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Volume 2017, Article ID 3482603, 11 pages
Research Article

A Geochemical Model of Fluids and Mineral Interactions for Deep Hydrocarbon Reservoirs

1State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
2Dimue Technology Ltd. Co., Wuhan, China

Correspondence should be addressed to Jun Li; moc.liamg@s9002nujil

Received 19 February 2017; Accepted 12 June 2017; Published 16 July 2017

Academic Editor: Keyu Liu

Copyright © 2017 Jun Li 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.


A mutual solubility model for CO2-CH4-brine systems is constructed in this work as a fundamental research for applications of deep hydrocarbon exploration and production. The model is validated to be accurate for wide ranges of temperature (0–250°C), pressure (1–1500 bar), and salinity (NaCl molality from 0 to more than 6 mole/KgW). Combining this model with PHREEQC functionalities, CO2-CH4-brine-carbonate-sulfate equilibrium is calculated. From the calculations, we conclude that, for CO2-CH4-brine-carbonate systems, at deeper positions, magnesium is more likely to be dissolved in aqueous phase and calcite can be more stable than dolomite and, for CO2-CH4-brine-sulfate systems, with a presence of CH4, sulfate ions are likely to be reduced to S2− and H2S in gas phase could be released after S2− saturated in the solution. The hydrocarbon “souring” process could be reproduced from geochemical calculations in this work.

1. Introduction

With the exploration and production of middle-shallow oil and gas reservoirs, the main oil/gas fields have come to the late stages of production. More and more intensive exploration work has been done on middle-shallow fields and it is not easy to achieve more breakthroughs. So, researchers are devoting more efforts in deep reservoirs (with depth more than 5000 m). In China, the depositional environment is quite complex and special, so abundant hydrocarbon resources are possible. From the drilling evidence, an effective hydrocarbon reserve was found at more than 7000 m depth in China [1]. More and more research on deep layer hydrocarbon exploration has been carried out in recent years.

For deep hydrocarbon research, fluid-rock interaction is an important topic, as it will influence the fluid composition, physical and chemical properties, and transportation in porous media. The geochemical reactions are more active at locations with both gas and water, such as so-called gas-water transition zones [2, 3]. When gas and water contact, both gas components and mineral will be dissolved in water, and many geochemical reactions could be triggered. In Sichuan basin, H2S can usually be found from gas reservoirs. The existence of H2S can be a result of geochemical reactions of dissolved hydrocarbon and sulfates. It is called “souring” process in some literature [2].

Numerical modeling of geochemistry is a useful tool to understand the mechanism of fluid-mineral interactions in deep reservoirs. PHREEQC is one of the most popular geochemistry software packages in hydrological applications [4]. The speciation in water associated with hundreds of chemical reactions can be dealt with. TOUGHREACT is a 3D reactive transportation simulator which is able to calculate geochemical reactions with similar database as PHREEQC [5]. This simulator has been widely used in CO2 geological storage and geothermal recovery projects. Both of the software programs are powerful for geochemical reaction analysis in porous media. However, for fluid-mineral interactions in deep reservoir, gas-brine phase partitioning and speciation should be carefully considered due to high temperature and pressure. In gas reservoirs, CO2 usually exists with quite a bit amount of hydrocarbons. So, in this work, we establish a mutual solubility model for CO2-CH4-brine systems, which is accurate for a pressure range of 1 bar to 1500 bar, temperature range of 0°C to 250°C, and salinity range of 0 to 6 m. With the solubility calculated by the model, PHREEQC is used to calculate equilibrium of CO2-CH4-brine-minerals (carbonates and sulfates).

2. CO2-CH4-Brine Mutual Solubility Modeling

We assume that there are two fluid phases (i.e., aqueous phase and nonaqueous phase) existing at given temperature, pressure, and feed composition. CO2 or CH4 always dominates nonaqueous phase. Their solubilities in water and H2O content in nonaqueous phase are desired to be accurately reproduced by a thermodynamic model. In equilibrium state, for each component in the system (e.g., component ), the chemical potential in each phase should be equal. Then we have,For nonaqueous phase,where stands for standard chemical potential of component , which is the ideal gas chemical potential at the pressure of 1 bar [6, 7];   is mole fraction of component in nonaqueous phase; is fugacity and is fugacity coefficient; is the gas constant (8.31446 J/K/mol); is temperature in ; and is pressure in bar hereafter.

For aqueous phase, where is the standard chemical potential of species in an ideal aqueous solution with a hypothetical unit molality [8]; is the molality (in mole/Kg water, molal for short hereafter) of salt in the aqueous phase; is the mole number of 1 kg water (55.508); is the mole fraction of species dissolved in the aqueous phase; is activity of component in aqueous phase; and is activity coefficient of component .

