University of Groningen

Effects of impurities on subsurface CO2 storage in gas fields in the northeast NetherlandsBolourinejad, Panteha

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99

Chapter 7

An experimental study of dolomite dissolution

kinetics at conditions relevant to carbon

sequestration

Submitted for publication in:

Baritantonaki, A., Bolourinejad, P. and Herber, R. (2015, submitted). An experimental study of dolomite dissolution kinetics at conditions relevant to carbon sequestration. Journal of Chemical Geology

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Chapter 7

An experimental study of dolomite dissolution kinetics at 7conditions relevant to carbon sequestration

Abstract

Dolomite is one of the abundant minerals in Rotliegend sandstones in gas fields in North East Netherlands. When depleted, these fields are potential candidates for CO2 sequestration. It is therefore important to assess the characteristics of dolomite dissolution in view of reservoir integrity during storage. In this study the kinetics of dolomite dissolution have been experimentally investigated under subsurface conditions at 100oC in brine with total dissolved solid (TDS) of approximately 300 g/l and in an acidic regime. Experiments were performed in closed, stirred, batch reactors at far from equilibrium conditions, with dolomite powders of different grain size with diameter of: 20-25 microns, 75-100 microns and 300-350 microns and respective geometric surface areas of: 935 cm2/g, 225 cm2/g and 65 cm2/g. Furthermore the experiments were repeated for all grain sizes at 25oC in order to derive the activation energy values of the reactions. For reference the experiments were also conducted in deionized water in order to determine the effect of brine composition. Partial CO2 pressure was kept at 0.1 MPa as it was found that CO2 pressure only indirectly affects the dissolution through changes in pH. The rates were deduced from the measurement of the amount of Mg2+ and Ca2+ released from the dolomite powder. The rates were normalized by the surface area of the minerals at each time interval which was derived by the using Scanning Electron Microscopy (SEM) imaging. In both deionized water and brine, linear dependencies of elemental concentrations (Mg or Ca) and pH were obtained, which resulted in the kinetic rate constants of: k1=-8.16 at 25 oC and k2=-7.61at 100 oC (300-350 microns), k3=-7.87 at 25 oC and k4=-7.45 at 100 oC (75-100 microns), and k5=-6.62 at 25 oC and k6=-5.96 at 100 oC (20-25 microns). The results obtained in this study indicate that in an acidic regime the dissolution of dolomite in brine is a factor of 2 faster than in deionized water. It was also shown that the dissolution rates, when normalized by surface area, are increasing with decreasing grain size. Keywords

CO2 storage; dolomite; dissolution; kinetics; Rotliegend reservoir

7.1 Introduction

Since the industrial revolution, the atmospheric concentration of greenhouse gases (GHG) has reached record levels leading to climate change. Amongst these greenhouse gases, carbon dioxide (CO2) has been recognized as an important contributor to global warming (IPCC, 2007). Under the 1997 Kyoto Protocol developed countries agreed to reduce greenhouse gas emissions by 5.2% on average in comparison to 1990 levels (Gale et al.,

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2001). Hence several approaches have been suggested as potential methods to mitigate anthropogenic CO2: energy conservation, improved energy efficiency, use of renewable resources and biofuels or creation and enhancement of carbon sinks (IPCC, 2007; Pacala and Socolow, 2004). In the latter category carbon dioxide capture from point sources and storage in geological media has emerged as a promising technology for combating climate change. Depleted oil and gas reservoirs, saline aquifers and unmineable coal seams are suitable storage sites in which CO2 can be trapped physically and chemically (White et al., 2003). Chemical (solubility and mineral) trapping is generally more stable than the physical forms of trapping (structural and residual) (Bachu et al., 1994; Johnson et al., 2004). During mineral trapping CO2 can be stored in stable carbonate compounds at long time scales, thus safeguarding storage integrity(Allen and Brent, 2010; Lackner and Brennan, 2009) . The extent of CO2 mineral trapping depends on the kinetics of mineral-brine interactions. The mineral dissolution kinetics can be determined through laboratory experiments and extrapolated at reservoir scale. For longer time periods geochemical models are applied. Numerous studies have investigated the kinetics of mineral dissolution under various conditions, yet mineral dissolution data at in situ subsurface conditions (temperature, mineralogical characteristics, salinity, solution composition, pressure and pH) are scarce in literature (Bundschuh and Zilberbrand, 2011). For example, Zhang et al., (2007) investigated the dissolution of dolomite as a function of particle size (grain surface area: 5000-8000 cm2/g) at constant temperatures up to a maximum of 250oC, constant pressure of 12.07 MPa and at neutral pH in deionized water. They concluded that dolomite dissolution rates vary with the sample’s grain size even when normalized by surface area. Pokrovsky et al., (2005) studied the dissolution of carbonate minerals as a function of salinity (0.001M≤[NaCl]≤1M) and partial CO2 pressure (0-5 MPa) in acidic solutions (pH=3-4) at 25oC. They found that partial CO2 pressure only has a weak effect on dissolution rates compared to that of pH. Experiments in high salinity brines of variable composition, often encountered in hydrocarbon reservoirs, are very scarce. One such study is from Gledhill and Morse (2006) who examined the kinetics of calcite at reservoir conditions (pH= 5-6.5; T=25-82.5 oC) with pCO2 < 1 bar) using concentrated Na-Ca-Mg-Cl brines (50-200g/l TDS). They found that calcite dissolution and precipitation rates are composition dependent and that increasing ionic strength led to a reduction in dissolution rates. The current study aims at quantifying the kinetic rate of dolomite dissolution, relevant to conditions encountered in Rotliegend gas fields in northeast Netherlands, which are potential candidates for CO2 sequestration. The reservoir is characterized by hydrostatic pressures around 30 MPa and a temperature of 100oC and brine with TDS concentration of approximately 300 g/l, the highest encountered in literature so far. In our experiments there was no attempt to introduce partial CO2 pressure (PCO2 ) in the reactors other than the contribution of the ambient PCO2. It has been found that partial CO2 pressure only

