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Abstract: This study extensively investigates the influence of different pyrolysis temperatures and organic matter contents on the fluid flow and heat transfer properties in oil shale samples. Utilizing CT images to generate three-dimensional digital rock, coupled simulations of CO2 flow and heat transfer were conducted, analyzing parameters such as velocity fields, permeability, temperature fields, average temperatures, and heat transfer coefficients. The results reveal that, for relatively homogeneous oil shale samples, the permeability exhibits a monotonous increase with rising pyrolysis temperature. While the effect of pyrolysis temperature on the distribution characteristics of velocity and temperature fields is minimal, it significantly impacts the heat transfer coefficients. Specifically, the heat transfer coefficients increase significantly in the direction perpendicular to the bedding plane, while they decrease or remain unchanged parallel to it. Additionally, the organic matter content significantly influences the fluid flow and heat transfer properties of shale samples. After undergoing heat treatment, the heterogeneity of pore structures in shale samples varies significantly, affecting the characteristics of fluid flow and heat transfer. The influence of organic matter content and pyrolysis temperature on fluid flow and heat transfer in shale primarily stems from the effect of organic matter pyrolysis on the original pore structure. The development and connectivity of pore networks are closely related to the distribution characteristics of the original organic matter and are not directly correlated with the organic matter content. These findings provide essential theoretical guidance and technical support for the development and utilization of oil shale resources, while also offering valuable references and insights for future research.

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Abstract: Seismic observations show the Earth's inner core has significant and unexplained variation in seismic attenuation with position, depth and direction. Interpreting these observations is difficult without knowledge of the visco- or anelastic dissipation processes active in iron under inner core conditions. Here, a previously unconsidered attenuation mechanism is observed in zinc, a low pressure analog of hcp-iron, during small strain sinusoidal deformation experiments. The experiments were performed in a deformation-DIA combined with X-radiography, at seismic frequencies (∼0.003–0.1 Hz), high pressure and temperatures up to ∼80% of melting temperature. Significant dissipation (0.077 ≤ Q−1(ω) ≤ 0.488) is observed along with frequency dependent softening of zinc's Young's modulus and an extremely small activation energy for creep (⩽7 kJ mol−1). In addition, during sinusoidal deformation the original microstructure is replaced by one with a reduced dislocation density and small, uniform, grain size. This combination of behavior collectively reflects a mode of deformation called “internal stress superplasticity”; this deformation mechanism is unique to anisotropic materials and activated by cyclic loading generating large internal stresses. Here we observe a new form of internal stress superplasticity, which we name as “elastic strain mismatch superplasticity.” In it the large stresses are caused by the compressional anisotropy. If this mechanism is also active in hcp-iron and the Earth's inner-core it will be a contributor to inner-core observed seismic attenuation and constrain the maximum inner-core grain-size to ≲10 km.

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Abstract: In this study, we present experimental investigations on a low-porosity bioclastic calcarenite from the Cotiella Basin in the Spanish Pyrenees. Our objective is to elucidate the dominant failure mechanisms during the laboratory reactivation of natural deformation bands oriented at various angles to the maximum principal stress (σ1) direction. Triaxial compression experiments were conducted at the I12-JEEP beamline of the Diamond Light Source, UK, using a modified version of the Mjolnir cell employed by Cartwright-Taylor et al. (2022). Moreover, 4D (space and time-resolved) X-ray computed tomography images were acquired at 8 μm3 voxel size resolution during the triaxial compression tests (10 MPa to 30 MPa confining pressure). Our mechanical data show that the presence of natural deformation features within the tested samples influences the material's strength. When comparing intact samples of the host rock under the same confining pressures, we observed that these samples exhibit higher peak stresses as opposed to those containing natural deformation features. Our research reveals that new deformation bands are formed as the angle (θ) between the deformation bands and σ1 increases. In this low-porosity carbonate, the reactivation of pre-existing deformation bands only occurs when their dipping angles are close to 70o. To investigate the spatial and temporal relationships among naturally occurring and laboratory induced deformation bands and fractures, we employed time-resolved X-ray CT and Digital Volume Correlation (Figure 1). Utilizing the SPAM open-source software (Stamati et al., 2020), we calculated the volumetric and shear strain fields. The orientation of the laboratory-induced failure planes is influenced by the orientation, width, and presence (or absence) of porosity along the length of the pre-existing natural bands. Additionally, the pre-existing secondary deformation features may contribute to additional mechanical damage, which can either facilitate the development or divert the newly formed failure planes. In summary, our findings emphasize that the presence of natural deformation features weakens the material. We also observe that the reactivation of pre-existing bands occurs primarily at dipping angles near 70o in this low-porosity carbonate. The use of advanced imaging techniques and the SPAM software have allowed us to explore the relationships between the naturally occurring and laboratory-induced deformation features, highlighting the influence of orientation, width, and porosity on the orientation of failure planes. Finally, the presence of pre-existing deformation features triggers additional mechanical damage, affecting the development and direction of new failure planes.

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Abstract: Determination of mineral texture and diagenetic features in mudstones is crucial to reveal the history of their pore systems and provides key information to predict their future sealing ability, reactivity and storage capacity for sequestered CO2, hydrogen storage or nuclear waste disposal. To understand the spatial transport and storage of fluids, it is necessary to map the distribution of minerals and fractures in three dimensions (3D). This study proposes a novel, multi-scale three-dimensional (3D) imaging method, i.e., a combination of synchrotron- sourced micro- x-ray tomography and lab- sourced nano-tomography, to investigate the sedimentology and diagenetic features of the Bowland Shale, one of the most volumetrically important mudstone-dominated systems in the UK. Diagenetic minerals have been identified and characterised, including pyrite, calcite, kaolinite, illite, chlorite, dolomite, ankerite and authigenic quartz (micro-sized quartz and quartz overgrowths). Multi-scale 3D images provide detailed information about dolomite-ankerite zonation and carbonate dissolution pores. These features cannot be observed or quantified by conventional 2D methods, and they have not been reported in this subject area before. Using these results, potential reactions during carbon storage and other subsurface storage applications are predicted.

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Abstract: Methane (CH4) hydrate dissociation and CH4 release are potential geohazards currently investigated using X-ray computed tomography (XCT). Image segmentation is an important data processing step for this type of research. However, it is often time consuming, computing resource-intensive, operator-dependent, and tailored for each XCT dataset due to differences in greyscale contrast. In this paper, an investigation is carried out using U-Nets, a class of Convolutional Neural Network, to segment synchrotron XCT images of CH4-bearing sand during hydrate formation, and extract porosity and CH4 gas saturation. Three U-Net deployments previously untried for this task are assessed: (1) a bespoke 3D hierarchical method, (2) a 2D multi-label, multi-axis method and (3) RootPainter, a 2D U-Net application with interactive corrections. U-Nets are trained using small, targeted hand-annotated datasets to reduce operator time. It was found that the segmentation accuracy of all three methods surpass mainstream watershed and thresholding techniques. Accuracy slightly reduces in low-contrast data, which affects volume fraction measurements, but errors are small compared with gravimetric methods. Moreover, U-Net models trained on low-contrast images can be used to segment higher-contrast datasets, without further training. This demonstrates model portability, which can expedite the segmentation of large datasets over short timespans.