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Carbon isotope (δ13C) variations measured in carbonates have been attributed to large-scale phenomena throughout Earth history, such as changes in atmospheric oxygen or global glaciations. These interpretations follow from a model wherein the δ13C of marine dissolved inorganic carbon (DIC) is controlled by the relative sedimentary burial rates of biogenic carbonate (BC) and organic carbon (OC). A new model proposes authigenic carbonate (AC) as a third major sedimentary C pool, implying that δ13C anomalies are not necessarily indicative of extreme changes in the global carbon cycle and/or atmospheric oxygen. Two conditions are required for AC formation to significantly alter bulk carbonate δ13C: the AC isotopic composition must be at least ∼3‰ different from that of BC and the AC/BC ratio must be >0.1. We use pore fluid Ca and Sr concentrations to estimate rates of AC formation in Late Cenozoic marine sediments, then calculate relative fractions of AC, OC, and BC. Today AC is not expected to constitute a significant fraction of total sedimentary carbon (AC+OC+BC) globally; however, there are modern sites where local conditions promote elevated AC/BC and anaerobic metabolisms can alter the δ13C of pore fluids. We investigate these sites to determine what conditions might enable AC to alter δ13C of marine DIC. We find there is very little net addition of AC relative to BC, but large quantities of AC form today across many settings via recrystallization. In settings where remineralization of organic matter causes recrystallized carbonate to form with modified δ13C, AC/BC is generally too low for this recrystallization to significantly shift the δ13C of the bulk carbonate. However, exceptions are found in sites with very low BC and extensive methane oxidation, suggesting that this environment type would need to be globally extensive in the past in order for AC formation to change the δ13C of marine DIC.

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We present a finite element-finite volume simulation method for modelling fluid flow and solute transport accompanied by chemical reactions in experimentally obtained 3D pore geometries. The advantage of the proposed methodology with respect to other pore-scale modelling approaches is that no simplifications regarding the geometry of the porous space are required and no approximations to the flow equations are introduced. We apply this method in a proof-of-concept study of a digitised Fontainebleau sandstone sample. We use the calculated velocity profile with the finite volume procedure to simulate pore-scale transport and diffusion of the adsorbing solute. We also demonstrate how analysis of the pore geometry can be used to identify the locations of oil during the two-phase flow and couple this with the reactive transport modeling to show how this procedure can be used to estimate the potential of the enhanced oil recovery techniques.

The relationship between porosity and permeability in limestones is a fundamental constitutive equation in subsurface fluid flow modelling, and is essential in quantifying a range of geological processes. For a given porosity, the permeability of limestones varies over a range of up to five orders of magnitude. Permeability of a given rock sample depends on the total amount of pore space, characterized by porosity, as well as how the pore space is distributed within the rock, which can be expressed as a probability density function of pore sizes. We investigate in this study whether the information about pore-size distribution can be sufficiently captured by the bulk petrographical properties extracted from thin sections. We demonstrate that most of the uncertainty can be explained by variations in texture, which is defined by the mud content (mass fraction of particles less than 0.06 mm in diameter). Using mud content as a quantitative texture descriptor, we used multivariable regression and neural network models to predict permeability from porosity. For a given porosity, inclusion of mud content reduces the uncertainty in permeability prediction from five to two orders of magnitude.