Influence of Caprock Morphology on Solubility Trapping during CO<sub>2</sub> Geological Sequestration

Punnam, Pradeep Reddy; Krishnamurthy, Balaji; Surasani, Vikranth Kumar

doi:https://doi.org/10.1155/2022/8016575

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Abstract Introduction Results and Discussion Conclusions Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2022 | Article ID 8016575 | https://doi.org/10.1155/2022/8016575

Influence of Caprock Morphology on Solubility Trapping during CO₂ Geological Sequestration

Pradeep Reddy Punnam,¹Balaji Krishnamurthy,¹and Vikranth Kumar Surasani¹

Academic Editor: Ondra Sracek

Received24 Aug 2021

Revised27 May 2022

Accepted30 May 2022

Published25 Jun 2022

Abstract

Carbon capture and sequestration (CCS) technology is one of the indispensable alternatives to reduce carbon dioxide (CO₂) emissions. In this technology, carbon capture and transport grid will send CO₂ to the storage facilities that are using various storage techniques. Geologic carbon sequestration (GCS) is one such storage technique where CO₂ is injected into a deep geological subsurface formation. The injected CO₂ is permanently stored in the formation due to structural, residual, solubility, and mineral trapping phenomena. Among different trapping mechanisms, solubility trapping plays a significant role in the safe operation of GCS. In this work, the study is conducted to elucidate the influence of top surface caprock morphology on the solubility trapping mechanism. The simulation results show that the naturally available heterogeneous formations with anticline and without anticline structure influence the solubility fingering phenomena and solubility entrapment percentage over a geological time scale. The lateral migration and sweeping efficiency results of both the synthetic domains for the injected CO₂ have shown the importance of caprock morphology on solubility trapping and selection of injection rate. Quantification of solubility trapping in two morphological structures revealed that the synthetic domain without anticline morphology had shown higher solubility trapping. In the future, the simulation data using Artificial Neural Networks can be applied to predict the structural and solubility trapping of geological formations. This analysis further helps incorporating the interaction of CO₂ with porous media leading to a mineral trapping mechanism.

1. Introduction

Carbon capture, utilization, and sequestration (CCUS) technology is an emerging field to mitigate the CO₂ emissions into the earth’s atmosphere. Precombustion, oxy-fuel combustion, postcombustion, and chemical loop combustion are four widely used carbon capture technologies [1, 2]. Post capture, in carbon utilization technologies, CO₂ is chemically transformed into other value-added products, mostly fuels like hydrogen, methanol, and synthetic natural gas [2, 3]. However, the carbon utilization technologies are in an emerging stage that needs new novel catalyst developments and scale-up procedures to meet the current emission rate. Alternatively, in carbon sequestration technology, CO₂ can be stored in deep sea beds and geological formations and used in Enhanced-Oil-Recovery (EOR), methane recovery from coal seams, etc. [2]. Among carbon sequestration technologies, the geologic CO₂ sequestration (GCS) is the most viable option to permanently dispose CO₂ in deep geological formations [4, 5]. Upon implementation of carbon capture and sequestration (CCS) technology, it can effectively decrease the social cost of carbon value. Despite having the potential to be a mainstream technology for reducing CO₂ emissions, the CCS also has barriers and hurdles in implementation in most countries. The transportation and setup cost of the injection grid is financially expensive [6]. During postinjection period, a dedicated monitoring and disaster unit has to be established to monitor the migration and control the leakage of CO₂ from the subsurface [6]. The acceptance rate from the public communities for the technology is slim because of the unawareness and low confidence in the technology [6, 7].

The in situ thermodynamic conditions of geological formations, such as temperatures greater than 31.1°C and pressures greater than 7.39 MPa, must keep the injected CO₂ in the supercritical state [8, 9]. Such supercritical conditions preferably exist in the geological subsurface where CO₂ is highly dense and occupies less volume than the gaseous state. When CO₂ is injected below caprock, it moves upwards in the subsurface and is obstructed at the caprock stratum [10]. The CO₂ that spreads along the caprock and becomes immobile under the caprock is classified as structural trapping. After the injection, the CO₂ trapped in porous structures leaves residuals during its movement. This part of injected CO₂ co-exists with water, classified as the residual trapping mechanism [11–13]. During upward migration of injected CO₂ from the injection point, some quantity of CO₂ will get trapped in the migration pathway due to the higher entry capillary pressure of the pore. The high entry capillary pressure will act as the barrier to injected CO₂. This trapped CO₂ can be classified as local capillary trapping [14–16]. The CO₂ trapped in the migration pathway and under caprock will dissolve in water to form weak carbonic acids. This phenomenon is classified as solubility trapping [17]. The dissolved CO₂ chemically interacts with minerals present in the formation layer and undergoes mineral reactions to form secondary carbonate minerals. This geochemical transformation of CO₂ is called mineral trapping [18, 19]. Among all the trapping mechanisms, solubility trapping plays a significant intermediate role in permanently disposing CO₂ over geological time. Therefore, this study focuses on how the heterogeneity of the geological domain will determine the fate of CO₂ in the form of solubility trapping efficiency [18, 20].

