Open AccessArticle

Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO₂ as Cushion Gas

Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA

PETROBRAS, Rio de Janeiro 20231-030, RJ, Brazil

Aramco Americas, Houston, TX 77002, USA

Authors to whom correspondence should be addressed.

Hydrogen 2025, 6(1), 4; https://doi.org/10.3390/hydrogen6010004

Submission received: 9 December 2024 / Revised: 7 January 2025 / Accepted: 10 January 2025 / Published: 17 January 2025

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Figure 1
Synthetic 2D homogeneous model representing the saline aquifer studied in this paper (grid top map in meters). "> Figure 2
Relative permeability curves applied for this study [<a href="#B45-hydrogen-06-00004" class="html-bibr">45</a>,<a href="#B46-hydrogen-06-00004" class="html-bibr">46</a>]. "> Figure 3
Comparison of the H2S formation in moles over the years for two cases with different pyrite concentrations (0.5% in black and 2% in red). "> Figure 4
Comparison of the H2S formation in moles over the years for two cases with different hydrogen injection rates (1000 m3/d in solid blue, and 5000 m3/d in solid red). "> Figure 5
Comparison of H2S production in moles for three scenarios where the cushion gas was hydrogen, methane, and carbon dioxide. "> Figure 6
Cumulative volume of available H2 in m3 in the reservoir over 9 years. "> Figure 7
Cumulative volume of H2S generated in m3 in the reservoir over 9 years. "> Figure 8
H2S gas mole fraction captured after an elapsed time of one year and a half from the initiation of the simulation. "> Figure 9
Cumulative produced H2S in m3. "> Figure 10
Cumulative produced volume of H2 in m3 over time. "> Figure 11
Cumulative hydrogen production (in kg) for different cases. "> Figure 12
H2 volume (in m3) in the reservoir with methanation process. "> Figure 13
Hydrogen cumulative production (in kg) with the prolonged producing operation for Case H and base case. "> Figure 14
The minimum and maximum impurity levels for the different gases within UHS. "> Figure 15
Water saturation at the same time point for the base case (on top) and Case H (on bottom). "> Figure 16
Volume of water (in m3) in the aquifer for the base case and Case H. "> Figure 17
Cumulative water production (in m3) for 2 different cases. "> Figure 18
Average reservoir pressure (in kPa) for 2 different cases. "> Figure 19
H2 cumulative moles in the reservoir. "> Figure 20
CO2 cumulative moles in the reservoir. ">

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Abstract

Hydrogen is a pivotal energy carrier for achieving sustainability and stability, but safe and efficient geological underground hydrogen storage (UHS) is critical for its large-scale application. This study investigates the impacts of geochemical and biochemical reactions on UHS, addressing challenges that threaten storage efficiency and safety. Geochemical reactions in saline aquifers, particularly the generation of hydrogen sulfide (H2S), were analyzed using advanced compositional and geochemical modeling calibrated with experimental kinetic data. The results indicate that geochemical reactions have a minimal effect on hydrogen consumption. However, by year 10 of storage operations, H₂S levels could reach 12–13 ppm, necessitating desulfurization to maintain storage performance and safety. The study also examines the methanogenesis reaction, where microorganisms consume hydrogen and carbon dioxide to produce methane. Numerical simulations reveal that microbial activity under suitable conditions can reduce in situ hydrogen volume by up to 50%, presenting a critical hurdle to UHS feasibility. These findings highlight the necessity of conducting microbial analyses of reservoir brines during the screening phase to mitigate hydrogen losses. The novelty of this work lies in its comprehensive field-scale analysis of impurity-induced geochemical and microbial reactions and their implications for underground hydrogen storage. By integrating kinetic parameters derived from experimental data with advanced computational modeling, this study uncovers the mechanisms driving these reactions and highlights their impact on storage efficiency, and safety. By offering a detailed field-scale perspective, the findings provide a pivotal framework for advancing future hydrogen storage projects and ensuring their practical viability.

Keywords:

underground H₂ storage; geochemical reaction; microbial reactions; cushion gas; H₂ recovery; H₂ plume

1. Introduction

Hydrogen is emerging as a key element in the shift towards sustainable energy because of its adaptability and reduced carbon emissions throughout its lifecycle [1]. With an energy density that surpasses that of natural gas by weight, hydrogen acts as a strong candidate for being an alternative energy source and carrier. Recent estimates project an annual growth of hydrogen production of up to 10% [2].

Therefore, developing effective storage methods is crucial in transitioning toward clean energy and net-zero emissions. Storing hydrogen in underground formations, such as depleted reservoirs or saline aquifers, is an effective strategy for long-term storage, ensuring that the energy supply remains consistent, particularly when the demand is high [3,4]. There are ongoing research efforts focused on understanding the detailed processes involved in storing hydrogen in subsurface formation. Primarily, the potential of geochemical and biochemical reactions emerges as a critical research domain, which demands in-depth studies and evaluation of any potential risks, such as the alteration of the reservoir’s properties over time [5,6], and the formation of undesired gases like hydrogen sulfide (H₂S) which can adversely affect the infrastructure, or bio-methane which can degrade the purity of hydrogen.

Herein, we shed light on the possibility of H₂S generation and bio-methanation, and we assess their influence on storage’s feasibility and safety. The change in the stored gas composition was a common observation during the storage of town gas in Europe, which is the most relevant experience to the future vision of underground hydrogen storage in saline aquifers or depleted gas reservoirs. The technical association of the European natural gas industry [7] published a list of the previous town gas projects (also referred to as manufactured gas or water gas), including nearly twenty geological storage projects. Nearly half of these projects are aquifers and depleted gas reservoirs. We performed a reinterpretation of the published data and addressed the technical issues that were reported for these projects, specifically focusing on hydrogen loss and reactivity. While navigating through the literature, we encountered a scarcity of information and data related to these projects. Nevertheless, we identified Ketzin (Germany), Lobodice (Czech Republic), and Beynes (France) as the most relevant projects, each with more published data and substantial information. It is important to note that town gas comprises multiple gases with varying compositions. Typically, these gases include H₂, CH₄, CO₂, CO, N₂, and He. Each of the previously mentioned projects has its unique gas composition and its distinctive geological properties. The average composition, in mole fractions, of each gas was reported by Liebscher et al. [8] to be 10–33% CH₄, 25–60% H₂, 12–20% CO₂ + CO, and up to 30% N₂, with the possibility of hydrocarbons and O2 being present. The literature indicates that all the mentioned projects experienced varying degrees of hydrogen loss and/or a change in gas composition. However, the analyses of the gas loss differed from one project to another.

