Shale reservoirs offer significant potential for CO₂ geological sequestration due to their extensive nanopore networks and heterogeneous pore systems. This study comparatively assessed the CO₂ storage potential of the Lower Silurian Longmaxi and Lower Cambrian Qiongzhusi shales through an integrated approach involving organic geochemical analysis, mineralogical characterization through X-ray diffraction (XRD), mercury intrusion capillary pressure (MICP), low-pressure nitrogen and carbon dioxide physisorption, field-emission scanning electron microscopy (FE-SEM), stochastic 3D microstructure reconstruction, multifractal analysis, and three-dimensional succolarity computation. The results demonstrate that mineral assemblages and diagenetic history govern pore preservation: Longmaxi shales, with moderate maturity and shallower burial, retain abundant organic-hosted mesopores, whereas overmature and deeply buried Qiongzhusi shales are strongly compacted and mineralized, reducing pore availability. Multifractal spectra and 3D reconstructions reveal that Longmaxi develops broader singularity spectra and higher succolarity values, reflecting more isotropic meso-/macropore connectivity at the SEM scale, while Qiongzhusi exhibits narrower spectra and lower succolarity, indicating micropore-dominated and anisotropic networks. Longmaxi has nanometer-scale throats (D₅₀ ≈ 10–25 nm) with high CO₂ breakthrough pressures (P₁₀ ≈ 0.57 MPa) and ultra-low RGPZ permeability (mean ≈ 1.5 × 10⁻² nD); Qiongzhusi has micrometer-scale throats (D₅₀ ≈ 1–3 μm), very low breakthrough pressures (P₁₀ ≈ 0.018 MPa), and much higher permeability (mean ≈ 4.63 × 10³ nD). Storage partitioning further differs: Longmaxi’s median total capacity is ≈15.6 kg m⁻³ with adsorption ≈ 93%, whereas Qiongzhusi’s median is ≈12.8 kg m⁻³ with adsorption ≈ 70%. We infer Longmaxi favors secure adsorption-dominated retention but suffers from injectivity limits; Qiongzhusi favors injectivity but requires reliable seals.

 Succolarity follows a power-law relationship with permeability, highlighting its effectiveness in predicting flow properties.  The combination of succolarity and the specific Euler number quantifies connectivity, revealing percolation thresholds in porous media.

Characterising the complexity of spatial patterns and their underlying physics using a nonlinear approach is growing in many fields. Many features in geomaterials, such as pore and fracture systems, exhibit scaling behaviour, allowing their properties to be characterised using fractal theory.The widely used fractal dimension is a ratio that compares how the level of detail in a structure varies with its size, measuring its space-filling ability. Lacunarity, derived from the Latin word "lacuna," meaning "gap," quantifies the “voidness” of a texture. Nevertheless, neither fractal dimension nor lacunarity can characterise the percolating properties of a fractal. Mandelbrot coined the concept of succolarity. Given that "percolare" in Latin translates to "to flow through," the term "succolare" (sub-colare) aptly conveys the concept of "to nearly flow through" in neo-Latin. A succolating fractal is characterised by almost containing the connecting paths that permit percolation, i.e., one below the percolation threshold. However, it remains a less known notion than the other two fractal counterparts. In the last ten years, succolarity has evolved from an idea to a computable parameter. It has characterised many patterns in different scales and fields, such as medical objects, material surfaces, and networks from nano-micropores to rivers.In this contribution, we aim (i) to understand the physical meaning of succolarity and how it relates to pore networks and other petrophysical properties across different scales, and (ii) to provide new approaches to succolarity calculation. We implemented the succolarity algorithm using the gliding box-counting method. We then re-examined the published datasets for validation and comparison. The succolarity for 2/3D images of rock samples and synthetic models with various porous structures was also calculated for deeper understanding. Finally, we correlated the succolarity results with porosity, permeability, and other petrophysical parameters.Our findings reveal that (i) succolarity contains information about a structure's anisotropy, phase fraction (e.g., porosity in the case of pore space), and percolation information. (ii) It is susceptible to connectedness. As we cut out smaller pores of a structure, succolarity decreases linearly until a pore size (porosity) threshold is reached; it drops significantly and follows a power law. (iii) Succolarity (Su) and permeability are fitted to an exponential relation: k = aebSu. The computation of succolarity excludes isolated pores for a given flooding direction, allowing it to reflect the flow properties better than porosity alone. (iv) Moreover, it is worth noting that using pressure or velocity field in the succolarity calculation algorithm would endow it with a clearer physical meaning than being a proxy for porosity.