In the geologic CO₂ sequestration process, the solubility trapping mechanism is critical to the safe eradication of injected CO₂. Figure 1 represents CO₂ migration phenomena leading to solubility trapping in geological formations with and without anticline dome (see Figures 1(a) and 1(b)). During injection, CO₂ forms a stable plume due to injection pressure and moves upward to spread laterally under impermeable caprock. A thin interface layer starts forming slowly between this CO₂ plume and reservoir water due to the dissolution of CO₂ into the water. Once this interface layer becomes thick enough, the fluid channelling takes place. These channelling effects generally form due to the density differences between CO₂ dissolved water and reservoir water, which ultimately leads to the diffusive convection in the pore space of the domain [20, 21]. Furthermore, this leads to the generation of a geological anastomosing pattern called the solubility fingering phenomenon. In this process, the dissolved CO₂ fluid moves downwards due to gravitational forces acting on the higher density fluid, resulting in CO₂ plume contact with freshwater, ultimately resulting in more dissolution of CO₂ in the subsurface domain. This convective movement continues to enhance solubility trapping of the formation domain. The dissolved CO₂ easily interacts with the surrounding rock (CO₂-water-rock interactions) formation, triggering geochemical reactions resulting in CO₂ trapping in the subsurface through a mineral trapping mechanism. In mineral trapping, the formation rock interacts with neighbouring CO₂ and reservoir water and undergoes various geochemical reactions [20, 21]. The percentage of solubility trapping influences the efficiency of the mineral trapping, which decides the fate of carbon sequestration technology. In this way, solubility trapping phenomena play a significant role in the enhancement of CO₂ geological storage.

A review on geological CO₂ sequestration by Kumar et al. [22] highlighted the existing gaps in the present research regarding trapping mechanisms and site characterization. Over the past decade, the research on structural trapping has mainly focused on elucidating storage capacity and integrity [22–24]. In residual trapping research, studies on pore size, heterogeneity, injection strategies, and resident brine density have been conducted predominantly to analyze and increase the residual trapping efficiency [16, 22, 25]. In recent times, research on solubility trapping has been carried out to study the influences of parameters like brine salinity, pH, microbial activity, and reservoir conditions on the solubility trapping efficiency. Abba et al. [26] conducted experiments on the solubility trapping mechanism to examine its influences on the salinity in the gas reservoir. In the gas reservoir, even at higher salinity of 10% weight percentage of NaCl, the trapped efficiency of solubility trapping was observed 63% [26]. In Kumar et al.’s [27] simulation analysis carried out in carbonate formation, an increase in salinity has no impact on the pH variation and has a meagre influence on mineral trapping [27]. In a study conducted by Zhao et al. [28], the microbial-mediated process improved solubility trapping. The author observed that the CO₂ dissolution and solubility trapping increased by increasing the microbe activity [28]. In Shen et al.’s [29] simulation analysis, the microbial activity has shown positive results. During the injection period, the microbes promote mineral dissolution, and during the postinjection period, it favours mineral precipitation, which has increased overall trapping efficiency [29].

During the CO₂ injection and migration period, various geological and sequestration parameters influence the efficiency of trapping mechanisms. Major parameters are petrophysical heterogeneity, well injection configuration, wettability, salinity, top subsurface perturbation, etc. In the research conducted by Al-Khdheeawi et al. [30–33], the influence of wettability was studied in the heterogeneous (variation in petrophysical properties) domain. This numerical study observed that in the strongly CO₂ wet domain, the vertical migration of injected CO₂ was rapid compared to the strongly water wet. But, the lateral spreading was lower in the strongly CO₂ wet compared to the strongly water wet. Due to this, the residual CO₂ entrapment was lower; and the solubility trapping and free mobile CO₂ quantity were higher in the strong CO₂ wetted domain than in all other considered domains. The author recommends that the strongly water wet domain is preferable for implementing geological CO₂ sequestration (GCS) because a more significant time is consumed by CO₂ plume to reach the caprock in a strongly water wet domain that can increase overall trapping efficiency [30–33].

In the naturally available subsurface reservoir, the wettability can vary from strongly water wet to strongly CO₂ wet within the domain space. But the magnitude of these influences might be unpredictable because wettability mostly depends on the rock surface chemistry, connate reservoir water composition, and reservoir temperature [30–34]. Wettability, influences of microbial, salinity, pore network analysis, and other mesoscopic analysis, is very computationally intense [21]; therefore, these analyses were excluded in the current study. Al-Khdheeawi et al. [35–37] have also conducted simulation analysis on the injection well configuration analysis [35] and salinity [36, 37]. It is observed that during horizontal well injection, the lateral spreading of the CO₂ leads to an increase in the contact area between injected CO₂–reservoir water. Due to this reason, the residual and solubility entrapment in the domain was increased [35]. It was also determined that the salinity of reservoir water influences the mobility and vertical migration distances of the CO₂ plume. It is observed that lower salinity is desirable for geological CO₂ sequestration [36, 37].