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indirectly affects the dissolution of dolomite through changes in pH, as CO2 dissolves in brine making the environment more acidic (Pokrovsky et al., 2005; Schott et al., 2009). Dolomite (CaMg(CO3)2) dissolution has received less attention in literature due to its complexity as a two component carbonate (Morse and Arvidson, 2002; Wollast, 1990)It is however the most pronounced carbonate mineral in the Rotliegend gas reservoirs, representing 2 wt% of the reservoir mineralogy (Bolourinejad et al., 2014). The dolomite matrix ranges from fine particles of 20 µm size to coarser grains of 350 µm, as derived from SEM imaging measurements of Rotliegend core samples. The grain size distribution is an important parameter which can affect mineral dissolution rates and should be determined on a case specific basis, however it has rarely been tested in experimental studies. In our study dolomite dissolution rates were experimentally determined as a function of temperature, pH, in very high salinity brine, which – to the best of our knowledge- is the highest encountered in literature so far. The derived kinetic data will help to improve the simulation of CO2 sequestration.

7.1.1 Theoretical background

Mineral trapping initiates after CO2 is injected in the reservoir and dissolves into brine, producing carbonic acid (Reaction 7.1 and 7.2) (Bachu and Adams, 2003; Hellevang et al., 2005). Carbonic acid increases the acidity of the brine (Reaction 7.3) (Bachu and Adams, 2003). CO2(gas)↔CO2(aq) Reaction 7.1

CO2(aq)+H2O↔H2CO3 Reaction 7.2

H2CO3↔H++HCO3- Reaction 7.3

The acidic environment stimulates partial dissolution of the primary minerals present in the host rock, resulting in the release of divalent ions Me2+ (e.g. Ca2+ or Mg2+) (Bachu and Adams, 2003; Hellevang et al., 2005). This is of particular importance for storage capacity, since these ions react with bicarbonate ions to form stable secondary carbonates thus reducing initial porosity (Bachu and Adams, 2003; Hellevang et al., 2005). In this research experiments were performed with dolomite, the most pronounced carbonate mineral in the Rotliegend gas fields (Bolourinejad et al., 2014). Dolomite dissolution is complicated by the fact that it is a two component carbonate mineral, which is why it has not been studied extensively, especially at conditions representative of CO2 storage. According to Plummer et al., (1978) dolomite dissolution is a composite rather than an elementary reaction and following the dissolution pattern of most carbonate minerals, it is comprised of three reaction mechanisms: protonation (Reaction 7.4), carbonation (Reaction 7.5) and hydration (Reaction 7.6). These reactions occur in parallel at the active sites at the dolomite surface.

CaMg(CO3)2+2H+ k1→ Mg2++Ca2++2HCO3- Reaction 7.4

CaMg(CO3)2+2H2CO3k2→ Mg2++Ca2++4HCO3

- Reaction 7.5

CaMg(CO3)2

k3↔ Mg2++Ca2++2CO32-

Reaction 7.6

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Where k1, k2 and k3 are the kinetic rate coefficients of the respective reactions. Reaction 7.6 can also proceed backwards, signifying dolomite precipitation. According to the transition state theory (TST) as proposed by Eyring (1935a; 1935b), the overall dissolution rate can be described by Equation 7.1:

r=k1aH+ n1 +k2aH2CO3

p +k3-k-3aMg2+aCa2+aCO3

2- Equation 7.1

where ai is the activity or effective concentration of the reactants, which is considered unity under the standard state and for pure water, which is why there is no activity term for the hydration mechanism. The exponents n1 and p, are called partial orders of reaction, usually ≤1 for dolomite (Brantley et al., 2008; Plummer and Busenberg, 1982). As (Plummer et al., 1988) stated, individual terms of Equation 7.1 can dominate the overall reaction dependent on pH or PCO2 conditions. Protonation is considered the predominant dissolution mechanism in the acidic region, typically below a pH of 5 (Yadav and Chakrapani, 2006). Carbonation has been suggested to dominate the overall reaction over a pH range between 4-6 at high PCO2 (Plummer et al., 1978). The region at pH>6 is commonly called circum-neutral and is dominated by the hydration mechanism (Plummer et al., 1978). However, in recent studies the carbonation term has been eliminated from the overall reaction. Pokrovsky et al. (2005) and Schott et al. (2009) suggested that surface carbonation is already accounted by the acidic mechanism, as carbonic acid dissolves in brine and reduces the solution pH. Moreover, for experiments at far from equilibrium conditions, as in this study, dolomite does not precipitate or other secondary minerals precipitate instead (Palandri and Kharaka, 2004). The latter happens when the ions released from the primary mineral combine with ions already present in the formation water. Based on the above, in case of dolomite dissolution during exposure to the acidic environment (pH<5) at far from equilibrium conditions, Equation 7.2 is reduced to Equation 7.2

r=k1aH+ n1 Equation 7.2

The temperature dependence of the dissolution rates is quantified through the Arrhenius equation, which assigns an activation energy value to each reaction rate coefficient (k). (Equation 7.3):

ki25e-Ei/R(

1T-

1298.15

)=kiT Equation 7.3

where Ei is the activation energy (J/mol) for the acid or hydration mechanism over a specific temperature range, R is the gas constant in J.mol-1.K-1, ki

25 is the kinetic rate coefficient for the acidic or hydration mechanism at 25oC and ki

T is the kinetic rate coefficient at temperature T (Marini, 2006). It should be noted that the overall equation (Equation 7.2) does not include the effect of ionic strength or individual ions or ligands on the dissolution rates. It is likely that the dissolution mechanism is affected by the presence of ions in the solution. In the present paper this effect is included in the kinetics rate coefficients of the main dissolution mechanisms.

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7.2 Methodology

7.2.1 Sample preparation

Dolomite samples were obtained from Gerolstein in the Eifel (Germany). For the experiments dolomite was crushed into powder and screened with a graduated sieve set. From the sieved samples three different (min, mid, max) grain sizes were used in the experiments. Those were inferred from the cumulative size distribution of dolomite in core samples of Rotliegend sandstones from gas fields in North-East Netherlands (Bolourinejad et al., 2014). The surface areas for the three grain sizes were determined using Scanning Electron Microscopy by applying a geometric quantification method assuming cubic-shaped dolomite grains. The surface area of the smallest grains (20-25µm) is 936 cm2/g, the surface area of the medium grains (75-100 µm) is 225 cm2/g and the surface area of the coarser grains (300-350µm) is 66 cm2/g. The representative grain diameter value for each sample was the median diameter of the grain size distribution as obtained from 30-50 grains for each grain size class. These values together with the standard deviation and surface area are presented in Table 7.1. Table 7.1. Median diameter for each grain size class and corresponding surface areas.

Grain size (µm) 25-100 µm 75-100 µm 300-350 µm

Median diameter 21 89 316

Standard deviation 7 22 47

Surface area (cm2/g) 936 225 66

The mineral purity was examined by SEM-EDS, from which less than 3 wt% impurities of Al, Mn, Fe, K and Si were traced in the samples. These are illustrated in Table 7.2.

Table 7.2. Impurities detected by Scanning Electron Microscopy (SEM)

Element Wt % Al 0.71 Si 0.81 K 0.18

Mn 0.34 Fe 0.51

7.2.2 Aqueous solution

As derived from well data, the Permian Rotliegend reservoir contains high salinity brine, the composition of which is presented in Table 7.3 illustrating the major ions present in the formation water. This is also the composition chosen for the aqueous solution used in the experiments.

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Table 7.3. Brine composition of the Permian Rotliegend gas fields in northeast Netherlands, as obtained from well data.

Ion Concentration (ppm)

Na+ Ca2+ Mg2+ K+ Cl- S2-

81338 25193 2346 1462 176626 68

7.2.3 Apparatus

Experiments were conducted in 200 ml glass batch reactors. Each reactor was placed in an oil bath to ensure thermal insulation and the whole system was placed on a hot plate. The solution was continuously stirred with a Teflon magnetic stirring bar at a speed of 300 rpm. The reactor had two openings, one for placing the thermocouple and one for sampling extractions. A Teflon tape was used to completely seal and cap the thermocouple opening to avoid evaporation during the experiment. A schematic illustration of the experimental setup is presented in Figure 7.1.

Figure 7.1. Schematic illustration of the experimental setup used in the present study.