1.1. Hydrogen Sulfide in Underground Hydrogen Storage

The formation of hydrogen sulfide (souring), in particular, is a common problem that has occurred previously in the oil and gas industry, causing corrosion to infrastructure and toxication to the existing gas, an issue which requires further gas treatment to overcome [9,10]. In the previous underground gas storage experience, the generation of H₂S was documented but not thoroughly explained or investigated [11]. The town gas storage at Beynes in France, for instance, encountered some composition changes, including the generation of hydrogen sulfide. Bourgeois et al. [12,13] presented the hypothesis that the generation of hydrogen sulfide that was observed in Chemery, France, is more likely attributable to abiotic processes rather than the biotic reactions of sulfate-reducing microorganisms. Their theory is supported by empirical evidence suggesting that certain geological and chemical conditions, such as the range of temperatures and pressures associated with salinity and alkalinity, can lead to the generation of hydrogen sulfide in the absence of microbial activity. The bacterial count tests conducted on the formation water extracted from these reservoirs yielded negative or inconclusive results. Therefore, the absence of bacteria in the formation’s brine suggests that biotic processes are not responsible for H₂S generation. On the other hand, the presence of impurities in the formation gas, especially CO₂, is believed to be the contributing factor driving abiotic reactions. Furthermore, the presence of pyrite in their qualitative scanning samples is believed to be the source of H₂S generation [13]. Other researchers also believed in the possibility of generating H₂S abiotically as a result of pyrite reduction in the presence of H₂. Spietz et al. [14] conducted several experiments involving laboratory-synthesized nanoparticulate pyrite and highly pure natural pyrite. The study conducted two sets of experiments, utilizing 100% H₂ with an aqueous concentration of 1.98 × 10⁻³ M in one set and 100% N₂ in the other. The pyrite weighed 1.5 g of ground particles that were immersed in 75 mL of base salt medium. The results obtained after five days revealed that the H₂ experiments generated a substantial amount of total sulfide (aqueous HS− and gaseous H₂S combined) equal to 7.19 (±0.01 μmol), while the N₂ experiments showed no observation of sulfide generation. They performed these experiments at 38 °C to determine if the pyrite reduction is possible below 90 °C, which has been validated as viable. Truche et al. [15], on the other hand, examined the possibility of pyrite reduction in the presence of hydrogen and the generation of H₂S in high temperatures ranging between 90 °C and 180 °C. They maintained the pH in a range of 6.9–8.7 by adding calcite powder. The dissolved hydrogen concentration was calculated using Henry’s law and found to range from 7 × 10⁻³ M through 24 × 10⁻³ M at temperatures ranging between 120 °C and 180 °C. Their results were in agreement with Spietz et al. [14]; the reduction of pyrite into pyrrhotite resulted in the formation of H₂S. Their results also revealed that increasing temperature is correlated with elevated concentrations of hydrogen sulfide (H₂S), prompting concerns regarding the storage feasibility within deep aquifers characterized by higher temperatures.

This interpretation emphasizes the significance of considering the abiotic factors in assessing the generation of hydrogen sulfide in underground hydrogen storage. In this paper, we aim to evaluate the abiotic reactions that can lead to the formation of H₂S during hydrogen storage in saline aquifers. Commencing with our exploration of the literature, hydrogen has the potential to act as a reducing agent of sulfur species such as sulfate and pyrite. This reaction will lead to the consumption of hydrogen as an electron donor, whereas sulfate or pyrite acts as an electron acceptor.

While sulfate reduction requires higher temperatures than the normative conditions typically encountered in saline aquifers, pyrite reduction can occur during the average deep saline aquifer temperatures. Assuming that we are injecting pure hydrogen that has no sulfide content, we are limited to the hypothesis of generating H₂S as a result of the pyrite reduction in the rock formation. Previous studies on town gas storage have documented varying levels of hydrogen sulfide (H₂S) content in the produced gas. Specifically, research conducted in France reported a range of 20 mg/Nm³ H₂S content, while similar investigations in the Netherlands observed levels around 10–15 mg/Nm³. The observed ranges surpass the permissible limit of (~3 mg/Nm³) H₂S content, indicating levels that exceed regulatory thresholds, leading to the need for desulfurization processes for the produced gas. However, for sustainable and feasible hydrogen storage, such gas treatment is considered a costly investment, and limiting or avoiding the cause of H₂S generation would be the optimum solution

1.2. Methanogenesis: A Biochemical Challenge in Hydrogen Storage

Besides the H₂S impurity that may raise concerns in UHS, the formation of CH₄ in UHS is another issue. Despite CH₄ being a primary energy source today, the process of methanogenesis is regarded as unfavorable for hydrogen storage in light of the net-zero emissions target, and all efforts are directed towards maintaining a high purity of the stored hydrogen. The presence of CO₂ impurity not only influences abiotic reactions but also plays a significant role in driving biochemical reactions, such as methanogenesis, and forms methane as a byproduct. This phenomenon has been previously observed in town gas projects. One of the town’s gas operations that lasted for a long time was the Ketzin aquifer located in Germany. Ketzin is a lower Jurassic sandstone aquifer that was utilized for town gas storage between 1964 and 1985. The town gas storage operation in this site underwent massive loss of the stored gas, degradation of underground technical infrastructure due to corrosion, and alternation in the gas composition at the withdrawal periods compared to the injected composition [8]. The Lobodice town gas storage facility is one of the few monitored and documented underground town gas storage projects, providing comprehensive insights and invaluable lessons for advancing future endeavors in reliable hydrogen storage [16,17]. The town gas composition (mole fraction) in Lobodice is 50–54% H₂, 25% CH₄, and a mixture of other gases (8–12% CO₂, 7–12% CO, 6–10% N₂) [16]. Within the first year of the gas storage, an alteration in gas composition was reported, including the formation of methane and the reduction of hydrogen, carbon dioxide, and carbon monoxide quantities, and up to 20% of the injected gas volume was lost in the formation.

The altered composition after 7 months of storage was 37% H₂, 40% CH₄, 9% CO₂, and 3% CO [17]. The production of methane, abiotically or biotically, is therefore highlighted as the main reaction that occurred in Lobodice [1,18]. The conditions of the reservoir, i.e., the presence of carbon dioxide, moderate temperature (25–50 °C), low pressure (4 MPa), low salinity, and an anaerobic environment (absence of oxygen), are conducive to methanogenic bacteria growth and hydrogen consumption [19], thereby supporting the hypothesis of the biotic formation of methane (methanogenesis). The archaea microorganisms accountable for methanogenesis were also reported to be present in higher-temperature conditions [20], thereby enabling methane generation in environments with elevated temperatures and where CO₂ or acetate (CH₃COO⁻) is present. These facts, therefore, raise significant concerns regarding the prospect of blending pure hydrogen with CO₂ as the cushion gas for UHS. Methanogenesis occurs when CO₂ reacts with H₂ to form methane and water [21,22,23,24].

The process of methane formation is called the Sabatier reaction [25], which occurs abiotically under elevated pressures and temperatures [30 bar, and 300–400 °C], and requires a catalyst, typically nickel, for the process to operate. These conditions significantly exceed the prevailing reservoir parameters, which serves to corroborate the invalidity of the hypothesis that methane was formed abiotically in Lobodice.