In Khudaida et al. [38], the numerical simulation was conducted to study the influence of heterogeneity on the CO₂ geological sequestration. A significant share of the injected CO₂ is registered under solubility trapping in the homogenous domain. The CO₂ plume flow is fluent in spreading laterally, increasing the contact area with reservoir water, further increasing the solubility trapping. In contrast to the homogenous domain, in the heterogeneous domain, the residual trapping percentage increases due to the restriction on the flow of CO₂ plume in the migration pathway [38]. Lee et al.’s [39] research described the influence of anticline structure on the selection of injection rate for the CO₂ sequestration. With a higher injection rate, the CO₂ plume is directed towards the anticline structure; during this process, some CO₂ gets immobilized in the migration pathway towards the anticline at a lower injection rate [12]. The flow dynamics of CO₂ plume in the migration pathway and contact area of CO₂ plume with water are highly dependent on the domain heterogeneity, which further influences the residual and solubility trapping percentage [39]. A similar conclusion was made by Raza et al. [40], where the aquifer heterogeneity directs the selection of injection rate [40]. The degree of suitable heterogeneity for implementing safe CO₂ sequestration was studied with the help of the petroleum Lorenz coefficient in Rasheed et al. [41].

The previous study on the influences of geological folds has shown their impacts on the primary trapping mechanisms and sweeping efficiency of CO₂ plume for different ranges of perturbed subsurface morphology [42]. The existence of geological structures like anticline and syncline can certainly control the CO₂ migration, lateral spreading, and safe storage of CO₂ in the domain [12]. Figure 1 gives a glimpse and schematic explanation of the simulation analysis carried out in the current research study. In this study, the influence on the CO₂ sweeping efficiency and lateral migration by the presence of geological features like anticline dome is analyzed. The impacts on lateral migration and sweeping efficiency directly influence the solubility trapping; it was clearly illustrated and explained in Sec. 4 and in Figures 1(a) and 1(b). As explained earlier, once the injected CO₂ plume reaches the caprock, it will start to migrate in the lateral direction. During lateral migration, the CO₂ plume might get trapped in any geological features like anticline and stagnate under it, as illustrated in Figure 1(a). In the absence of geological features, a significant quantity of CO₂ plume might migrate in the lateral direction and increase sweeping efficiency. A considerable amount of CO₂ might move away from the observable or monitoring region at a higher injection rate, as illustrated in Figure 1(b), while in lateral spreading, the movement of the CO₂ plume will get reduced, and the interaction between water and CO₂ will lead to solubility fingering. The solubility fingering phenomena give glimpses of solubility trapping and vertical separating of CO₂. Studying the occurrences of solubility fingering for different caprock domains, mainly under the presence of geological features, and its influences on the solubility trapping is one of the key aspects of novelty for the current research study. The illustration of CO₂ plume migration for two caprock morphologies with their respective influences on solubility trapping analysis is the crucial outcome of the research. This study also presented the significance of selecting an injection point near the high elevation region like the anticline dome. However, as the geology of porous media is neglected, i.e., no dissolved CO₂ and mineral interactions, this work is limited to structural and solubility trapping mechanisms. The geological faults, folds, and subsurface structures can influence the CO₂ migration and CCS integrity. The presence of faults in the domain might lead to CO₂ leakage and be prone to disrupt the structural integrity of the subsurface domain [43–45]. The research has to be carried out on the geological structures with faults, and different folds, which are still nascent with regard to primary (structural and residual) and secondary (solubility) trapping mechanisms. Therefore, this study is also limited to establishing the fundamental transport mechanism during CO₂ sequestration, which is useful for establishing the mineral interactions and ANN studies on physical trapping phenomena.

In this study, the CO₂ migration, lateral spreading, and solubility trapping for both synthetic domains (without and with anticline dome) are analyzed by observing the CO₂ mole fraction, total CO₂ aqueous presence, and pH distribution in the domain. Additionally, average reservoir pressure and the average temperature are also analyzed to study the impacts of CO₂ injection in the domain over a geological time scale. The heterogeneity term is used to describe the irregularities in petrophysical properties and the subsurface geological structure forming on caprock morphology, such as anticline and syncline formations.

In Sec. 2 of this research article, the methodology used in the simulation analysis is explained. Then, the modelling of synthetic subsurface domains with and without anticline domain is illustrated, and other simulation setups are described in Sec. 3. Sec. 4 illustrates and explains the parametric simulation outcomes focusing mainly on caprock morphology. Finally, in Sec.5, summary of the conclusions is presented based on the current research study.

2. Mathematical Modelling

Multiphase flow and reactive transport modelling (RTM) is used to perform this numerical analysis. RTM has the ability to predict the spatial and temporal evolutions of geochemical species during CO₂ geological sequestration [46]. The RTM code utilizes the multiphase, multicomponent mass, momentum, and energy balance equations which are incorporated with geochemistry to understand the interaction between the CO₂ plume and water [47, 48].

2.1. Multiphase Flow Equations

Geological sequestration of CO₂ occurs in a subsurface porous structure that involves several processes, including flow and transport of CO₂. In this section, multiphase flow equations are explained. And it is assumed that the immiscible displacements of CO₂ and water are occurring in a complex porous geological formation. Each phase can involve more than one chemical species and can be considered a mass transfer occurring between phases to accommodate the dissolution of CO₂ in water [48, 49]. The general mass and energy conservation equations governing the multiphase flow are illustrated in Table 1 Eq. (1)–(3). The subscript , denotes phases in the conservation equations, where is for gas and is for liquid. The first term in the equation affiliates to an accumulation in the control volume , and the second term affiliates to the net flux into the control volume. The third term refers to the source/sink term (, _, and ) [47, 48].