The rapid escalation of global warming, driven by anthropogenic carbon dioxide (CO₂) emissions, underscores the necessity of carbon capture and storage (CCS) technologies as a critical strategy for mitigating atmospheric CO₂ levels. Shale reservoirs, characterized by their extensive nanopore networks and heterogeneous pore structures, hold significant promise for CO₂ sequestration. This study investigates the storage and sequestration potential of shales from two distinct formations: the Lower Silurian Longmaxi Formation (TY1 group) and the Lower Cambrian Niutitang Formation (N206 group). A comprehensive suite of experiments, including XRD analysis, mercury intrusion porosimetry (MIP), low-pressure gas adsorption (N₂ and CO₂), field-emission scanning electron microscopy (FE-SEM), and mineralogical analysis, was employed to characterize pore structure, adsorption behaviour, and mineralogical controls on CO₂ storage. Moreover, a novel fractal parameter, succolarity along with conventional mass and surface fractal dimensions were used to depict the pore systems of the two groups.Results reveal that the TY1 samples exhibit higher total organic carbon (TOC; up to 7.58%), greater microporosity, and stronger CO₂ adsorption energies (up to 34 kJ/mol) compared to the N206 samples, which display a more mesopore-dominated system and lower adsorption energies (28–30 kJ/mol). The Longmaxi Formation demonstrates superior pore connectivity and pore size distribution (PSD) homogeneity, enhancing both CO₂ retention and transport. Its higher carbonate content also suggests potential for mineral trapping through carbonation reactions. In contrast, the Niutitang Formation is characterized by higher total porosity (up to 2.4%) and mesoporous contributions, favouring rapid injection but limiting long-term retention. Meanwhile, the FE-SEM observations revealed that many authogenic minerals such as quartz, pyrite and rutile occupy the pore space in organic matters. It is much more prevalent in the N206 samples, which may be responsible for its lower microporosity.Key findings include a strong correlation between TOC and micropore volume, as well as between clay minerals and mesopore-macropore attributes. These correlations highlight the dual role of organic matter and mineral content in determining gas adsorption capacity and flow dynamics. The TY1 group’s balanced micropore and mesopore contributions make it ideal for long-term CO₂ sequestration, while the N206 group’s larger pore sizes enhance its suitability for rapid injection and enhanced gas recovery (EGR) applications.This study provides critical insights into the interplay of organic matter, mineral composition, and pore structure in controlling CO₂ storage potential in shale reservoirs. The findings emphasize the Longmaxi Formation's superior suitability for CO₂ storage and EGR, with implications for optimizing CCS strategies in similar shale systems globally.

One strategy for reducing global greenhouse gas emissions as the world progresses towards net zero is to extract more hydrocarbons from existing resources. Conventional modelling and simulation of heterogeneous and anisotropic reservoirs consistently and significantly underestimates production, sometimes by as much as 70%.We now understand that many reservoir properties are fractal, such as porosity, grain size and permeability. While water saturation and capillary pressure have distributions which arise from fractally-distributed microstructural properties. Recent work has resulted in the development of the fractal theory of Archie’s laws, providing fractal dimensions underlying both the cementation and saturation exponents that is consistent with the n-phase Archie’s law theory.The significant underestimation of production by conventional reservoir models can be overcome by the use of advanced fractal reservoir models (AFRMs) which take account of the fractal distribution of key petrophysical properties such as porosity, grain size, cementation exponent, permeability, water saturation and capillary pressure. These models employ existing and interpolated data across an extended range of scales and take account of variability less than the 50 m seismic resolution limit. AFRMs provide production profiles that are much closer to actual production profiles.This presentation describes briefly the AFRM approach to the modelling and simulation of heterogeneous and anisotropic reservoirs, showing how AFRMs can be generated easily to match an imposed degree of heterogeneity and anisotropy, or can be conditioned to represent the heterogeneity and anisotropy of the target reservoirs. We describe how AFRMs can be generated and normalised to represent key petrophysical parameters, how AFRM models can be used to calculate permeability, synthetic poroperm cross-plots, water saturation maps and relative permeability curves, and how AFRMs which have been conditioned to represent real reservoirs provide a much better simulated production parameters than the current best technology.Generic AFRM modelling and simulation show that total production, production rate, water cut and the time to water breakthrough all depend strongly on heterogeneity and anisotropy. Counter to expectation, optimal production is obtained from placing both injectors and producers in the most permeable areas of heterogeneous reservoirs. Furthermore, modelling with different degrees and directions of anisotropy shows how hydrocarbon production depends critically on anisotropy direction, which changes over the lifetime of the reservoir.AFRMs are ultimately only useful if they can be conditioned to real reservoirs. We have developed a method of fractal interpolation to match AFRMs to reservoir data across a wide scale range. Results comparing the hydrocarbon production characteristics of such an approach to a conventional krigging approach show a remarkable improvement in the modelling of hydrocarbon production when AFRMs are used; with AFRMs in moderate and high heterogeneity reservoirs returning values always within 5% of the reference case, while the conventional approach often resulted in systematic underestimations of production rate by over 70%.Although more work needs to be done on this new approach to reservoir modelling, initial results indicate that it has the potential for improving the accuracy of modelling and simulation in heterogeneous and anisotropic reservoirs by an order of magnitude or more.