# Hydrogen storage in depleted gas reservoirs with carbon dioxide as a cushion gas: Exploring a lateral gas separation strategy to reduce gas mixing

Harri A Williams, Niklas Heinemann, Ian L Molnar, Fernanda de Mesquita L Veloso, Toni Gladding, Tarek L Rashwan

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Harri A Williams, Niklas Heinemann, Ian L Molnar, Fernanda de Mesquita L Veloso, Toni Gladding, et al.. Hydrogen storage in depleted gas reservoirs with carbon dioxide as a cushion gas: Exploring a lateral gas separation strategy to reduce gas mixing. International Journal of Hydrogen Energy, 2025, 102, pp.1116 - 1129. 10.1016/j.ijhydene.2024.12.371. hal-04978019

HAL Id: hal-04978019

https://brgm.hal.science/hal-04978019v1

Submitted on 5 Mar 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

# Hydrogen storage in depleted gas reservoirs with carbon dioxide as a cushion gas: Exploring a lateral gas separation strategy to reduce gas mixing

Harri A. Williams<sup>a</sup>, Niklas Heinemann<sup>b, c</sup>, Ian L. Molnar<sup>b, d</sup>,
Fernanda de Mesquita L Veloso<sup>c, d, e</sup>, Toni Gladding<sup>a</sup>, Tarek L. Rashwan<sup>a, *, f</sup>

## ARTICLE INFO

Handling Editor: Suleyman I. Allakhverdiev

Keywords:

Depleted gas reservoir

Cushion gas

Lateral separation

CCS

Capacity estimation

Underground hydrogen storage (UHS)

## ABSTRACT

Large-scale H₂ storage in depleted hydrocarbon reservoirs offers a practical way to use existing energy infrastructure to address renewable energy intermittency. Cushion gases often constitute a large initial investment, especially when expensive H₂ is used. Cheaper alternatives such as CO₂ or in-situ CH₄ can reduce costs and, in the case of CO₂, integrate within carbon capture and storage systems. This study explored cushion and working gas dynamics through numerically modelling a range of storage scenarios in laterally extensive reservoirs – such as those in the Southern North Sea. In all simulations, the cushion and working gases were separated laterally to limit contact surface area, and therefore mixing. This work provides valuable insights into (i) capacity estimations of CO₂ storage and H₂ withdrawal, (ii) macro-scale fluid dynamics, and (iii) the effects of gas mixing trends on H₂ purity. The results underscore key trade-offs between CO₂ storage volumes and H₂ withdrawal and purity.

## 1. Introduction

Climate change is a defining challenge of our generation. The Paris Climate Change agreement, signed in 2015 by 196 member countries at COP21, set a goal of limiting global warming to below 2 °C, preferably to 1.5 °C, compared to pre-industrial levels [1]. This commitment necessitates that global energy systems must shift from fossil fuels to renewable power generation [2,3]. The UK Net Zero Strategy states that by 2035 the UK will be powered entirely by carbon-free energy. Offshore wind power is projected to be the primary source of clean power in the UK, with an anticipated 40 GW capacity by 2030 [4]. However, renewable energy sources, such as wind and solar power, offer only an intermittent supply of clean energy, where excess energy is curtailed.

Storing surplus energy in the form of hydrogen (H₂) offers a viable strategy to manage intermittency and reduce energy curtailment [5-8]. H₂ can be produced via electrolysis using excess renewable energy and stored for later use [9]. H₂ can be used in various ways within the energy supply network: (i) directly within fuel cells, [10-13]; (ii) used as feedstock in various industries [14,15]; (iii) fed directly into the natural

gas grid [16,17]; (iv) combined with captured CO₂ to drive methanation [18-20]. Numerous key advancements in H₂ technologies are enabling these applications. For example, the reducing cost of fuel cells has positioned H₂ as a key contender to replace diesel engines in heavy-duty transport [13]. Advancements in H₂ combustion technologies, such as H₂-rich gas turbines, will improve combustion efficiencies and lower carbon emissions [17]. However, reducing the cost of H₂ production remains a major challenge hindering the advancement of these technologies [12-14,16,17,21-26].