From Table 1 Eqs. (1)-(3), the term represents the porosity of the domain, and stand for Darcy velocity of phase and , and _or stands for phase saturation in a domain. _or represents phase diffusivity coefficient, represents the enthalpy, represents the internal energy, and represents the rock density.

2.2. Reactive Transport Modelling

The multicomponent reactive transport equation [46] is illustrated in Table 1 Eq. (4). The total concentration of the components is calculated with the equation mentioned in Table 1 Eq. (5). The subscript represents the phase or . The total flux is calculated with the equation mentioned in Table 1 Eq. (6). The Darcy velocity is already substituted in the total flux equation. The term stands for saturated permeability of the porous media, is the relative permeability of phase is the viscosity of phase, is the pressure of phase, , g is the acceleration due to gravity, and is the vertical coordinate, represents the molar density, represents the formula weight [47, 48]. The reactive transport modelling technique is used to perform the numerical analysis; it can predict the geochemical reactions in both spatial and temporal directions along with the fluid flow [46]. The reactive transport code utilizes the multiphase, multicomponent mass, and energy balance equations incorporated with reaction chemistry to understand the interaction between the CO₂ plume and nearby reservoir water [47, 48].

2.3. Brooks–Corey Relation

In Table 1, Eq. (7) illustrates the saturation relation for all phases. The Brooks–Corey relation is used to relate the capillary pressure to effective invading fluid saturation . In this current simulation study, CO₂ is the invading fluid in the reservoir. The Brooks–Corey relation is illustrated in Table 1 Eq. (9). The term in the Brooks–Corey relationship represents the entry pressure; denotes the capillary pressure. The formulation of reservoir capillary pressure is illustrated in Table 1 Eq. (10). The terms and represented densities of water and injected CO₂; is the effective CO₂ saturation. The term is the parameter related to the pore-size distribution, its value is considered 2.5, and its range is between 0.2 and 5 [49]. Brooks–Corey-Mualem model gives the relationship equation between relative permeability and effective saturation (illustrated in Table 1 Eq. (8)). The terms , , and in the Brooks–Corey-Mualem equation are constants. The value of is 1, is , and is 2, which are obtained by the experimental fitting. The term is effective water saturation. The effective saturation fluid should be considered normal saturation of fluid in this simulation analysis because it is considered that there are no presences of isolation pore space [49]. The fluid movement is primarily defined by the action of buoyancy and capillary forces, which will govern the movement of injected CO₂ in the geological structure domain [49].

3. Simulation Setup

3.1. Synthetic Domain

Two geological domains are modelled to conduct the numerical analysis to elucidate the influence of caprock morphology on the solubility trapping mechanism. A MATLAB software’s default membrane function and trigonometric function are used to model the synthetic domains. By combining the membrane and trigonometric functions, auxiliary equations are developed. Utilizing the meshgrid MATLAB function, two-dimensional grid coordinates are developed with two vector variables. These vectors are further substituted in the auxiliary equations to form top surface layers for two models. The membrane function is used to model the geological anticline structure. And the trigonometric function is used to model the perturbation and irregularity, which will demonstrate as geological ridges. After creating two-dimensional top surface layers, the grid cells are assigned in the third direction to construct three-dimensional grid structures. The membrane function is suppressed for the second synthetic domain to model the domain without anticline structure. Figure 2 illustrates the modelled three-dimensional domains and petrophysical properties distributions considered for the simulations. The physical dimensions of the synthetic domains are about 10 km ×10 km ×0.15 km, and it is discretized into 50 × 50 ×10 grid cells (25,000 grid cells). For the petrophysical properties distribution, the porosity ranges from 20 to 40%, and the value for permeability varies from 10 to 1500 mD [50, 51]. The distribution of porosity and permeability for both synthetic domains is illustrated in Figure 2 [49]. The two synthetic geological domains considered in this simulation analysis have one disguised feature: one domain contains a caprock anticline structure, and another does not include any structure. These synthetic domains contain the same number of perturbations and similar petrophysical property distribution of porosity and permeability. This analysis will be helpful in forecasting injected CO₂ storage and entrapment potential of the domains through structural and solubility trapping. The injection point coordinate considered in these simulations is (4000, 4000, 950), which is also illustrated in dark red colour with the alphabet word I in Figure 2.

3.2. Reactive Transport Mechanism

The multiphase flow forms a liquid-gas interface where ScCO₂ is in contact with water. Due to the chemical potential gradient of CO₂, to maintain local thermodynamic equilibrium at the interface, CO₂ will solubilize in water to form CO₂(aq). Aqueous CO₂ interactions with H⁺ and OH^- ions lead to a series of equilibrium reactions, as listed in Table 2 [20, 52–54]. In the current numerical study, only the solubility reactions are considered to estimate the potential of solubility trapping alone. The initial concentration of CO₂ and H₂O for the whole domain before starting the injection of the ScCO₂ is 4.6 ×10^-12 M and 55.508 M, respectively. In addition, the initial pH of the entire domain is maintained at 5.6.