7.2.4 Experimental procedure

For each grain size two experiments were performed at constant temperature, once at ambient and once at reservoir temperature of 25oC and 100oC, respectively. The purpose of experiments at both temperatures was to compute the activation energy and dissolution rate of dolomite. One gram of dolomite powder and 200 ml of solution were used in each experiment. The pressure was kept at one bar throughout the experiment. There was no attempt to increase the pressure at reservoir levels by introducing CO2 in the vessel. Normally, the pressure in the depleted reservoir is 50 bar and once CO2 is injected, the pressure rises up to 300 bar. Golubev et al. (2009), Pokrovsky et al. (2005) and Smith et al. (2013) have demonstrated that PCO2 pressure only indirectly affects the dissolution rates through changes in the pH. Experiments were carried out both in deionized water and in brine containing HCl. At this point it should be noted that the temperature was kept at 95 oC during the experiment in

106

deionized water to prevent the solution from evaporating. The rest of experiments were conducted at 100 oC, since the addition of salt in the water raises the solution’s boiling point. A schematic representation of the number and type of experiments is depicted in Figure 7.2.

Figure 7.2. Schematic representation of the number and type of experiments in acidic solutions. Experiments with smaller grains at higher temperatures (experiment number 5-7) produced fewer data in the acidic region at far from equilibrium. Especially experiment 7 did not sufficiently cover the acidic region and was repeated.

A total of 8 different experiments were conducted and their duration varied from 1.5 hours to 4 days. The water samples of 2-4 ml were taken at progressively longer intervals (starting from 15 seconds reaching to 3.5 days in some cases) for elemental analysis and pH measurements. For the sampling a 5 ml syringe was used, equipped with a 1.2 microns filter to avoid collecting dolomite grains during sampling. The pH was measured with a HI 991001 HANNA pH meter immediately after each sampling at 80 oC temperature. The solution samples were analyzed for the concentration of metal ions using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) Prior to the ICP analysis each sample was diluted 100 times and a further 10,000 times with 4%HNO3 solution. The elemental concentration was measured with an uncertainty of 1% standard deviation.

7.2.5 Calculations

The dissolution rates (mol/(cm2.s)) were computed as a function of the change in composition of the solution with time using Equation 7.4:

r=2·V

A·(mi+mi-1)·

d[Me2+]·10-6

MMe·dtEquation 7.4

where V(L) is the volume of water in the reactor between two samplings, A(cm2/g) is the specific surface area of the mineral, m(g) is the mass of the mineral, and [Me2+](mg/l) is the concentration of the metal ions (either Ca2+ or Mg2+) present in the solution, MMe(gr/mol) is the molar mass of Ca2+ or Mg2+, dt(s) is the time interval between two samplings, mi and mi-1 (g) are the mass of unreacted dolomite at the ith and (i-1)th

107

samplings, respectively. The factor of 2 in the numerator is derived from the average mass

expression: *+*+,-

� .

The rates in deionized water (experiment 1, Figure 7.2) were determined once with respect to Mg2+ and once with respect to Ca2+. In brine the high initial Ca2+ concentration of the brine (25200 ppm) complicated the measurements of Ca2+ release causing fluctuations in the elemental release. Hence the rates for experiments 2-7 were derived with respect to Mg2+. In experiments 1-3 (300-350 µm) linear regression was performed on the concentration vs time plots. In experiments 4-7 the concentration vs time plots were left unregressed in view of the small number of data points. In the calculation of dissolution rates from experiments researchers use either the initial or final mineral mass (Bibi et al., 2010; Daval et al., 2011; Drever, 2005). This can be one of the sources of uncertainty in the results. In this project the mass of unreacted dolomite present in the reactor was derived from mass balance calculations according to the formula by Hellevang et al. (2005) (Equation 7.5):

mt=mo-M∑∆nt-1→t Equation 7.5

where mo is the initial mass of dolomite present in the reactor (g), M is the molar mass (gr/mol) of dolomite and Δn0-2→0 the release of dolomite moles in the solution between

two samplings. Furthermore, PHREEQC (version 2.18.00) (Parkhurst and Appelo, 1999) was used with the Pitzer database (Pitzer.dat) in order to derive the thermodynamic parameters, such as the degree of disequilibrium of the system, the saturation indices and total dissolved inorganic carbon (TIC) . The input data included the solution temperature, pH, and concentrations of the dissolved ions in the solution.

7.2.6 Evolution of surface area

Similarly to the mass normalization term, most researchers normalize the dissolution rates by either the initial or final mineral surface area. However this assumption can be a significant source of variation in the results. Hence in this research the rate computations take into consideration the evolution of surface area during the experiments. First, dolomite powder was recovered after each experiment in order to measure the final surface area. . The greatest change in grain size was observed for the largest grain size, which indicated abrasion due to the stirring bar since the heaviest grains were more likely to be in contact with it. The post-experimental surface area was calculated with the same method as described before in section 7.2.1, with 50-80 grains of recovered dolomite measured after each experiment. Following this, the surface area at each time interval was calculated based on the observation that the change is due to the combined effect of dissolution and stirring. Specifically, the larger the amount of [H+] on the dolomite surface the greater the dissolution. Therefore, we assume a proportional function between the [H+] and the decrease in grain size, based on the initial and final surface area as measured using SEM. Additionally, the effect of the stirring bar continues throughout the whole experimental duration, thus we assume a proportional function with the time. By assigning the two linear dependencies of the change in grain diameter upon time and [H+]

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it is possible to compute the evolution of the surface area. This procedure was followed in all experiments, therefore every experiment is assigned its own surface area [H+] - time function. An example of the subsequent change of surface area with time is presented in Figure 7.3. In this graph, which corresponds to the experiment 3 with 300-350 microns grains at 25 oC, it is shown how the surface area develops with time and pH.