Limited studies have been conducted to study the source of methane in Lobodice, including isotopic studies [16,17] and simulation studies that model the Redox reactions as a function of microbial kinetics [26,27]. Smigan et al. [17] performed an experiment to verify the methanogenesis in Lobodice by utilizing samples of the stratal water taken from near the wells in Lobodice at a depth of 400 m, with samples of the rock formations after being grained into powder. A mixture of a 4:1 ratio of hydrogen to carbon dioxide was introduced to the samples, and then the sample tubes were pressurized to 150 kPa at a temperature of 37 °C and 60 °C for 2–4 weeks. Their results revealed the formation of methane and reductions in hydrogen and carbon dioxide concentrations, and therefore, the presence of the methanogenic bacteria was confirmed. They carried out isotopic analyses to indicate the source of the generated methane. Such analyses study the isotopic composition of the molecules involved, particularly carbon-12 (12C) and carbon-13 (13C) in the case of methane generation. The ratio of these components indicates the origin of the methane, and they confirmed that it was generated from microbial activity. Buzek et al. [16] performed similar experiments on samples taken from the same reservoir. Buzek [16] and Smigan [17] both agreed that the methane in Lobodice was generated through microbial activity. This particular experience underscores the significance of impurity injection in hydrogen storage and its potential effect on hydrogen consumption. Additionally, it highlights the possibility of methane production as a result of the microbial reactions in the presence of CO₂, which could have significant technical and economic implications on hydrogen storage.

Existing studies investigating this matter are rare and lack a comprehensive description of the potential reactions and their possible impact on hydrogen storage [1]. Moreover, the experience of town gas storage led us to explore this dimension [5,28,29].

A few recent publications investigated different aspects of hydrogen reactivity in porous media. Zhan et al. [29] studied the influence of redox reactions on the dissolution of minerals in underground hydrogen storage using PhreeQC software version 3. They suggested that the presence of oxygen in the environment has a minor influence on hydrogen loss but can cause the dissolution of calcite and siderite and decrease the pH. They recommended excluding carbonate reservoirs for hydrogen storage, and suggested clean sandstone formation as the optimum option for hydrogen storage. Saeed et al. [30] have similarly modeled the geochemical reactions of various minerals using PhreeQC. However, they focused on the influence of the combined reactivity of these minerals on the porosity and permeability of the reservoir, and no discussion was made on the significance of each mineral in hydrogen loss. They varied the temperature, pressure, and salinity to look into the loss of hydrogen in a spectrum of conditions. They concluded that the abiotic reactions have minimum influence on hydrogen loss under different pressure, temperature, and salinity values.

To keep the objective of this paper focused on the influence of pyrite reduction in underground hydrogen storage (UHS), we have excluded the study of calcite mineral. More analysis on calcite dissolution can be found in the following references [31,32].

The existing research on hydrogen reactivity appears to primarily center around geochemical modeling, with limited consideration for transport modeling essential to account for the complex nature of hydrogen storage operations, including cyclic injection and production. In this study, we integrated geochemical and biochemical reactions in a compositional and reactive transport model.

The novelty of this work lies in its comprehensive field-scale analysis of impurity-induced geochemical and microbial reactions and their implications for underground hydrogen storage. By integrating kinetic parameters derived from experimental data with advanced computational modeling, this study uncovers the mechanisms driving these reactions and highlights their impact on storage efficiency, and safety. By offering a detailed field-scale perspective, the findings provide a pivotal framework for advancing future hydrogen storage projects and ensuring their practical viability.

The main assumptions in this paper are as follows:

The caprock was not explicitly modeled, and diffusion into its structure was not accounted for. This assumption is made based on [33], who found minimal to no impact of hydrogen diffusion into the caprock;
Other microorganism-induced reactions were neglected, since the likelihood of their formation in the temperature and pressure ranges we are dealing with is low;
No restrictions were imposed on the water production, assuming the facility could handle the water production.

2. Materials and Methods

The following section will present the geochemical and geological models utilized for this study, offering insights into each model’s description and presenting the parameters associated with these models.

2.1. Numerical Simulation of Geochemical and Biochemical Reactions

2.1.1. Chemical Equilibrium Reactions in the Aqueous Phase

The acid-based and oxidization reactions occurring in the aqueous phase within the formation brine are governed by kinetic parameters sourced from the Wolery database [34]. For the underground storage of hydrogen, several reactions are critical to include in order to attain a more accurate, realistic, and detailed description of the geochemical changes that are anticipated to potentially occur during these storage operations. The introduction of hydrogen into a reservoir can lead to the formation of a redox environment characterized by a complex interplay of reduction–oxidation reactions. These reactions involve the transfer of electrons between different chemical species, which can significantly impact the geochemical and microbiological dynamics of the system. Hydrogen molecules are known for having a high potential to act as a reducing agent by donating an electron (oxidation), which contributes to the reduction of other species that accept the electrons, like pyrite. Hence, the oxidation reaction of hydrogen in the aqueous phase is the key reaction to represent the redox reaction of pyrite, and is stated as follows:

H_{2 (g)} = 2H⁺_(aq) +2e⁻

(1)

Moreover, the presence of impurities, such as CO₂, can intensify the effects of this reaction. Therefore, this factor must be included in the system to accurately predict the overall changes in geochemistry during hydrogen storage. CO₂ can dissolve in water to form bicarbonate (HCO₃⁻) and hydrogen ions (H⁺) (Reaction (2), which leads to a decrease in the pH. Primarily, the pH of the system is governed by the dissociation of water molecules, which break apart into hydrogen ions (H⁺) and hydroxide ions (OH⁻) (Reaction (3)). The pH of the environment, on the other hand, can influence pyrite reduction, leading to the release of hydrogen ions (H⁺) and the formation of bisulfide ions (HS⁻) and ferrous ions (Fe²⁺). Hydrogen ions (H⁺) and bisulfide ions (HS⁻) can combine to form hydrogen sulfide (H₂S) (Reaction (4)), which also can undergo a partial dissociation in water. The ions subsequently engage in reactions with the minerals in the formation, causing the dissolution of some minerals and precipitation of others, such as calcite and pyrite. Below are the potential reactions to occur in the aqueous phase that we included in the modeling of hydrogen reactivity model.

CO_{2 (aq)} + H₂O = H⁺_(aq) + HCO₃⁻ _(aq)

(2)

H⁺_(aq) + OH⁻_(aq) = H₂O

(3)

H₂S_(aq) = H⁺_(aq) + HS⁻_(aq)

(4)

The equilibrium constant (K_eq) for these reactions is determined using a mathematical equation involving a fourth-order polynomial in temperature (T), as follows:

Log₁₀(K_eq) = a₀+ a₁T + a₂T² + a₃T³ + a₄T⁴

(5)

where T is in °C, and the coefficients (a₀, a₁, …a₄) are obtained from the Wolery database for each mineral.

2.1.2. Mineral Dissolution and Precipitation: Transition State Theory Approach

Hydrogen’s reactivity with certain minerals found in rock formations is a fact. These reactions can lead to the dissolution or precipitation of minerals, which can significantly impact the productivity index and storage operations. Therefore, it is imperative to account for these geochemical changes to ensure the safe and efficient storage and usage of hydrogen. Hence, the rate of abiotic reactions of minerals, such as pyrite reduction, is calculated through the Transition State Theory (TST) [35,36].