The injection of CO₂ at point I is facilitated in Eq. (2) with the source term . During injection and postinjection, solution of multiphase flow and energy balance Eqs. (1)-(3) gives the phase distributions of water and CO₂. Darcy’s velocities of individual phases are given by Eqs. (1a) and (2a). Eqs. (7) to (10) give the axillary/closure equations, which include Brooks–Corey’s relationships between saturation, capillary pressures, and relative permeability. The local equilibrium between ScCO₂-water interfaces gives aqueous CO₂ by Henry’s relations. The fate of CO₂ and H⁺ in the water phase due to convection and diffusion, i.e., the total concentration of CO₂() and H⁺(), is solved using reactive transport model Eq. (4).

3.3. Estimation of Structural Residual and Solubility Trapping Percentage

The structural and residual trapping is estimated based on the cells’ porosity, pore volume, and CO₂ saturation. The structural and residual trapping is calculated using the equation illustrated in Table 1 Eq. (11)-(12). The movable plume is the remaining quantity of CO₂ after the structural and residual trapping. The term in Table 1 Eq. (11)-(12) is the total number of cells in the grid structure. The term represents porosity. and are the cell volumes of structural traps and residual traps, respectively. The structural traps are identified by analyzing the top surface. The top surface is modelled by using the meshgrid. Then, the MATLAB Gaussian noise function is used to integrate the perturbation into the mesh surface. Now the numerical distance differences between each cell of the mesh surface are identified. The structural traps are then identified, and the consecutive cells are saved under structural trapping cells and analyzed during simulations. The remaining cells other than the structural trapping cells of a domain are the active cells for residual trapping calculation. Only the immobile CO₂ saturation cells are considered for the entrapment calculation. The remaining cell saturations are considered for the movable-plume calculations. The and are the saturation of CO₂ and residual CO₂ saturation. The CO₂ entrapment percentage of solubility is analyzed by observing the CO₂ present in the aqueous and gaseous forms in the geological simulation domain.

This study used a massively parallel reactive transport code PFLOTRAN for this simulation analysis. The detailed mathematical implementation of PFLOTRAN is discussed in Mills et al. [48]. The parallelization is achieved through domain decomposition using the PETSc (Portable Extensible Toolkit for Scientific Computation) libraries. PETSc is a data structure and routine suit for the scalable solution of scientific applications [55]. The Newton–Krylov iterative solver is used in this simulation analysis. The PFLOTRAN has the ability to solve coupled thermal-hydrologic-chemical three-dimension problems in variably saturated, nonisothermal porous media. [55].

4. Results and Discussion

The CO₂ mole fraction and pH variations are two significant factors that enable the visualization of CO₂ entrapment in the formation zone. Here, CO₂ mole fraction values for the whole domain provided an overall picture of CO₂ migration. Simultaneously, the domain’s pH variation helped visualize the solubility fingering phenomena and solubility trapping occurrence within the domain. Additionally, the average reservoir pressure, average reservoir temperature, and CO₂ trapped in the different phases have given an adequate understanding on the influence of caprock morphology. This simulation analysis is carried out to analyze and visualize the effects of caprock morphology on the quantity of CO₂ that undergoes the solubility trapping mechanism in the domain. The CO₂ injection is carried out continuously for the first 30 years at the mass flow rate of 0.315 Mt/year. The density and viscosity of water considered in the simulations are 975.86 kg/m³ and 0.3086 ×10^-3 Pa.s, and that of CO₂ are 686.54 kg/m³ and 0.0566 ×10^-3 Pa.s, respectively [49]. The initial temperature of the reservoir is maintained at 75°C. The reservoir depth starts from 800 m, as illustrated in Figure 2, which indicates that the sequestration of CO₂ in the simulation domain is carried out 800 m below the earth’s surface. The synthetic domain considered in this research analysis is a sloping landscape. So, the depth value “” for each grid cell changes. The initial reservoir pressure in the reservoir is calculated by . As the density of water () considered in the geological domain is constant, the pressure depends only on the depth (). The initial reservoir pressure varies from 77 to 84.6 bars in the geological domain. The rock formation’s tortuosity values are assumed to be 1, and the rock density is considered 2900 kg/m³ [56]. For the solubility trapping simulation analysis, the initial pH of the domain is maintained at 5.6. The porosity and permeability distribution of the domain is illustrated in Figure 2.

4.1. Base Case Scenario

A synthetic anticline domain (Figure 2) is considered a base case scenario to understand solubility trapping phenomena. The petrophysical properties, injection rate, and fluid properties are considered as mentioned in Sec. 3 for this simulation analysis. Two sets of simulation analyses were carried out with and without considering the CO₂ dissolution. The simulation set without CO₂ dissolution mechanism consideration will calculate only structural and residual trapping; this simulation set will be referred to as simulation 1 in subsequent text, whereas in the simulation setup where the dissolution reactions are considered, the solubility trapping is calculated in addition to structural and residual trapping; this will be referred to as simulation 2. These simulations are carried out at the same injection point at the constant injection rate. The CO₂ saturation profiles on the top surface of the anticline domain are illustrated in Figure 3(a).