Figure 7.3. Evolution of surface area with time, during experiment 3 (300-350 microns, 25 oC) over a period of 5.5 hours. The change in surface area is more rapid at lower pH and continues at a lower rate beyond the acid dominated region. After a pH of 4.68 the system passes the acid dominated region.

7.2.7 Error propagation

Analytical uncertainties were calculated using the standard expression for error propagation Equation 7.6 (Barrante, 1998) :

∆P= 3∑ 4∂P∂xi52 6∆xi

27i 812

Equation 7.6

Where P is the calculated parameter, Δ9: is the uncertainty in the measured quantity of xi. For experiments 1-3 with the large grains (300-350 µm) the error propagation was calculated by the uncertainty of the slope of the concentration vs time plots, as derived from linear least squares regression. In experiments 4-7, where the data were not regressed, the uncertainties were calculated using standard propagation of error considering a 1% error on the measured ICP elemental concentrations. The time and volume uncertainties were not taken into account as they were very small.

7.3 Results

7.3.1 Elemental release

For the experiments in deionized water the rates were calculated both with respect to Ca2+ and Mg2+, while for the brine experiments only the Mg2+ concentration was used. The

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elemental Mg2+ and Ca2+ releases during the experiment with 300-350 µm grain size in deionized water and brine are presented in Figure 7.4.

Figure 7.4 Elemental concentration (mg/L) as a function of elapsed time for the 300-350µm dolomite grains: a) Mg2+ and Ca2+ in deionized water, at 25 ˚C (experiment 1, see Figure 7.2); b) Mg2+ in brine, at 25 ˚C (experiment 2, see Figure 7.2). Please note that in deionized water, the reactor or sample tube might have contained a small amount of salts, hence the initial Ca2+ and Mg2+ concentrations are not zero. The error bars in deionized water data points coincide with the symbol size. The Ca2+ elemental release concentration with time in brine was scattered even in the initial stages of the experiments. PHREEQC suggested that precipitation of Ca bearing species e.g. anhydrite, at higher pH (close to 5) would only occur during the experiments at 100 oC. During the experiments at 25 oC no precipitation of either Ca or Mg bearing species was suggested by PHREEQC. Thus the fluctuations are attributed to adsorption of Ca on the dolomite surface, at least in the initial phases of each experiment at low pH. A particularly interesting observation is that the amount of released Mg2+ in brine is considerably higher than in deionized water. In the experiments with smaller grains, 75-100µm and 20-25µm, dissolution of dolomite occurred very fast and the pH quickly shifted to close to equilibrium values. Hence, the number of measured elemental release data points is limited. For this reason, since it is difficult to assess how well the fitted line matches the data, the elemental concentrations were not regressed with time for experiments 4-7. Examples of the Mg2+ concentrations in brine at 25 oC for the experiments with 75-100µm (experiment 4) and 20-25µm grains (experiment 6) are presented in Figure 7.5.

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Figure 7.5 Mg2+ concentration (mg/L) for the 75-100 microns (experiment 4, Figure 7.2) and 20-25 microns grains (experiment 6, Figure 7.2) at 25 ˚C in acidic pH, in brine. Contrary to the measured Mg concentrations in brine, the Ca concentrations were scattered even from the first stages of the experiments. One possible explanation for this behaviour is the precipitation of Ca-bearing minerals (e.g. anhydrite), as PHREEQC suggested for the high temperature experiments for close to neutral pH values. However, adsorption of Ca ions on the dolomite surface is the most dominant process, as explained earlier on. The final total inorganic carbon (TIC) and final saturation indices (SI) with respect to dolomite are presented in Table 7.4. Table 7.4. Saturation indices (SI), total inorganic carbon (TIC), temperature and final pH for all experiments in brine.

Experiment Temperature (oC)

Final pH SI

TIC (mol/kg)

2 25 4.7 -1.8 3.24e-03 3 100 3.7 -5 5.47e-03 4 25 4.8 -0.88 6.68e-03 5 100 4.9 -0.48 9.57e-03 6 25 5.0 -0.94 2.56e-03 7 100 4.6 -0.85 1.35e-02

7.3.2 Kinetic rate of dolomite in deionized water

The elemental release exhibited an approximate stoichiometric behavior, with a Ca2+ to Mg2+ ratio ranging from of 1 – 1.2 throughout the Experiment 1 (Figure 7.2).