The reaction rate (r) in the TST model is calculated as follows:

r = s g n [1 - (\frac{Q}{K_{e q}})] A s_{w} [k_{0} + \sum_{i = 1}^{n c t} k_{i} a_{i}^{ω i}] {|1 - {(\frac{Q}{K_{e q}})}^{ξ}|}^{ζ}

(6)

sgn: mathematical operator to return the sign of the expression;

Q: ion activity product (IAP);

S_w: aqueous phase saturation;

nct: number of reactant components;

A: reactive surface area;

a_{i}

: the activity of component i computed with Pitzer’s model;

ω i

: activity power;

ξ, ζ: TST model parameters.

The rate constant at a different temperature condition (

k_{o}

) is computed using the rate constant at the reference temperature (

k_{0}^{*}

), where the reference temperature

T^{*}

equals 298.15 K (25 °C) and R is the universal gas constant, approximately 8.314 J/mol K. The following equation expresses the calculation of the rate constant (

k_{o}

k_{o} = k_{0}^{*} . e x p [- \frac{E_{a}}{R} (\frac{1}{T} - \frac{1}{T^{*}})]

(7)

The modeling of this type of reaction is controlled by four parameters: the chemical equilibrium constant rate K_eq, the rate constant of the reaction at 25 °C, k₂₅, also referred to as the reference rate, the activation energy E_a, and the reactive surface area (A) for the mineral. The available parameter values from the open-source database [34] were utilized in our simulation. Table 1 represents the minerals considered in this study with the associated parameters to model the TST reaction [37].

The source of hydrogen sulfide in underground hydrogen storage is the presence of sulfur-containing minerals in the rock formations. The most important mineral, and the one known for its reactivity, is pyrite (FeS₂). The literature suggested the presence of minor quantities of this mineral. However, this mineral is highly reactive with hydrogen gas. Hydrogen acts as a reducing agent by donating electrons to the pyrite, and pyrite acts as the acceptor of electrons and, therefore, undergoes reduction, leading to the production of iron (Fe) and hydrogen sulfide (H₂S). Reaction (4) is taken into account in our numerical simulation to quantify the formation of H₂S within the hydrogen storage system.

2.1.3. Modeling Methanogenesis via the Arrhenius Reaction Framework

Due to the limited number of experimental studies and inadequate documentation of previous hydrogen storage operations, there is a notable level of uncertainty surrounding the fate of the stored hydrogen. A substantial part of this uncertainty arises from the complexity of the redox reactions’ kinetics that are governed by microbial activity. In this study, the methanogenesis reaction is modeled through the Arrhenius rate law [38]. The Arrhenius kinetics is a widely used model to describe the temperature dependence of reaction rates, and it is a suitable option to estimate the reaction rates in underground hydrogen storage through numerical simulations since the experimental data for microbial-induced reaction of hydrogen are limited. Thus, this methodology serves as a fitting approach for modeling the geochemical reactions catalyzed by microorganisms such as methanogens. The equation of the Arrhenius rate is as follows:

r = F . e x p [- \frac{E_{a}}{R T}] \prod_{i = 1}^{n o . o f r e a c t a n t s} c_{i}

(8)

r

: reaction rate, (mol/s);

F: rrequency factor, which is the number of collisions per unit time between reacting molecules in which a reaction did occur (1/mol·s);

E_{a}

: the activation energy required to facilitate the reaction (J/mol);

R: universal gas constant (J/mol·K);

T: absolute temperature (K);

c_{i}

: the molality of reactants (mol/kgw).

This approach involves calculating the reaction rate based on several key parameters, including the reaction order, frequency factor, and activation energy barrier. These parameters are determined through rigorous analysis of experimental data and are crucial for accurately predicting the reaction kinetics. More details on the data selection of the methanogenesis reaction can be found in Appendix A.

Typical values for the activation energy of methanation reactions catalyzed by methanogenic microorganisms are in the range of 30,000 to 80,000 J/mol (Joule per mol) [39,40]. On the other hand, the literature search did not yield specific frequency factor values for the methanogenesis reaction. However, published data on reaction rates provide a valuable basis for determining the frequency factor using theoretical calculations such as the Arrhenius reaction equation. The following subsection presents an overview of the data selection process for reaction rates and the determination of frequency factor values.

It is important to emphasize that the simulator utilized in this study is unable to predict or account for the microbial growth phase or the subsequent death phase. The estimation of hydrogen consumption is assumed to occur solely during the steady-state phase. Further research is required to quantify the natural duration until microorganisms transition into the death phase, which will subsequently result in a gradual decrease in the reaction rate until it ultimately ceases.

2.2. Solubility Modeling in Hydrogen Storage Systems

The solubility of gases in the aqueous solution is simulated using the general Henry’s law based on Li and Nghiem (1986) [41]. Li and Nghiem model is used to compute the H₂ solubility in brine, as a function of pressure and temperature according to (9), and calibrated for a specific salinity.

\ln (H_{i}) = \ln (H_{i}^{*}) + \frac{\bar{v_{l}}}{R T} (p - p^{*})

(9)

H_{i}

= Henry’s constant at current pressure (p) and temperature (T);

H_{i}^{*}

= Henry’s constant at reference pressure (p*) and temperature (T);

\bar{v_{l}}

= partial molar volume at infinite dilution;

R = universal gas constant, approximately 8.314 J/mol K;

i: species dissolved in water (H₂).

The alternative Henry’s law, which is a function of pressure, temperature, and salinity, uses correlations from Harvey (1996) [42] for the referenced Henry’s constant, and it is capable of accurately predicting the solubility for various gases up to 150 °C. Therefore, it will be used to compute the solubility of specific components, such as CO₂, H₂S, and CH₄.

2.3. Description of the Geological Model

The represented model is a synthetic 2D saline aquifer characterized by homogenous petrophysical properties throughout the reservoir (horizontal permeability of 100 mD and porosity of 30%). This model aimed to evaluate the geochemical aspect during UHS; therefore, the model was intentionally constructed to have uniform geological features to highlight the significance of geochemistry while disregarding the effects of geological variability. The model incorporates a single well positioned at the midpoint of the aquifer, serving both as the injector and producer and perforated through the first four layers. Figure 1 shows the model size, divided into 100 × 1 × 20 gridblocks; each gridblock has a volume of 10 m × 10 m × 5 m. The model discretization has been previously assessed and determined to be appropriate for simulating reactive transport [43,44]. The reservoir’s main properties are summarized in Table 2. The operation of our simulation starts with a one-year injection of the cushion gas (H₂ or CO₂). Following that, we set the injection constraint to be 5000 m³/day over six 6-month periods (spring and summer) for the working gas. We shut down the well for three months and started producing at double the rate (10,000 m³/day) for three months (winter season). Our model included 9–20 complete cycles of hydrogen injection/production over 20 years. To illustrate how fluid flows through porous media under varying saturation conditions, the interpolation of relative permeability sets for H₂/brine [45] and CO₂/brine [46] is incorporated into our model (Figure 2). Given the analogous flow behavior of CH₄ to H₂, we assumed that CH₄ mobility in the reservoir would be based on the same relative permeability curve for H₂/brine.