With (1) to (3), we have Here, equilibrium constant is defined as , so we have

The mutual solubility model of CO2-CH4-brine system is established based on the above principle. Equilibrium constants (), fugacity coefficients (), and activity coefficients () should be properly carefully obtained.

2.1. Equilibrium Constants

For equilibrium constant of H2O, we follow the work of Li et al. [7] with an empirical equation revised from Spycher et al. (2003):

The parameters ( to ) in (6) are all from Li et al. [7], listed in Table 1.

Table 1: Parameters of H2O equilibrium constant in (6).

For equilibrium constants of CO2 and CH4, we follow the form of Mao et al. (2013):where = CO2, CH4.    are parameters. The parameters are determined from experimental data of gas solubility in aqueous phase. See Table 2 for more details.

Table 2: Parameters of CO2 and CH4 equilibrium constants in (7).
2.2. Fugacity Coefficients

Peng-Robinson equation of state (PR-EOS for short [9]) is used from CO2, CH4, and H2O fugacity coefficients in the nonaqueous phase. PR-EOS is a classic two-parameter equation of state of cubic form. The related parameters of pure component systems can be found from the original work of Peng and Robinson [9]. For gas mixtures, mixing rule is used for the two parameters. where and are binary interaction parameters of species and . Binary interaction parameters for CO2, CH4, and H2O can be found in Table 3 according to Søreide and Whitson [10].

Table 3: Binary interaction parameter in PR-EOS.
2.3. Activity Coefficients

For activity coefficients, Pitzer model [11] was successfully used in gas-water-mineral modeling for high salinities in previous works [1215]. Cations, anions, and interaction between particle pairs are considered to influence the component activity behaviors in aqueous phase. The activity coefficient equations are as follows:where is cation molality, is anion molality, and , , and are parameters that are functions of temperature and pressure. , , and are known as Pitzer parameters and they are usually estimated from gas solubility data from aqueous solutions with dissolved salts. In this work, Pitzer parameters are usually calibrated from gas solubility from NaCl solutions. is assumed to be 0. As the approximation in Duan and Sun [14] and Duan et al. [16], and are estimated as and . All ternary parameters are estimated as . Pitzer parameters are listed in Table 4.

Table 4: Pitzer parameters for activity coefficients.
2.4. Model Validation

The model performance is evaluated from comparison of model results and related experimental data of CO2-CH4-brine systems (including the subsystems).

For CO2-H2O-NaCl systems, the experimental studies [1719] are sufficient, which cover temperature from 0°C to more than 250°C and pressure from 1 bar to more than 1500 bar. From our comparison, the average absolute derivations for most of the data points are less than 10%. Figures 1(a) and 1(b) show a comparison of CO2 solubilities in pure water and NaCl solutions calculated from this model and related experimental data. We can find that the model solutions agree with the experimental data in the wide ranges of temperature, pressure, and salinity. Figure 1(c) shows the H2O solubility in nonaqueous (CO2-rich) phase of the model solutions and experimental data. From the figure, the model can well reproduce H2O solubility in nonaqueous phase.

Figure 1: Mutual solubilities of CO2-brine systems. Lines are calculated results from this model, and dots are from experimental data. (a) CO2 solubility in pure water; (b) CO2 solubility in NaCl solutions; (c) H2O solubility in CO2-rich phase.

Experimental data of CH4-H2O-NaCl system are also sufficient with temperature from 0 to more than 250°C and pressure from 1 bar to more than 1500 bar [20]. Figures 2(a) and 2(b) show the comparison of CH4 solubilities in water and NaCl solutions of experimental data and this model. Figure 2(c) shows the experimental data of H2O in nonaqueous (CH4-rich) phase and the related model solutions. From the comparisons, the experimental data can be well reproduced by the model.

Figure 2: Mutual solubilities of CH4-brine systems. Lines are calculated results from this model, and dots are from experimental data. (a) CH4 solubility in pure water; (b) CH4 solubility in NaCl solutions; (c) H2O solubility in CH4-rich phase.

Compared with single gas (CO2 or CH4)-brine systems, gas mixture (CO2 and CH4 existing at the same time)-brine systems have less experimental data. The existing data are also not systematic. Qin et al. [21] have studied phase equilibria for CO2-CH4-H2O system at 325 K and 376 K and with pressure from 100 bar to 500 bar. 21 data points were generated in the work. We compared their results with our model. From the comparison (see Figure 3), we can conclude that the model can predict mutual solubilities for CO2-CH4-H2O system.

Figure 3: CO2/CH4 solubilities in water in CO2-CH4-H2O systems at different temperature and pressure. Dots are from Qin et al.’s [21] experimental data, and lines are from this model.