The calculated dissolution rates of dolomite in the deionized, acidic water with respect to both Ca2+ and Mg2+ release are presented in Figure 7.6.

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Figure 7.6 Dolomite dissolution rates with respect to Ca and Mg against time (Experiment 1, Figure 7.2). The rates exhibit a decrease with time as the pH shifts to higher values. The rates calculated from the elemental release of both Ca and Mg are in good agreement, with the release rate of Mg being slightly (some 5%) less than that of Ca. This is in line with the observation of Plummer and Busenberg, (1982) that the CaCO3 component of dolomite dissolves faster than the MgCO3 component (Reaction 7.7 and 7.8):

CaMg(CO3)2+H+⇌MgCO3+Ca2++HCO3- Reaction 7.7

MgCO3+H+⟶Mg2++HCO3-

Reaction 7.8 Since Reaction 7.8is the slow, rate-limiting step, this effectively controls dolomite dissolution, determining the rates at which dolomite is consumed. Therefore, the rates might as well be determined on the basis of Mg alone. In order to obtain the reaction rate coefficient (k) and order of reaction (n) the kinetic rates (logr) are plotted against pH (Figure 7.7).

Figure 7.7 Plots of logr against pH for Ca and Mg. The error bars coincide with the symbol sizes. The average pH values between two samplings were used for the plots. The line fitted to the Mg dataset, yields the relationship. logr= -0.27pH - 8.1 (k=10-8.1, n=0.27), and for the Ca dataset yields: logr= -0.28pH – 8.1 (k=10-8.1, n=0.28).

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Both empirical lines exhibit a very good linear correlation of logr with pH (R2>0.95), and yield similar rate coefficients. Based on the Ca2+ dissolution rates, the calculated reaction rate coefficient is logkCa = 8.11±0.05 and the order of reaction is nCa = 0.27±0.02. For Mg2+ the reaction rate coefficient is logkMg = 8.14±0.05 and the reaction order is nMg = 0.28±0.02.

7.3.3 Kinetic rate of dolomite in brine

The experiments performed in brine were complicated by the effect of high ionic concentration (TDS of approximately 300 gr/l). Despite the abundant occurrence of electrolytes in the solution, an initial linear trend in the Mg2+ elemental release with time was observed. It is worth noting that in all experiments the released Mg2+ versus time deviated from linearity (fluctuated) as the pH shifted past the acidic region into the circumneutral region, which is not used in the calculations. This behaviour is attributed to adsorption of Mg2+ on the dolomite mineral surface. The calculated dissolution rates with respect to Mg2+ release during experiment number 1-7 are presented in Figure 7.8.

Figure 7.8. Dolomite dissolution rates with respect to Mg2+ (a) grain size of 300-350 µm , 25˚C and 100˚C in brine and at 25˚C in deionized water (experiment 1-3) (b) grain size 75-100 µm, 25˚C and 100˚C in brine (experiments 4, 5) (c) grain size 20-25 µm , 25˚C and 100˚C in brine (experiments 6, 7) See Figure 7.2 for experiment numbers and parameters.

At grain sizes of 300-350 µm (Figure 7.8 a) the dissolution rate of dolomite in brine is approximately a factor 2 higher than in deionized water. Furthermore, the dissolution rates at 100 oC are a factor 3 faster than at 25 oC. The reaction rate coefficient and reaction order at 25 oC in brine are logkMg= 8.16±0.06 and nMg=0.07±0.03, and for the 100 oC are logkMg= 7.61±0.05 and nMg=0.08±0.02, respectively.

(a) (b)

(c)

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For the 75-100µm grains (Figure 7.8 b), at 25 oC logkMg= -7.9 ± 0.2 and nMg= 0.26 ± 0.06, and for the 100 oC dataset a logkMg= -7.45 and nMg= 0.17 was obtained. For the grain size of 20-25 µm (Figure 7.8 c) the resulting coefficients are logkMg= -6.6±0.5 and nMg= 0.6±0.1 at 25 oC, and logkMg= -5±1 and nMg= 0.7±0.3 at 100 oC . Furthermore, the experiment with the 20-25 µm grains at 100 oC was repeated in order to cover the more acidic region (Figure 7.8 c). The results are presented in Table 7.5 together with the respective activation energies in section 7.3.3.1. Table 7.5. Aggregated results of the reaction rate coefficients and activation energies for all grain sizes and temperatures in brine.

*: The reported value for the 75-100 microns grains at 100 oC (experiment 5, Figure 7.2) is based on only two data points, which do not fully represent the acidic region. That is why the value is likely underestimated. The same applies for the 20-25 microns grains at 100 oC, but this was partly compensated for by repeating the experiment. However, the resulting error remains large, yielding an inconclusive value for the activation energy at the small grain size.