(a)

(b)

(c)

Figure 3

(a) Saturation of CO₂ in anticline dome representing the migration at discrete times 1, 30, and 3000 years. Simulation 1, structural, and residual trapping only represent ScCO₂ migration without CO₂ solubility. Simulation 2 for solubility trapping clearly shows lower CO₂ saturation describes the injected CO₂ in the aqueous phase. The dynamic profile of the amount of CO₂ in various forms of trapping mechanisms, (b) during structural and residual trapping (without CO₂ dissolution) and (c) solubility trapping (with CO₂ dissolution).

In simulation 1, due to the absence of CO₂ in the aqueous phase, the injected CO₂ percolates and undergoes structural and residual trapping [7]. From Figure 3(a), it is noticed that in simulations 1 and 2, the CO₂ plume is migrating towards the top surface of the anticline domain. Once the injected CO₂ plume completely reaches the anticline dome, it gets stagnates in the anticline dome. This restricts the CO₂ plume from migrating in the lateral direction. This restriction of CO₂ plume in the domain will limit the residual trapping. In simulation 1, the saturation of CO₂ on the top surface of the domain is more compared to simulation 2. This implies that the CO₂ migration in simulation 2 is less because ScCO₂ dissolves into the resident reservoir water and undergoes solubility trapping. To understand more on CO₂ migration in the formation domain, the mass of CO₂ in various forms is quantified in Figures 3(b) and 3(c). For the initial 30 years of injection, 9.7 Mega tonnes of CO₂ was injected into the formation. Figure 3(b) illustrates the dynamic variation of the mass of CO₂ in the form of structural and residual trapping and free mobile CO₂, where the dissolution mechanism is not considered (simulation 1). Figure 3(c) illustrates the efficiency of solubility trapping by quantifying the mass of CO₂ in both aqueous and gas phases. In Figure 3(c), CO₂ aqueous represents the dissolved mass of CO₂ in water, and the CO₂ gas represents the free mobile, structural and residual trapped CO₂ over a geological time scale. It can be observed that the structural and residual trapping was dominant during the injection period (30 years) (see Figure 3). However, during the migration, the solubility of CO₂ in water is prevalent from Figure 3(c). During the postinjection period, the CO₂ plume stagnates under the anticline dome, and the constant dissolution of CO₂ into resident water will take place. And about 90% of injected CO₂ is dissolved in water at 3000 years (see Figure 3(c)).

4.2. Solubility Fingering Phenomena

After injecting the ScCO₂ into the domain, it will form a CO₂ plume, start migrating upwards, and spread laterally under impermeable caprock. After the injection is ceased, the velocity of the CO₂ plume will decrease gradually over time, which increases the contact time between the CO₂ plume and the connate reservoir water. The obtained results of plume migration in the domain are illustrated in Figure 4. The interface layer will be formed between the CO₂ plume and connate reservoir water. At the interface, the CO₂ dissolves into connate reservoir water. Molecular diffusion and mass transfer occur from CO₂ plume to resident reservoir water. As the CO₂ dissolved into the water, it became denser and led to convection mixing in the downward direction [18, 57].

The fingering phenomenon occurs during the solubility trapping mechanism due to the dissolution-diffusion-convection process. The solubility fingers form in the domain help increase the efficiency of solubility trapping. Due to this fingering phenomenon, more CO₂ will come in contact with the fresh formation water. The illustrative results of the fingering phenomenon can be seen in Figure 4. The CO₂ concentration is higher near the injection well during the injection period, and the dominance of dissolution is not seen in the domain (see Figure 4 for 30 years). During postinjection, the plume spreading over a geological time scale creates more CO₂-water interface to facilitate the CO₂ dissolution phenomena. It is observed that the fingering phenomena gradually shift beneath the anticline dome where the maximum amount of CO₂ plume has migrated. The number of fingers increases with geological time scale (see Figure 4 for 200 and 3000 years). This phenomenon of solubility trapping effect is evident in Figure 4 for comparison of CO₂ saturation in residual trapping-only trapping and residual-and-solubility trapping.

The simulation results in Figure 5 depict the fate of CO₂ at discrete geological times in the form of a CO₂ mole fraction across the domain. After reaching the caprock, the plume laterally spreads under the impermeable caprock. During this time, one can notice a constant decrease in the CO₂ mole fraction. This can be attributed to residual and solubility trapping, which works in tandem to increase the entrapment of the injected CO₂. The plume reaches the caprock within one year, and at the end of the injection period, it slowly starts to migrate towards the anticline dome. It assumed that the upper layer of the domain is impermeable. Therefore, it will restrict the CO₂ from passing through it and allow it to migrate towards the anticline. During this migration, due to the absence of injection force and the presence of perturbation on caprock, the momentum of the CO₂ plume decreases, which increases the contact time between CO₂ and water, which further leads to an increase in the percentage of entrapment in the domain. A steady reduction in CO₂ mole fraction and increase in total aqueous phase CO₂ quantity after the injection phase suggest that the entrapment of CO₂ occurs through the solubility trapping mechanism.

