*2.2. Reaction Potential*

The mineralization potential is given by the amount of available cations per given rock volume, but the term reaction potential is more useful for summarizing the geochemical processes. In the case of the Johansen Formation, plagioclase (5–8 wt% in samples [29]) is the most reactive phase in fine- and medium-grained sand fractions, while K-feldspar (9–12 wt% in samples [29]) is more abundant. Fe-rich chlorite (1–9 wt% in samples [29]) is the most reactive clay phase. There is generally more clay in the finer grained, lower shoreface facies (e.g., Figure 4).

The potential for CO2 to be mineralized, i.e., trapped in solid state, depends firstly on the amount of CO2 added to the system and less on the solubility in formation water, considering salinity, pressure, temperature, and thermodynamic constraints. CO2 is transported through the aqueous phase during mineralization [18]. The solution composition applied in simulations (Table 1) was selected based on analogous reservoirs in the North Sea [54]. There is currently no data available on detailed water composition from the Johansen Formation.


**Table 1.** Aqueous solution input for kinetic simulation.

Aqueous trapping capacity; CO2 + HCO3 <sup>−</sup> + CO3 <sup>2</sup>−, is relatively small and in the order of a few percent [55]. Further dissolution of residual CO2 adds to the dissolution potential [56]. Carbonate precipitation reactions consume bicarbonate and cations from solution, lowering the pH as H<sup>+</sup> is produced. Dissolution of silicate minerals consumes protons, and release cations, HCO3 −, aqueous silica and/or secondary clay minerals to solution (e.g., [19]). Carbonate stability is enhanced by increased pH, and the cation supply drives further carbonate precipitation. Dissolution and precipitation are interconnected through these feedback mechanisms [56], and the rate of either will be controlled by the slowest reaction [18]. Carbonate precipitation, most often considered a more rapid reaction compared to silicate dissolution (e.g., [54]), may in some settings provide the rate limiting reaction, such as for low temperature settings [18].

As a first approximation of reactivity and identification of primary reactants, initial geochemical batch simulations including the full mineral assemblage are adequate. For example PHREEQC, TOUGHREACT, and other numerical tools may be applied for batch geochemical modelling in combination with thermodynamic databases such as llnl.dat, phreeqc.dat, or equivalents, including kinetic expressions with nucleation growth rate equations (e.g., [10]).

Based on previous geochemical studies of siliciclastic reservoirs from the North Sea and elsewhere, it may be concluded that a few percent of scattered carbonate equilibrates instantly, that quartz is close to chemically inert, and that reactive accessory minerals present in small amounts (<<1 wt%) are insignificant on reservoir scale. One sedimentary facies may be represented by several samples, which in turn should be averaged with respect to grain size distributions, porosity and mineral content. Subsequently, cases for geochemical simulations, may be defined. If the sediment sorting is poor, it may be relevant to divide the sand fraction in two or more classes. Each mineral is assigned a representative wt% within each class according to petrographic studies of occurrence.

#### *2.3. Reactive Surface Areas*

Estimation of reactive surface area (m2/liter pore water) must relate weight or volume percent of mineral to grain size, shape, porosity, and mineral density. Aged, coated, diagenetically altered and/or weathered grain surfaces are expected to display lower reactivity compared to crushed sample material commonly used in laboratory studies of kinetics.

The mineral content given as wt% from XRD must be translated to the specific surface area by relating mineral density and grain shape (e.g., spheres or circular disks) in geometric formulas. Spherical grains are an appropriate assumption if grain sizes are adjusted according to appearance, e.g., 0.1 μm diameter for the clay fraction if assuming spherical grains, rather than 2 μm diameter if measuring more realistic clay appearances such as flakes (Figure 3b). Porosity is a characteristic of the sedimentary facies and diagenetic imprint, which must be estimated for the associated sample and/or interpolated to the study area. The geometric surface area may be described as:

$$\overline{S}\_{i} = \frac{3\mathbf{x}\_{i}\rho\_{solid}}{\rho\_{i}} \left[\frac{1}{\varphi} - 1\right] \sum\_{j} \frac{\mathbf{x}\_{j}}{r\_{j}} \tag{1}$$

where *Si* is the average specific surface area of mineral *i* for the appropriate facies (m2/L pore water). *x* is the mass fraction of mineral *i*, and ρsolid (g/L) and ρ*<sup>i</sup>* (g/m3) are the average density of the total solid and density of mineral *i* respectively, ϕ*<sup>i</sup>* is porosity, *r* is the mean radius of grains belonging to the discrete size group *j*, and *x* is the fraction of grains belonging to the same discrete grain size

group. As a next step in detailed studies of separate mineral phases, the reactive surface area may be further adjusted according to petrographic observations. The true reactive surface area *St*, differs from *Si*, as only some parts of the surface is reacting at any given time (e.g., [10,17]). Grain roughness may increase *St* by up to several orders of magnitude compared to *Si*, while grain coats and "aged" surfaces have the opposite effect. Diagenetic processes may provide inaccessible (−) or accessible (+) micro-porosity within grains or mud aggregates. Appropriate fractions may be estimated qualitatively and/or quantitatively by elemental analysis and microscopy.

For example, the reactive surface area of plagioclase in lithic fragments may be assigned a lower reactive surface area, *Sr* < *Si*, compared to plagioclase as monocrystalline grains, where *Sr* = *Si*. In the case of etched plagioclase grains with additional internal porosity, *Sr* > *Si*. Using spheres as proxy for geometric grain shapes is sufficient in most cases, as long as the true morphology is considered. Needle-like crystals (e.g., illite) may for example be represented as a series of small spheres, and must be accounted for by reducing grain size. Clay minerals with flaky occurrence (e.g., chlorite in Figure 3b) are most reactive at the edges, and thus, *Sr* << *Si*, as shown in Figure 5a. Assuming spherical grain shapes is therefore not necessarily a drastic simplification. For shales, where the connected porosity is low, reactive surface areas have to be estimated from a geometric model of the pore space rather than the solid phase [17].

**Figure 5.** Parameterization of reactive surface areas: (**a**) Examples of grain geometries in relation to specific and reactive surface areas. For platy clay minerals *Sr* << *Si*, as reactions only occur along the edges; (**b**) Grain size distribution curves for typical lower (finer) and upper (coarser) shoreface facies. The small amounts of clay in reservoir sandstone and small amounts of available sample material makes separate clay analysis for detailed speciation difficult. Note that if disaggregating samples to analyse the clay fraction separately in XRD, a large part of the reactive phase may sort as sand (e.g., chamosite grain coats and ooids). Bulk XRD for the same samples show 6–9 wt% chlorite; (**c**) Reactivity quantification may be performed on bulk XRD data if typical mineral occurrences are described (vol %), and reactive surface area assigned. Example from the Johansen Formation: plagioclase, K-feldspar, chamosite, sorted from right to left according to reactivity in sand and clay fractions, respectively. Occurrence affecting reactive surface area is related both to sedimentary facies and diagenetic alterations (e.g., altered perthites).

3D imagery of crystal habits in SEM is useful in quantification of reactive surfaces (Figure 3b). By use of 2D element-mapping of thin sections, mineral distributions may be efficiently estimated. These methods are of particular importance when variations in solid-solution chemistries relate to different reaction potentials; e.g., for feldspars, chlorites, smectites, carbonates, sometimes by orders of magnitude (e.g., [46]). Micro-porosity and fluid access is challenging to quantify, and total porosity is likely to be underestimated by microscopy methods. The total surface within connected pores may be measured in 3D by use of micro-tomography or Hg intrusion. In combination, these methods may be applied to estimate reactive surface areas, as described in [23]. However, available sample material or budget is often limiting 3D characterization.