7.3.3.1 Activation energy of dolomite in brine

The temperature dependence of the reaction kinetics is expressed via the activation energy (Equation 7.3.). The activation energy can be derived by plotting the natural logarithm of the dissolution rates (lnk) against the reciprocal temperature (1/T) as shown in Figure 7.9 (Marini, 2006).

Figure 7.9 Arrhenius plot of natural logarithm of the dissolution rates (lnk) against the reciprocal temperature (1/T). The slope of the line is the ratio of the activation energy over the gas constant (-Ea/R).

T = 25 oC T = 100

oC

Grain size (µm ) Logk n Logk n Ea (kJ.mol-1

)

300-350 -8.16 ± 0.06 0.068 ± 0.026 -7.61 ± 0.05 0.08 ± 0.02 15.72 ± 2.40

75-100 -7.88 ± 0.17 0.26 ± 0.06 -7.45 * 0.17* 12.12 ± 4.83

20-25 -6.62 ± 0.54 0.54 ± 0.14 -5.96 ± 0.98 0.5 ± 0.3 18.70 ± 31.82

-1

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This method is based on the assumption that the activation energies are constant throughout the selected temperature range, in this case between 25oC – 100oC as well as the selected pH range, in this case 2-5. From the graphs of lnk versus 1/T the slope of the line (-Ea/R) is derived, leading to a value for the activation energy. The results are presented in Table 7.5. It follows that the surface area normalized dissolution rates increase with decreasing grain size. Therefore, apart from a temperature dependence, the rates exhibit a critical dependence on particle size as well. The rate coefficient for the 75-100 µm grains at 100 oC (experiment 5, Figure 7.2) is likely underestimated since it covers the acidic region from a pH>2.5.

7.4 Discussion

7.4.1 Effect of solution composition

The experimental results show that the dissolution rates of dolomite in brine are considerably faster than those in deionized water. This was unexpected since the brine contained high concentrations of ions similar to those released from dissolving dolomite, namely Ca2+ and Mg2+, which would lower the dissolution rate of dolomite. The explanation is found when inspecting the competing mechanisms acting on dolomite dissolution in brine. One of these mechanisms is the so-called “ion-pairing” effect (Ford and Williams, 2013) .For instance, Ca2+, Mg2+, K+ or Na+ can combine with CO2-

3, HCO-3

or SO2-4 etc. in usually weak associations (Adams, 1971). This effect tends to decrease the

activities of the ions, leading to greater solubility of dolomite. However, this is more likely to happen later in the experiments, as the total inorganic carbon in the solution increases in combinations with CO2-

3, HCO-3. Furthermore, the electrostatic forces

between the mineral surface (Ca and Mg) and the ions present in the brine are stronger than the chemical forces within the mineral (White, 2013). Thus, ions are loosely bound on the mineral surface, polarizing the surface charge on the minerals, thereby making the ionic bonds weaker and possibly increasing ion detachment (Mg2+ and Ca2+) from the mineral surface (Aagaard and Helgeson, 1982; Walther, 1996). These mechanisms are in line with the observation that the brine takes up more of the dissolved elements than deionized water, as well as with the faster dissolution rates of dolomite in brine. The calculated rate coefficients in brine (logk(Mg)=-8.16 and deionized water (logk(Mg)=-8.14) do not reflect this large difference. The dissolution rates in deionized water reduce faster with the shift in pH (steeper slope). In brine however, the rates respond differently to the change in pH, due to the effect of electrolytes. This difference due to solution composition is better reflected in the reaction orders (n=0.26 in deionized water at 25 oC and n=0.068 in brine at 25 oC). It is worth noting that the regression line for the calculation of k in deionized water has a high correlation factor (R2>0.95), which leads to the conclusion that the change in pH is indeed the dominant mechanism of dolomite dissolution in deionized water.

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In brine there are multiple mechanisms interfering with the dissolution of dolomite as discussed above. These mechanisms have not been incorporated in the empirical formula, since that would require the assessment of the effect of each solution species on the dolomite dissolution separately. Since the regression line still has a reasonably good correlation factor (R2>0.78) it can be concluded that the elemental release still can vary linearly with the change in pH, although other competing mechanisms complicate the overall dissolution mechanism, leading to deviations from the linear relationship between lnk and pH.

7.4.2 Effect of grain size and surface area

The effect of grain size on dissolution rate of dolomite is not extensively described or tested in literature. In the present work, a difference in the rates with grain size is indeed observed, with smaller grains exhibiting faster surface area normalized dissolution rates. It is worth noting that dissolution on the mineral surface does not occur uniformly but rather on individual active sites. (Holdren and Speyer (1985) and Drever (2005) stated that these active sites change substantially with varying grain size. Specifically, they argue that the number of active surface sites per unit surface area is lower for the coarser grains. This explains why the rates normalized for geometric surface areas are not the same, meaning that the non-normalized rates do not scale linearly with the geometric surface area.