The CO₂ mole fraction and pH variation results are presented in Figure 5. Initially, a pH of 5.6 is attributed to the whole domain. As the CO₂ moves upwards and percolates through the formation layer, the CO₂ starts getting dissolved into connate reservoir water, which further leads to a decrease in pH value in the domain. From the results, it is observed that the large volume of the synthetic domain can be seen to be covered with a low pH. This happens due to lateral spreading and solubility fingering phenomenon of CO₂ plume in the domain; the results are illustrated in Figure 5. The pH drops to 3.5, suggesting solubility trapping occurrences with safe entrapment of injected CO₂ in the domain. For mineral trapping to occur, certain conditions are required, of which pH is an essential factor. For example, to have a dissolution of silicate minerals, a low pH range is preferred to have a higher concentration of H⁺ ions on the reactant side. For a precipitation reaction to occur, a slightly higher pH is preferred. In order to have reliable sequestration trapping_, it is preferred to have an optimal pH range. The aforementioned pH range of 3.5-5 is considered optimal enough to promote both dissolution reaction and precipitation reaction and thereby enhance the storage of CO₂ in the domain [58].

4.3. Caprock Structure Influence on Solubility Trapping

In this section, the simulation study is carried out to analyze the influence of caprock structure on CO₂ geological sequestration. The first set of simulations is carried on the synthetic domain incorporated with the anticline domain, and it will be referred to as synthetic domain-1 in the subsequent text. In the second set of simulations, a synthetic domain without caprock morphological structure is considered, and it is referred to as synthetic domain-2. Figure 6(a) illustrates the CO₂ mole fraction distribution for both synthetic domains. From Figure 6(a), it is observed that by the end of the simulation time, the CO₂ mole fraction distribution is lesser in synthetic domain-2 as compared to synthetic domain-1. It may be due to high lateral spreading and displacement efficiency in synthetic domain-2. Due to high lateral spreading, a large quantity of CO₂ came in contact with connate water, which triggered a dissolution reaction and further initiated the fingering phenomenon. So, for this reason, the total aqueous phase CO₂ quantity observed was higher, and the free mobile CO₂ quantity was lower in the synthetic domain-2 compared to synthetic domain-1 (see Figure 7(c)).

(a)

(b)

(a)

(b)

(c)

Figures 6(a) and 6(b) give an illustrative explanation about the higher solubility of injected CO₂ in synthetic domain-2 compared to synthetic domain-1. In the pH variation simulation results, see Figure 6(b); it is observed that a large volume of the domain in synthetic domain-2 is covered with low pH compared to synthetic domain-1. The volume covered and displacement efficiency of injected CO₂ plume is less in synthetic domain-1 than in synthetic domain-2. It is due to the migration pathway of CO₂ plume is congested to narrow pathway towards anticline centre. In synthetic domain-2, due to the absence of an anticline dome, the injected CO₂ plume leads to more spreading in the lateral direction, which leads to higher CO₂ dissolution. Furthermore, it contributes to the fingering phenomenon, which increases the dissolution in the depth axis and increases the vertical spreading. In this way, the pH in the domain changes over geological time. The low pH region created during the solubility trapping phase might trigger a mineral reaction for the mineral trapping mechanism as the domain’s pH range is within the acceptable limits [59].

The average reservoir pressure and temperature results of synthetic domain-2 are in the commendable range (see Figures 7(a) and 7(b)). As predicted, in Figure 7(a), the pressure in synthetic domain-1, i.e., with anticline structure, is high at the end of the simulation time compared to synthetic domain-2, i.e., without anticline structure. Due to the narrow pathway and stagnated CO₂ in the dome centre, it will uphold the normal reservoir pressure in synthetic domain-1. It is observed that the average reservoir temperature has not shown any significant variations during simulations. Its effects were recorded over the geological time scale were nominal (see Figure 7(b)). From solubility trapping, as depicted in Figure 7(c), it is observed that the mass of CO₂ dissolved in water at any time is higher in synthetic domain-2 compared to synthetic domain-1. As mentioned earlier, high lateral spreading in the synthetic domain-2 leads to more entrapment in the migration pathway. In synthetic domain-1, due to the presence of an anticline structure, the lateral spreading of the CO₂ plume was restricted and remained low, which ultimately reduced the residual and solubility entrapment. Overall, the free mobile CO₂ quantity is low in synthetic domain-2 compared to synthetic domain-1; from Figure 7(c), it is evident that at 3000 years, most of the injected CO₂ was dissolved in the water phase.

In comparison, 99% of the injected mass is dissolved without anticline structure, whereas it is 90% in the anticline structure case. But at a higher injection rate, synthetic domain-2 has shown a large quantity of CO₂ migrating out of the observable domain. In certain situations, the injected CO₂ must be confined within the limits of the geological domain by which CO₂ can be restricted from exploring the geological cracks and fault structures, which might further lead to leakage [45]. In such a scenario, the presence of geological structures like anticline dome in synthetic domain-1 is a viable option. As illustrated in synthetic domain-1 results, see Figure 6, the anticline dome restricts the CO₂ within the observable domain limits.