We included only the pyrite and calcite minerals in our models and excluded the rest. This assumption is based on trial experiments we ran numerically through complex models that included various reactive minerals, but no significant influence was observed in our simulations. Therefore, to save computational time and simplify the model, we included only these two reactions. Pyrite is found in trace amounts and does not exceed 1–2% of the rock volume in sandstones [47], and calcite is found in various volumetric concentrations in sandstone, ranging between 1 and 20% [48,49]. The composition of the formation brine is provided in Table 3.

3. Results and Discussion

Through reactive transport simulations, we aim to measure and predict the quantity of H₂S generated through abiotic reactions and the influence of bio-methanation during UHS. The potential utilization of an alternative cushion gas, such as CO₂, or the impurity of gases found in the subsurface can influence these reactions. Hence, we numerically experimented with this scenario by injecting CO₂ as the cushion gas and studying the change in geochemical reactivity. The results are divided systematically into two sections: (i) the first section discusses the pyrite reduction and the H₂S influence, and (ii) the second section explores the outcomes of methane formation and the potential consumption of hydrogen.

3.1. Abiotic Reactions: Pyrite Reduction and H₂S Generation

Table 4 provides a summary of all the cases mentioned in this result subsection.

3.1.1. The Influence of Pyrite Concentration

A minimum volume fraction of (0.5%) of pyrite and a maximum of 2% were both implemented as the only different factors in two duplicated scenarios to assess the impact of pyrite concentration on the generation of H₂S. Our results revealed that the concentration of pyrite was not an influential factor in decreasing or increasing the level of H₂S formed in the reservoir. Figure 3 is a comparison of the H₂S formation over the years for both scenarios.

Although the volume of pyrite was different, the changes in the mineral’s mole and the amount of H₂S formed were the same. Hence, we simulated other scenarios where the amount of the injected hydrogen varied, and therefore, the amount of dissolved hydrogen that would react with pyrite would be different. In the initial scenario, the injection rate remained consistent at 5000 m³/day, whereas in the subsequent scenario, the injection rate was reduced to 1000 m³/day. Our results showed that the total volume of injected hydrogen has a major influence on the amount of H₂S generated, as seen in Figure 4.

Similar results were also reported by Machado et al. [43], who stated that in the context of numerical simulation of CO₂ sequestration, the CO₂ injection rate was found to be a more influential factor impacting the dissolution of calcite than the initial concentration of calcite in the rock formation. Our results are consistent with their findings; however, further experimental studies are required to provide supporting knowledge on this observation and to ascertain the alignment of these results with the principles of geochemical behavior in nature or to identify any potential deficiencies in the numerical simulation.

3.1.2. The Presence of CO₂ Impurities

The presence of reactive impurities, such as CO₂, may alter the chemical environment and limit some reactions as a consequence. When CO₂ dissolves into brine, it forms carbonic acid, which then dissociates into bicarbonate and hydrogen ions, leading to an alternation in the pH of the system towards a more acidic environment [50]. Although the lower pH can create a stable condition for the pyrite reduction to thrive, the use of CO₂ as a cushion gas may alter the expected results. The strategic deployment of cushion gas denser than hydrogen, such as CO₂ and CH₄, facilitates the establishment of a confined spatial domain to contain the hydrogen in the reservoir, thereby constraining the lateral spreading of hydrogen molecules. This containment strategy effectively restricts the interaction of hydrogen with the minerals in the formation because it reduces the surface area for the minerals to interact with hydrogen. Hence, in the case of using a cushion gas other than hydrogen, there is less surface area of pyrite to interact with hydrogen, and consequently, the generation of H₂S is decreased. The influence of cushion gases on hydrogen plumes and lateral spreading is discussed in detail by Al Homoud et al. [51,52]. Figure 5 in our results presents a comparison of H₂S production in three scenarios where the cushion gas was hydrogen, methane, and carbon dioxide, respectively.

As mentioned in the previous discussion, the amount of injected hydrogen plays a substantial role in increasing the formation of H₂S in our simulation models because of the larger amount of dissolved hydrogen that would interact with pyrite (as the red curve shows). However, in the scenarios that employed CH₄ and CO₂ as the cushion gas, the total volume of injected hydrogen is exactly the same. Nevertheless, the H₂S formed in the scenario that utilized CO₂ as the cushion gas (the green curve) exceeded the level of H₂S formation in the last scenario where methane was the cushion gas. This result is explained from a physical perspective and a chemical perspective. Physically, CO₂ is highly soluble in water. Therefore, the volume of the cushion gas in reservoir conditions is less than that of methane, allowing for the more lateral spreading of hydrogen [52] and, therefore, more surface area for reactions. From the chemical perspective, as mentioned previously, the level of pH in the reservoir decreases as a result of CO₂ dissolving in water, and having acidic/neutral conditions in the reservoir can be attributable to the increase in H₂S production in Case D (CO₂ as a cushion gas) compared to Case E (CH₄ as a cushion gas). As the pH value decreases, there will be a higher concentration of hydrogen ions (H⁺), which can donate a proton to react with the pyrite, facilitating the reduction reaction, which is consistent with our discovery and provides a rationale for our findings.

3.1.3. Quantifying H₂S Production: Evaluating Safety Risks in Hydrogen Storage

The reference model for analyzing the risk associated with hydrogen sulfide (H₂S) will be the case that exhibited the maximum H₂S generation, specifically, the case that employed hydrogen (H₂) as the cushion. Here, we undertake a quantification of the volume of generated hydrogen sulfide (H₂S) in relation to the volume of injected hydrogen (H₂). Subsequently, we compare this quantified ratio against the acceptable limits established within the gas industry. Figure 6 and Figure 7 depict the volume of available H₂ in the reservoir and the volume of H₂S that was generated over the years in m³.

It is evident from these results that the maximum volume of the two components (H₂ and H₂S) available in the reservoir differs by a magnitude of 1000. However, most of the H₂S that formed in the reservoir accumulated along the perimeter of the H₂ plume and further away from the wellbore, as seen in Figure 8. Most of the reactions occur at the edge of the hydrogen plume, where hydrogen dissolves in water and interacts with pyrite; hence, most of the H₂S that is generated accumulates around the perimeter of the hydrogen plume, and away from the wellbore.

Therefore, we quantified the volume of H₂S that was produced with the H₂ in the withdrawal cycles. Figure 9 and Figure 10 illustrate the cumulative produced volume of H₂S and H₂, respectively.

The concentration of H₂S in the volume of produced gas was converted to ppm as follows:

C o n c e n t r a t i o n o f H_{2} S (p p m) = \frac{V o l u m e o f H_{2} S}{T o t a l V o l u m e o f p r o d u c e d g a s} \times 10^{6}

(10)

The results of this mathematical conversion yielded a value of 12–13 ppm of H₂S by the end of the 10th year of cyclic injection/production [53]. Linking these results of H₂S prediction to the regulation of H₂S content in gas production from previous town gas storages is a critical component of operational safety and environmental stewardship for the future of hydrogen storage. Previous studies regarding the acceptable content of H₂S in the produced town gas storage stated a threshold of 1.3 ppm of H₂S by volume [54] to be deemed acceptable to meet the criteria for exemption from gas treatment. Consequently, in light of our findings, hydrogen storage may encounter the production of H₂S that is beyond the acceptable limits, and desulfurization treatment would be necessary to overcome this problem.