7.4.3 Effect of temperature and pH

In general, dolomite dissolution rates increase with temperature and decrease with pH. The effect of temperature on the dissolution rates is determined by the activation energy as applied in the Arrhenius equation. Databases for activation energies of minerals are mostly constrained to atmospheric conditions and little data exist for reservoir conditions. Regarding the pH dependency, it is evident that the acidity is still largely driving the dissolution. The dissolution rates decrease with increasing pH. A comparison between the dissolution rate coefficients in acidic environments has been made between the current study and values from literature at the same or at least similar temperatures, but in very low salinity brines or deionized water (Table 7.6). Table 7.6. Comparison of dissolution rate coefficient of dolomite between the current study and literature values

Deionized water/ Brine (Ionic strength)

Grain size ( µm)

Logk (Temperature)

Logk (Temperature)

Author

Deionized water not specified -7.01(25oC) -5.75 (80oC) Gautelier et al.(1989)

Deionized water 100-200 -6.58 (25oC) - Chou et al.(1989) Brine (<0.1M) not specified -9.41 (25oC) -8.62 (100oC) Pokrovsky et al.(2009)

Brine (~6M) 300-350 -8.16 (25oC) -7.61 (100oC) This study Brine (~6M) 75-100 -7.87 (25oC) -7.45 (100oC) This study Brine (~6M) 20-25 -6.62 (25oC) -5.96 (100oC) This study

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The reported values from literature fall within the range of values of this study. The same holds for the order of reaction, n, which is different among experiments. The values derived in the present study are in agreement with literature in the sense that they are fractional (<1), as first stated by Plummer and Busenberg (1982). It is worth noting that in the experiments with 300-350 µm grains in brine, the reaction order is very low compared to the other grain sizes. This indicates a poor dependency of the elemental release on pH. The adsorption process that takes place on the dolomite surface can explain this. During adsorption processes H+ ions compete with other free ions in the solution (e.g. Na+ and Ca2+). Since the mineral surface area is considerably smaller in the case of large grains, it is likely that less H+ ions are adsorbed. The free ions attached on the mineral surface can still polarize the surface charge, making detachment of dolomite components easier, as explained before. Hence this is the reason why the dissolution rates are still faster in brine than in deionized water.

7.4.4 Uncertainties and limitation

The results obtained from the current research are in support of the modelling of subsurface CO2 storage. Furthermore a new perspective is provided of the dissolution of a complex mineral in high salinity brines. However, in order to eliminate the large uncertainty that comes with these experiments more research is needed on a number of aspects as concluded from our study:: The evolution of the mineral surface area during dissolution should be further investigated, since there is no mathematical expression to describe it. Furthermore, the normalization terms used so far do not account for anisotropic dissolution along the mineral surface. In this study, we attempted to quantify the changes in the geometric surface area during each experiment by measuring the initial and final surface areas, assuming that the change is due to a combined effect of dissolution and stirring. This is also supported by other studies, such as the one by Metz and Ganor (2001) on the effect of stirring on kaolinite dissolution. Research is needed to quantify the adsorption of elements on the mineral surface and to determine the effect of each ion on the dissolution individually. It is also recommended to further investigate the process of isotopic fractionation, since heavier isotopes are more likely to adhere to the mineral surface, thus influencing the dissolution process. The activation energy is considered to reflect only the effect of temperature on the dissolution rates. In the present work, in accordance with most studies in literature, we assigned a single activation energy value to a selected temperature range (here 25-100oC) and pH range (here 2<pH<5). However, the activation energy is governed by the changes in pH, temperature and ionic strength, especially in highly concentrated brines. These effects can be eliminated if each temperature is assigned its own activation energy value, corresponding to smaller pH ranges. Although the use of batch experiments allowed for an easy control of the experimental conditions, flow-through experiments could possibly better simulate the subsurface dynamics.

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7.5 Conclusion

The dissolution of three different dolomite powder size fractions was studied in the acidic, far from equilibrium conditions. The pH range of the reported experimental results was between 1 - 5, at temperatures of 25 oC and 100 oC, in deionized water and in brine with TDS of approximately 300 g/l, conditions characteristic of the Rotliegend gas reservoirs in North East Netherlands. The experiments were conducted in closed batch reactors, and the dissolution rates were derived from the change in the Mg2+ (and Ca2+ in the case of deionized water) concentrations with time. In the experiment in deionized the dolomite dissolution rate was calculated using the concentration of dissolved elements (Ca and Mg). The change in pH was confirmed as the dominant mechanism of dolomite dissolution in deionized water. Regarding the experiments in brine the elemental release in the acidic experiments exhibited a close to linear release of Mg2+ in the acidic region, similar to the one in deionized water. This indicates that the change in pH is still important mechanism of dolomite dissolution even in such concentrated brines. However, the elemental release also plays an important role, which is attributed to ion-pairing. The results indicated that the dissolution rates are faster in brine than in deionized water We also derived the dissolution rates and reaction rates coefficients in brine for different grain size fractions, at different temperatures. The smaller grain sizes had higher reaction rate coefficients than the larger grains..