In summary, the comparison of the model solutions with existing experimental data shows that the model can well reproduce and predict mutual solubility data of CO2-CH4-brine systems in wide ranges of temperature, pressure, and salinity. The model is reliable to be used in gas-water-mineral equilibrium analysis.

3. CO2/CH4-Water-Mineral Interactions in Deep Environments

In Sichuan basin, carbonates (such as dolomite or calcite) are the dominant minerals in some natural gas reservoirs; meanwhile sulfates (such as gypsum or anhydrite) and clay minerals are also commonly found [22, 23]. In Sichuan natural gas reservoirs, CH4 is always accompanied with other components such as CO2, N2, or H2S [24]. PHREEQC is a famous software package for water-mineral interaction calculations. Pressure effects can be considered using its third version [4]. With an accurate mutual solubility model of CO2-CH4-brine systems, geochemical reactions in CO2-CH4-water-mineral systems can be calculated by combining this model and the PHREEQC functionality. Through this research, we aim to find out(i)the influences on geochemical reactions in depth (i.e., temperature and pressure increase or decrease);(ii)sensitivity of gas components (i.e., CO2 or CH4) to water composition, mineral dissolution, or precipitation.

In this work, the calculations are based on Sichuan basin background. The hydrostatic pressure is assumed to be 100 bar/Km, and geothermal gradient is assumed as 25°C/Km according to a previous work [25] with surface temperature set as 25°C. The depth range of the research is from 3000 m to 6000 m. Relationships of depth, temperature, and pressure are shown in Figure 4. To clarify the influences from gas components, sodium chlorite is considered as the only salt that is dissolved in water as an initial solution. Geochemistry equilibrium of CO2-CH4-brine-dolomite, CO2-CH4-brine-calcite, and CO2-CH4-brine-gypsum/anhydrite systems is studied. Two gas compositions are considered, pure CH4 or 10% CO2 + 90% CH4, to evaluate CO2 influences.

Figure 4: Temperature, pressure, and depth relationships.

Table 5 lists the species of ions, minerals, and gases which get involved in geochemical reactions in CO2-CH4-brine-carbonate systems and CO2-CH4-brine-sulfate systems.

Table 5
3.1. CO2-CH4-Brine-Carbonate Systems

For CO2-CH4-brine-carbonate systems, cases of fluid equilibrium with calcite and dolomite are studied, respectively. Figure 5 shows the molality of carbon (including , CO2, , CaCO3, , , and MgCO3) dissolved in aqueous phase with different depths, gas compositions, and salinities. Figure 6 shows the molality of calcium (including Ca2+, CaCO3, , and CaOH+) and magnesium (including Mg2+, MgOH+, MgCO3, and ) that is dissolved in aqueous phase. From Figure 6, it is shown that CO2 in the gas phase will promote calcite or dolomite dissolution. From the calculations, we find that, with CO2 existing in the system, carbon concentration in aqueous phase increases with depth. From 3000 m to 6000 m, the carbon molality is almost doubled in Figure 5 at different salinities. However, compared with calcium, magnesium is more solvable and increases with depth. From our calculation, in fluid-dolomite systems, with an increase in temperature and pressure, more calcite precipitates. We can conclude that, in deep carbonate environments, calcium is more likely to precipitate and magnesium ion is more likely to be rich in aqueous phase and transport to shallower areas due to diffusion gradient. So, in general, calcite approaches being existing in deeper environments and dolomite is more likely to be existing in shallower environments.

Figure 5: Molality of total carbon dissolved in water varying with depth at different salinities and gas compositions. Dashed yellow line represents the case of pure CH4 of gas in the system. Blue lines represent results from fluid-calcite systems (with gas composition CO2 : CH4 = 1 : 9 in mole). Red lines with dots represent the result from fluid-dolomite systems (with gas composition CO2 : CH4 = 1 : 9 in mole).
Figure 6: Molality of elements Ca and Mg dissolved in water varying with depth (with sodium chlorite molality 0). Yellow line represents the case of pure CH4 of gas in the system. Red lines with dots represent results from fluid-dolomite systems (with gas composition CO2 : CH4 = 1 : 9 in mole). Blue line represents results from fluid-calcite systems (with gas composition CO2 : CH4 = 1 : 9 in mole).
3.2. CO2-CH4-Brine-Sulfate Systems

The element sulfur can have different chemical valences such as −2, 0, +4, and +6 in nature. When sulfates are dissolved in water, sulfur is usually in +6 valence state. It could be reduced to other valence states when reducer exists in the solution. In deep gas reservoirs in Sichuan basin, sulfates commonly exist. Different fluid compositions may trigger different redox geochemical reactions and lead to different forms of sulfur or even reservoir properties.