3.2. Biotic Reactions: Methanogenesis and Its Impact on Hydrogen Storage

The cases presented in this subsection are summarized in Table 5.

3.2.1. Methanogenesis and Its Effects on Hydrogen Recovery

To comprehensively understand the influence of methanation on underground hydrogen storage (UHS), we analyze three models developed with different methanogenesis rates, which are Cases F, G, and H, and compare them to a base case that excludes geochemical and biochemical reactions. All models are identical in all other aspects, including the use of CO₂ as a cushion gas and exact injection and production rates. The primary objectives are to determine the extent of hydrogen consumption and loss due to methanation, assess the impact on water production, and evaluate changes in hydrogen purity. The most critical aspect of all is to understand how much hydrogen might be lost due to the conversion to methane.

3.2.2. Hydrogen Recovery

The recovery factor of hydrogen during the production process is found to be similar for all cases, with a minor difference (~0.6%) in recovery (Figure 11).

This result is similar to what was observed in the study published by Wang et al. [57], where the curves for H₂ recovery overlapped. However, the volume of H₂ in the reservoir will provide a better indication of how much hydrogen was lost overall. Thus, we plotted the volume of H₂ in the reservoir (Figure 12).

The case using the Wang rate (Case H) resulted in an approximately 50% reduction in the volume of hydrogen present in the formation. To further investigate the range of hydrogen conversion due to methanation, we plotted the hydrogen volume using the frequency factor calculated in this study based on Olla Field (Case F). In this scenario, the conversion of hydrogen led to a 2.3% decrease in the total volume of H₂ remaining in the reservoir compared to the base case.

The frequency factor in Case H is the same value utilized by Wang et al. [57]. However, the conversion of hydrogen we observed is significantly higher than the 35% maximum hydrogen conversion reported by Wang et al. [57]. Taking into account the geochemical simulations from various studies [53], one potential explanation for the disparities observed between the findings presented in this study and the results reported by Wang et al. [57] may be attributed to the elevated injection rate implemented in our study. Another reason that may have caused the underestimation of hydrogen conversion in their analysis compared to ours is the relative permeability curves applied in their study. Relative permeability curves are a crucial component in numerical simulations as they control the flow and mobility of gases, determining the extent to which fluids can travel across the reservoir. In their study, they assumed relative permeability for CO₂ and brine. This assumption can lead to an underestimation of the lateral spreading of H₂, thereby reducing the surface area for reaction and mixing with CO₂. Assuming CO₂/brine relative permeability is not a valid approach due to the significant differences in the physical properties of CO₂ and hydrogen. In this study, we assumed that H₂ and methane would follow the same relative permeability trend, a justified assumption given the similar properties of these gases. To account for the presence of CO₂ in the reservoir, we implemented a second set of relative permeability curves specific to the CO₂/brine system. This approach enhances the accuracy and validation of our results.

To further elucidate the impact of the methanogenesis reaction on hydrogen storage operations, we extended the production period for 5 years until a plateau state was reached. Our comparative analysis includes Case H with maximum hydrogen conversion and the base case.

The results shown in Figure 13 suggested a 20% decrease in the recovery factor for Case H compared to the base case. This is evidence that methanogenesis can significantly impact the operation of hydrogen storage when the cyclic injection of hydrogen is not consistent, and the reservoir pressure is not maintained for production. The annual injection cycles maintained reservoir pressure at a sufficiently high level to sustain production throughout the cyclic operation. However, when injection ceased for five years and hydrogen was only being produced, the impact of methanation reactions adversely affected the operation. This reaction not only consumed a portion of the hydrogen but also resulted in a reduction in reservoir pressure, rendering it unsuitable for continued production. The influence on reservoir pressure and why it was reduced as a result of methanation is explained in the following sections. Our finding is in agreement with Wang et al. [57], who reported a recovery factor decrease of 19% when the methanation reaction was included (using F = 1 × 10⁻⁶).

The conversion of 2.3–50% of the hydrogen in the reservoir, while unfavorable for H₂ storage, mirrors observations from some of the town gas storage systems mentioned previously, such as Lobodice town gas storage. The impact on hydrogen purity and the composition of the recovered gas, which is another key aspect of underground hydrogen storage, will be discussed in the next section.

3.2.3. Hydrogen Purity

Injecting an alternative cushion gas will inevitably reduce the hydrogen purity. Furthermore, potential reactions that introduce additional gases into the system will further degrade the purity of the injected hydrogen. Here, we present our assessment in quantifying the degree of impurity that may be reached.

We examined two cases: one based on the frequency factor of the Olla Field rate we correlated in this study (Case F) and another based on the frequency factor presented by Wang (Case H). In Case F, the cumulative production of CH₄ was minimal, totaling 152 m³, with a maximum methane content of 0.03% in the production stream. Conversely, Case H showed significant methane production, reaching 28,918 m³ by the year 2040, which corresponds to a maximum of 5% of the produced gas composition.

The lowest concentration of methane observed in Case H was 1.5% of the mole fraction. Additionally, we must consider the presence of CO₂ impurity in all of the presented cases. Below is a plot (Figure 14) illustrating the minimum and maximum impurity levels for the different gases within the system, comparing the base case with Case H. Note that the base case has no methane in the system.

Methane, being a gas with low density, tends to migrate upwards, especially in geological structures like anticline reservoirs. The configuration of an anticline provides an environment where gases, including methane, can be contained within the cap structure. As a result, there is a higher likelihood of encountering methane closer to the producer. This proximity increases the risk of methane entering the production stream if hydrogen is stored in an anticline structure. A complete assessment of this aspect must be considered for future studies.

In comparing various cushion gases used to prevent hydrogen loss, previous research has shown that methane and nitrogen are more effective than CO₂, with detailed explanations provided for these results [51]. Additionally, these studies often utilize idealized conditions, such as anticline aquifers, which are considered optimal for hydrogen storage.

Herein, our study focuses specifically on the use of CO₂ as a cushion gas and investigates the formation of methane as a consequence of its presence. We applied this analysis to a 2D flat model where hydrogen spreads laterally more than it would in an anticline model, leading to most reactions occurring away from the wellbore. Importantly, methane and other impurities are a significant concern for hydrogen purity. In our scenario, the methanation reaction not only consumes part of the cushion gas and a portion of the hydrogen, but also decreases the impurity of the produced hydrogen. This impurity formation of methane is likely to reduce hydrogen purity even further in an anticline model, where reactions can occur closer to the wellbore.

3.2.4. Water Production

In the methanation reaction, for every 4 moles of hydrogen and 1 mole of CO₂, 2 moles of water are formed. Here, the water production assessment is based on Case H. The methanation reaction affects both water production and reservoir pressure. Our results indicate that the water saturation profile is higher when methanation is taken into account. Figure 15 below illustrates the water saturation at the same time point (1 October 2026, which is the last period of shut-in before production begins).

