were reconstructed using a proprietary filtered back projection algorithm from a set of 1601 projections, collected with the Zeiss Ultra 810 with 32nm voxel size using a 5.4keV energy quasi-monochromatic beam with an exposure time of 90s. The data was collected at Imperial College London and Zeiss Labs with the aim of investigating pore-scale microporosity in carbonates with a heterogenous pore structure. Understanding the effect of microporosity on flow is important in many natural and industrial processes such as contaminant transport, and geo-sequestration of supercritical CO2 to address global warming. These tomographic images can be used for validating various pore-scale flow models such as direct simulations, pore-network and neural network models for upscaling flow across scales.