In this work, we perform several numerical experiments to evaluate the influence of gas composition and depth on fluid-mineral equilibrium. For gas composition, we considered three cases: pure CH4, 10% CO2 + 90% CH4, and pure CO2. The calculations covered depth from 3000 m to 6000 m. Figure 7 presents S(−2) (i.e., sulfur dissolved in water with chemical valence −2, which can be S2−, HS, and H2S as ions) and S(+6) (i.e., sulfur dissolved in water in chemical valence +6, which can be , , CaSO4, and ) concentration in equilibrium of gas-water-gypsum. From Figure 7, we can find the following:(1)With pure CO2 in gas, S(−2) in water is extremely low, and more CH4 is dissolved in water leading to higher S(−2) concentration.(2)Higher CO2 mole fraction in gas phase will lead to higher S(+6) concentration in water phase.(3)With higher depth, higher S(+6) concentration can be found, but depth influence on S(−2) concentration is not clear.

Figure 7: Concentration of S(+6) and S(−2) in aqueous phase varying with depth in equilibrium of gas (pure CH4, 10% CO2 + 90% CH4, or pure CO2), water, and gypsum.

It is clear that CH4 is the key component for S(+6) to be reduced to S(−2) species in water. The related redox geochemical reaction isWhen CH4 and are dissolved in water, the above reaction is triggered, and CH4 is oxidized from C(−4) to C(+4). In the meantime, is reduced to S2−.

Figure 8(a) shows the amount of calcite precipitation for different cases of geochemical equilibrium. Referring to Figure 8(a), in case of pure CO2 in gas phase, there is no calcite precipitation; with higher CH4 mole fraction in gas phase, more calcite can be precipitated; in deeper environments, more calcite can be precipitated. This phenomenon is also connected with sulfur reduction. With CH4 dissolved in water, more sulfate is consumed and more calcium ions are dissolved in water. In this process, carbanions are generated because of the redox reaction. With more and more calcium and carbanion in the solution, calcite becomes saturated and precipitates. Another product is H2S in gas phase. With more and more S(−2) generated in water, S2− and H+ approach combining with one another, and H2S becomes saturated and is released in gas phase. As shown in Figure 8(b), with more CH4 in gas phase, more H2S will be generated in gas phase at equilibrium states. From this study, we can find that CH4-water-sulfate redox reaction could be a mechanism of H2S origin in gas reservoirs [2]. From the figure, we can also find that, at higher depth, more H2S can be generated. This result agrees with the statement from Li et al. [2].

Figure 8: (a) Mole number of calcite precipitated and (b) mole number of H2S released to gas with 1 KG water in equilibrium with gas (pure CH4, 10% CO2 + 90% CH4, or pure CO2) and gypsum at different depths.

4. Conclusions

In this work, an accurate mutual solubility model is constructed with “fugacity-activity” method for CO2-CH4-brine systems. This model has a wide application range of pressure, temperature, and salinity, which can be used for fluid phase equilibrium in deep hydrocarbon reservoirs.

Combined with the mutual solubility model and PHREEQC, the equilibrium CO2-CH4-brine-mineral systems under deep reservoir conditions can be calculated. The mutual solubility model can be used to calculate the mole numbers of CO2/CH4 dissolved in brine at given temperature, pressure, and salinity. With the dissolved mole numbers of CO2/CH4, PHREEQC is used to calculate the speciation between aqueous phase and mineral.

CO2/CH4-brine-carbonate (i.e., dolomite or calcite) and CO2/CH4-brine-sulfate (i.e., gypsum or anhydrite) equilibria were studied with the above methodology. From the study, we find the following:(1)For CO2/CH4-brine-carbonate (calcite or dolomite) systems, with an increase in depth, calcium is more likely to precipitate as calcite and magnesium is more likely dissolved in aqueous phase. In other words, dolomite could be rich in shallower position and calcite may approach being existing at deeper locations.(2)With CH4 present in the CO2/CH4-brine-sulfate (gypsum or anhydrite) systems, redox reaction is triggered and S(+6) is reduced to S(−2). H2S will be released when S(−2) becomes saturated in aqueous phase. This process could be one of the origins for H2S in gas reservoirs in Sichuan basin, China.

This work is an attempt to do preliminary fluid-mineral interaction calculations with a new established accurate mutual solubility model of CO2-CH4-brine systems combined with PHREEQC, version 3. The geochemical reaction parameters are still needed to be validated for high temperature and pressure. Also, more systematic research work of gas-water-minerals is still required in the future according to real depositional environments.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.


This work is supported by National Natural Science Foundation of China (Grant no. 41502246). Dimue Tech. Ltd. Co. provided technical support during the research. The authors also acknowledge the sponsorship from National Key R&D Program of China (2016YFE0102500).


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