Furthermore, the plot in Figure 16 illustrates the volume of water present in the reservoir over the operation period for both the base case and the scenario including the methanation reaction (Case H). The increase in water volume is 1920 m³, accounting for 0.06077% of the total water volume in the aquifer.

We hypothesize that the inclusion of the methanation process will lead to a measurable increase in water production and a corresponding decrease in gas volume, thereby reducing reservoir pressure. Our findings confirm this hypothesis, with the reaction-included model exhibiting an increase in water production and a noticeable decrease in reservoir pressure compared to the base case as observed in Figure 17 and Figure 18.

The methanogenesis reaction involves the consumption of 1 mole of CO₂ and 4 moles of H₂ to produce 1 mole of CH₄ and 2 moles of water (usually in the liquid phase at reservoir conditions). This results in a substantial decrease in the number of gas molecules involved. Based on the ideal gas law,

PV = nRT

(11)

The decrease in the number of gas moles, while the volume and temperature remain constant, leads to a decrease in pressure to maintain the balance in the equation. A comparison of the H₂ and CO₂ moles in the reservoir is shown in Figure 19 and Figure 20 to confirm the decrease in gas volumes when a methanation reaction is applied. Furthermore, the produced water will condense to liquid in the reservoir condition, which further reduces the total gas volume, leading to a decrease in pressure.

Rivolta et al. [58] modeled the bio-methanation reaction using STARS simulation by introducing a fictitious component that represents the bacteria in the water. Their results are in agreement with our findings and suggest that more than 20% of the hydrogen can be lost as a result of the methanation reaction if CO₂ is utilized as a cushion gas, or if a high impurity of CO₂ is found in the reservoir. They also agree that water production was elevated, and reservoir pressure decreased as a consequence of the reaction.

3.2.5. CO₂ as a Cushion Gas: Evaluation and Assessment

Assessing the methanogenesis reaction during hydrogen storage, particularly when CO₂ is utilized as a cushion gas, is crucial for two main reasons. Firstly, it is essential to investigate the potential loss of hydrogen due to its reaction with CO₂, and any possible operation complexity this may cause. Secondly, it is important to understand the impact on hydrogen purity. Maintaining high purity of stored hydrogen is critical, as various sectors demand high purity levels depending on each specific application. For instance, the transportation sector requires hydrogen with a minimum purity of 99.97% to ensure high efficiency and safe operation of fuel cells and other hydrogen-based technologies.

If the purity of hydrogen degrades during the storage period, purification technologies must be employed to restore it to the required standards. These purification processes can significantly impact the overall cost of hydrogen storage, potentially accounting for up to 30% of the total operational cost, as indicated by Wickham et al. [59].

In the context of hydrogen storage in saline aquifers, the selection of saline aquifers as storage sites is motivated by the potential for high purity of the produced hydrogen, owing to the exclusive interaction between brine and hydrogen within the system. While the fundamental concept of employing an alternative cushion gas holds promise for long-term benefits, aimed at minimizing hydrogen loss and maintaining reservoir pressure, the use of CO₂ as a cushion gas introduces risks of hydrogen impurity due to its reactivity with hydrogen and the likelihood of methane generation, as observed in the results discussed above.

Prior research conducted by Al Homoud et al. [53] has also highlighted the potential influence of CO₂ on the formation of H₂S, an additional impurity requiring removal. Moreover, apart from the intrinsic impurity of CO₂ itself in the produced hydrogen, comparative assessments of various gas alternatives have indicated that CO₂ exhibits lower performance in terms of recovering maximum hydrogen volume and maintaining hydrogen purity, as concluded by multiple studies [52,60,61]. Hence, based on the findings of our study and previous research, it is recommended to exclude CO₂ as a cushion gas in underground hydrogen storage (UHS) systems.

4. Conclusions

This study highlights the significant geochemical and microbial reactions that influence hydrogen storage performance and identify the potential hydrogen. Key findings include the following:

1. The injected rate of hydrogen is a critical factor affecting H₂S formation, while the concentration of pyrite in the matrix shows minimal impact on the simulations’ outcomes. After quantifying the concentration of H₂S in the produced gas, a range of 12–13 ppm of H₂S was predicted by year 10 of the operation. This range surpasses the acceptable limit that is specified by regulations governing gas safety operations.

2. Utilizing non-reactive cushion gases, such as nitrogen instead of CO₂, leads to reduced H2S generation and better containment conditions for hydrogen, thus minimizing hydrogen dissolution and pyrite reactivity.

3. The bio-methanation process can cause significant hydrogen loss—with reductions of up to 50% in in situ hydrogen volume. This decrease in hydrogen volume lowers the effectiveness of hydrogen storage and highlights the need for initial brine testing and careful selection of cushion gas.

It is essential to further investigate the impact of pressure and temperature on these geochemical and microbiological reactions, as well as to analyze microbial activity growth rates. Comprehensive data in these areas will aid in understanding the lifecycle of microbes in hydrogen storage environments.

Overall, these insights emphasize the importance of meticulous geological and microbial evaluations in advancing underground hydrogen storage technologies. Continued refinement of models and experimental methods will be crucial for improving the viability and reliability of these systems, thus supporting more effective and sustainable energy solutions in the future.

Author Contributions

Conceptualization, R.A.H., M.V.B.M., H.D. and H.A.; methodology, R.A.H., M.V.B.M. and H.A.; software, R.A.H. and M.V.B.M.; validation, M.V.B.M., H.D. and H.A.; formal analysis, R.A.H.; investigation, R.A.H.; resources, R.A.H.; data curation, R.A.H.; writing—original draft preparation, R.A.H.; writing—review and editing, M.V.B.M., H.D. and H.A.; visualization, R.A.H.; supervision, H.D. All authors have read and agreed to the published version of the manuscript.

Funding

The author: Rana Al Homoud, thanks the Saudi Arabian Cultural Mission (SACM) for their financial support.

Data Availability Statement

The data and model details used in this study are provided within the article.

Acknowledgments

The authors would like to thank Computer Modelling Group Ltd. (CMG) for the license support.

Conflicts of Interest

The author Marcos Vitor Barbosa Machado is employed by the company Petrobras, and author Harun Ates is employed by the company Aramco Americas. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Nomenclature

UHS	underground hydrogen storage
Sw	water saturation
Krw	relative permeability to water
Nm3	normal cubic meter
TST	Transition State Theory
sgn	mathematical operator to return the sign of the expression
Q	ion activity product (IAP)
S_w	aqueous phase saturation
nct	number of reactant components
A	reactive surface area
$a_{i}$	the activity of component i computed with Pitzer’s model
$ω i$	activity power
ξ, ζ	TST model parameters
K_eq	the chemical equilibrium constant rate
k₂₅	the rate constant of the reaction at 25 °C, also referred to as the reference rate
A	the reactive surface area for the mineral
$r$	reaction rate, (mol/s)
F	frequency factor, which is the number of collisions per unit time between reacting molecules in which a reaction did occur
$E_{a}$	activation energy required to facilitate the reaction (J/mol)
R	universal gas constant
T	absolute temperature
$c_{i}$	the molality of reactants.