The low availability of storage volume and low injection rate can increase the risk factor and financial aspects of the CCS operation in synthetic domain-2. The synthetic domain-1 can be cost-effective (see Figures 6(a) and 6(b)); it can be observed that injected CO₂ is migrating under a small volume of anticline dome, which will reduce the monitoring cost as it will require to screen a small area. But if the anticline dome contains faults, it can create severe problems for the safe operations of CCS.

5. Summary and Conclusions

In carbon capture and sequestration (CCS), CO₂ storage in geological formations is proven to be a viable solution [4]. During geological sequestration, the fate of CO₂ is governed by multiphase flow and geochemical interactions between water, CO₂, and minerals in the form of structural, solubility, and mineral trapping mechanisms. Solubility trapping is a significant phenomenon to facilitate the mineralization of CO₂. The structure of the caprock plays a major role in interaction of CO₂ with water to maximize solubility trapping during geological sequestration. In this work, the reactive transport modelling technique was used to simulate and understand the influence of caprock morphology on the solubility trapping mechanism. The outcome of the work is summarized as (i)The mole fraction of CO₂ and pH distribution across the synthetic domain are two major features to analyze and visualize the influence of caprock morphology on solubility trapping(ii)The variation of the CO₂ mole fraction over a geological time scale helped to visualize the entrapment of CO₂ within the formation zone. At the same time, the change in pH values helped in imagining solubility trapping that took place within the formation in the depth axis(iii)A comparative simulation study between two simulation domains (with and without anticline dome) was conducted to study the influence of caprock morphology. It was noticed that the presence of the anticline dome reduces the solubility trapping efficiency, but increases the range of the injection rate(iv)The influence of the solubility fingering phenomenon in increasing the CO₂ entrapment was observed from CO₂ solubility trapping plots. These factors helped understand that the naturally available domain is better in storing the injected CO₂(v)The average reservoir pressure plots have given a distinguished explanation for two comparative sets of simulation models, which helped analyze the effective storage of injected CO₂ in the formation domain(vi)Future works include the development of a comprehensive reactive transport model by incorporating the geochemistry of minerals, which elucidate the fate of CO₂ in the form of structural, residual, solubility, and mineral trapping mechanisms(vii)The future comprehensive model shall accommodate the heterogeneity effects of formation domains such as mineralogy, wettability conductions, pH, and salinity of connate water

Nomenclature

D:	Phase diffusivity coefficient (m² s⁻¹)
g:	Gravity (m s⁻²)
H:	Enthalpy (kJ mol⁻¹)
h:	Vertical height (m)
I:	Reaction rate (mol lit^-1 s^-1)
k:	Intrinsic permeability (m²)
k_r:	Relative permeability
P:	Pressure (Pa)
Pc:	Capillary pressure (Pa)
Pe:	Entry pressure (Pa)
Q:	Source or sink terms (kmol m⁻³ s⁻¹)
Q_e:	Source or sink term for energy
q:	Darcy flux (m s⁻¹)
S:	Saturation (-)
S_e,l:	Effective liquid saturation (-)
S_e,g:	Effective gas saturation (-)
S_rCO2:	Residual saturation of CO₂ (-)
T:	Temperature (K)
U:	Internal energy (kJ mol^-1)
V_r:	Volume of residual trapping grid cell (m³)
V_s:	Volume of structural trapping grid cell (m³)
W:	Formula weight (kg kmol^-1)
X:	Mole fraction
z:	Vertical coordinate (m).

Greek Letters

α:	Phase of specie
Ø:	Porosity
κ:	Thermal conductivity (W m^-1 K^-1)
ρ:	Density (kg m⁻³)
τ:	Tortuosity
μ:	Viscosity (Pa s)
ν:	Coefficient of reaction rate
η:	Molar density (kmol m⁻³)
ѱ:	Total concentration of species (mol m⁻³)
Ω:	Total flux of species (mol m⁻² s⁻¹).

Subscript/Superscript

α:	Phase of specie
l:	Liquid phase
g:	Gas phase
w:	Water
c:	CO₂
r:	Rock
j:	Primary species
m:	Minerals.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors would like to acknowledge Science and Engineering Research Board (SERB), India, for providing financial support under the Core Research Grant with file no. EMR/2017/02450.

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Copyright © 2022 Pradeep Reddy Punnam et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Geofluids

Influence of Caprock Morphology on Solubility Trapping during CO2 Geological Sequestration

Abstract

1. Introduction

2. Mathematical Modelling

2.1. Multiphase Flow Equations

2.2. Reactive Transport Modelling

2.3. Brooks–Corey Relation

3. Simulation Setup

3.1. Synthetic Domain

3.2. Reactive Transport Mechanism

3.3. Estimation of Structural Residual and Solubility Trapping Percentage

4. Results and Discussion

4.1. Base Case Scenario

4.2. Solubility Fingering Phenomena

4.3. Caprock Structure Influence on Solubility Trapping

5. Summary and Conclusions

Nomenclature

Data Availability

Conflicts of Interest

Acknowledgments

References

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Influence of Caprock Morphology on Solubility Trapping during CO₂ Geological Sequestration