Appendix A

Data Selection of Methanogenesis Rate

Although the Arrhenius reaction calculates the reaction rate at each time step, some key parameters are required to have a realistic reaction rate. The frequency factor is the primary input data in our simulation. The reaction rates found in the literature and the average activation energy reported from previous studies are utilized to determine the values of the frequency factor based on the Arrhenius equation.

Thaysen [56] reported a field rate of 0.02–1205 nmol/h for the hydrogen consumption in the methanogenesis process. However, the stoichiometry of the methanation reaction dictates that the molar ratio of hydrogen to methane is 4:1. Consequently, the reaction rate of methanation is one-fourth of the hydrogen conversion rate that is quantified in their study. Thus, we considered a methanation rate that ranges between 0.005 nmol/h and 301.25 nmol/h (nanomole per hour). After converting these numbers to the corresponding values in the relevant units we are utilizing (mol/s), our calculations yielded 1.39 × 10⁻¹⁵ to 8.37 × 10⁻¹¹ (mol/s).

Tyne et al. [55], on the other hand, studied microbial methanogenesis at a CO₂-EOR project located in Olla Field in Louisiana. Their research is highly relevant to our work because they also provide an in situ methanogenesis reaction rate based on data analyses of samples taken from the reservoir. Their study involved collecting samples from the wellhead and conducting detailed analyses for noble gases, stable isotopes, and clumped isotopologues using specialized techniques to distinguish between biogenic and thermogenic methane based on δ13C values. In chemistry, it is known that biogenic methane typically has δ13C values that are lighter (more negative) compared to thermogenic methane. The distinction between the two types is often described using a threshold value (e.g., around −50‰) [62,63]. This percentage refers to the ratio of isotopologues, which are molecules containing multiple isotopes of the same element, compared to a standard reference material. By utilizing the information from their analyses, they were able to calculate the rate of methanogenesis reaction in Olla Field. This analysis allowed them to quantify the percentage of CO₂ converted into methane, and they found that after 29 years, the biogenic formation of methane consumed about 13–19% of the CO₂ in the reservoir. They calculated the rate of the reaction and reported a range between 73 and 109 millimoles of CH₄ per cubic meter per year at standard temperature and pressure. This rate is equivalent to 2.31 × 10⁻⁹ through 3.47 × 10⁻⁹ moles per second. It is noteworthy that the rate obtained for the in situ measurement by Tyne et al. [55] aligns with the lower rate determined in the laboratory experiments by Thaysen et al. [56].

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Figure 1. Synthetic 2D homogeneous model representing the saline aquifer studied in this paper (grid top map in meters).

Figure 2. Relative permeability curves applied for this study [45,46].

Figure 3. Comparison of the H₂S formation in moles over the years for two cases with different pyrite concentrations (0.5% in black and 2% in red).

Figure 4. Comparison of the H₂S formation in moles over the years for two cases with different hydrogen injection rates (1000 m³/d in solid blue, and 5000 m³/d in solid red).

Figure 5. Comparison of H₂S production in moles for three scenarios where the cushion gas was hydrogen, methane, and carbon dioxide.

Figure 6. Cumulative volume of available H₂ in m³ in the reservoir over 9 years.

Figure 7. Cumulative volume of H₂S generated in m³ in the reservoir over 9 years.

Figure 8. H₂S gas mole fraction captured after an elapsed time of one year and a half from the initiation of the simulation.

Figure 9. Cumulative produced H₂S in m³.

Figure 10. Cumulative produced volume of H₂ in m³ over time.

Figure 11. Cumulative hydrogen production (in kg) for different cases.

Figure 12. H₂ volume (in m³) in the reservoir with methanation process.

Figure 13. Hydrogen cumulative production (in kg) with the prolonged producing operation for Case H and base case.

Figure 14. The minimum and maximum impurity levels for the different gases within UHS.

Figure 15. Water saturation at the same time point for the base case (on top) and Case H (on bottom).

Figure 16. Volume of water (in m³) in the aquifer for the base case and Case H.

Figure 17. Cumulative water production (in m³) for 2 different cases.

Figure 18. Average reservoir pressure (in kPa) for 2 different cases.

Figure 19. H₂ cumulative moles in the reservoir.

Figure 20. CO₂ cumulative moles in the reservoir.

Table 1. The input parameters to model the TST reactions.

Parameter	Pyrite	Calcite
Log₁₀(k₂₅)	−8.19 mol/m² s	−5.81 mol/m² s
E_a	90,900 J/mol	23,500 J/mol
A	5011.15 m²/m³	2709.95 m²/m³

Table 2. The synthetic reservoir properties utilized in this study.

Property	Value
Initial pressure	20,500 kPa @ 1000
Temperature	80 °C
Porosity	30%
Horizontal permeability	100 mD
Rock compressibility	5.8 × 10⁻⁷ kPa⁻¹
Pyrite, volumetric fraction	0.5–2%
Calcite, volumetric fraction	3%

Table 3. Ionic composition of formation water (personal communication with Aramco Americas. 2022. Houston, TX, USA).

Ions	Molality (mol/kg)
H⁺	1.00102 × 10⁻⁹
Ca⁺⁺	0.00249526
Na⁺	3.73896
SO₄²⁻	0.0104208
Fe⁺⁺	0.00179079
Cl⁻	1.88916

Table 4. Different scenarios of cushion gases and initial pyrite concentration.

Case Number	Cushion Gas Type	Pyrite Concentration	Injection Rate
A	Hydrogen	0.5%	5000 m³/day
B	Hydrogen	2%	5000 m³/day
C	Hydrogen	2%	1000 m³/day
D	Carbon dioxide	2%	5000 m³/day
E	Methane	2%	5000 m³/day

Table 5. Rate values and the associated parameters applied in this study.

Case Number	Methane Reaction Rate (mol/s)	Activation Energy (J/mol)	Frequency Factor (mol/s)	Reaction Rate Reference
F	3.47 × 10⁻⁹	0	3.47 × 10⁻⁹	Tyne et al. [55]
G	8.37 × 10⁻¹¹	0	8.37 × 10⁻¹¹	Thaysen et al. [56]
H	4 × 10⁻⁹	0	1 × 10⁻⁶	Wang [57]
Base Case	No reaction	NA	NA	-

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Al Homoud, R.; Machado, M.V.B.; Daigle, H.; Ates, H. Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO₂ as Cushion Gas. Hydrogen 2025, 6, 4. https://doi.org/10.3390/hydrogen6010004

AMA Style

Al Homoud R, Machado MVB, Daigle H, Ates H. Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO₂ as Cushion Gas. Hydrogen. 2025; 6(1):4. https://doi.org/10.3390/hydrogen6010004

Chicago/Turabian Style

Al Homoud, Rana, Marcos Vitor Barbosa Machado, Hugh Daigle, and Harun Ates. 2025. "Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO₂ as Cushion Gas" Hydrogen 6, no. 1: 4. https://doi.org/10.3390/hydrogen6010004

APA Style

Al Homoud, R., Machado, M. V. B., Daigle, H., & Ates, H. (2025). Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO₂ as Cushion Gas. Hydrogen, 6(1), 4. https://doi.org/10.3390/hydrogen6010004

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