The generation of H₂ through other industrial processes, such as steam CH₄ reforming [27] and coal gasification [22] are currently the most widely used methods for H₂ production [28]. These methods require the use of fossil fuels and emit CO₂. Other heavy industry processes such as steel, concrete, and ammonia production also emit significant amounts of CO₂, which cannot be easily avoided. Emissions from these industries can be reduced through deploying carbon capture and storage (CCS) technologies, where CO₂ from industry is captured, transported, and stored permanently within geological reservoirs. The energy transition is likely going to require a wide range of energy carriers with varying CO₂ footprints, thus both CCS and H₂ are expected to

<footnote><sup>a</sup> School of Engineering and Innovation, The Open University, MK7 6AA, Milton Keynes, UK</footnote>

<footnote><sup>b</sup> School of Geosciences, University of Edinburgh, Grant Institute, James Hutton Road, EH9 3FE, Edinburgh, UK</footnote>

<footnote><sup>c</sup> Risk and Risk Prevention Division, French Geological Survey (BRGM), 3 Avenue Claude Guillemin BP 6009, Orleans cedex 2, 45060, UK</footnote>

<footnote><sup>d</sup> C-Questra BV, Singel 250, 1016 AB, Amsterdam, Netherlands</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: tarek.rashwan@open.ac.uk (T.L. Rashwan).</footnote>
**Abbreviations:**

H₂ – Hydrogen

CH₄ – Methane

CO₂ – Carbon dioxide

CG – Cushion gas

WG – Working gas

CCS – Carbon capture and storage

BHP – Bottom hole pressure

SM – Supplementary materials

**Units**

GWh – Gigawatt hour

KWh – Kilowatt hour

TWh – Terawatt hour

Mt – Megatonne

mD – Millidarcy

atm – Standard atmosphere

USD – United States dollar

be important in reaching climate targets, at least in the near future [28–30].

Small-scale H₂ storage can be provided in tanks and pipes [23], providing megawatt hour (MWh) capacity with a discharge capacity of hours to days. Medium-scale storage can be provided in underground salt caverns [31] or lined rock caverns [32], providing gigawatt hour (GWh) capacity over days to weeks through multiple operational cycles. Large-scale H₂ storage can be provided in siliciclastic subsurface porous reservoirs, e.g., depleted oil and gas formations or saline aquifers, providing GWh to terawatt hour (TWh) capacity over months and years [33,34].

Long-term H₂ storage and CCS require similar storage environments, which include an adequately porous and permeable layer of rock (i.e., a reservoir in which gas can be injected, stored, and withdrawn at sufficient rates) and an impermeable top formation (i.e., cap rock) to prevent vertical gas leakage through buoyant forces. The cap rock must be suitably oriented to prevent lateral gas loss and provide a containment barrier or mechanism to keep the gas in place [34–37]. Long-term storage of pure H₂ within porous media has not yet been accomplished; however, the storage of other gases, e.g., CO₂ and CH₄, in geological reservoirs is a proven technology and therefore provide a technical basis for scoping studies. Note that H₂ has successfully been stored in underground salt caverns [38].

Saline aquifers and depleted gas reservoirs offer suitable environments for long-term H₂ storage. Depleted gas reservoirs have a proven ability to trap natural gas over geological timescales; therefore, these reservoirs offer significant potential for large-scale H₂ storage [33,35,39]. Confined gas reservoirs are often under-pressured after production and typically contain low to residual water saturations and any remaining in-situ CH₄. This in-situ CH₄ could be used to maintain gas pressures during injection and withdrawal cycles and save on initial investment costs [35]. Investment costs are expected to be lower in these reservoirs due to the existing geological knowledge and infrastructure in place. Depleted gas reservoirs are therefore highly promising for large-scale H₂ storage.

Within a gas storage environment, the fraction of reservoir gas that can be economically withdrawn during storage and recovery cycles is called the working gas (WG). The fraction of gas that remains within the reservoir, i.e., cushion gas (CG), provides pressure support for maintaining efficient WG injection and withdrawal rates, i.e., the reservoir WG capacity [35]. The WG is periodically injected and withdrawn from the reservoir at rates necessary for the required gas demand. CG will initially be injected into the reservoir to displace the in-situ reservoir

fluid and pressurise the reservoir. As WG is injected into the reservoir, the in-place CG will compress. During the withdrawal of the WG, the decompression and expansion of the CG will act as a driving force, contributing to the flow of the WG out of the reservoir. The volume of CG present within the reservoir directly affects the reservoir WG capacity and varies between 25% and 80% of the total reservoir gas volume [33, 40–42]. CG also represents a large upfront investment cost to a storage operation [43] and offers no economic return, other than its service for pressure support, as it is not economically feasible nor desirable to be extracted [44]. It is therefore important to determine and utilise optimal volumes and composition (i.e., type of gas) of CG specific for each storage reservoir operation.

Numerous studies have investigated the use of alternative CGs and their impact on withdrawal efficiency and recovery, including: CO₂ [45–47], CH₄ [48], and N₂ [49–51] in saline aquifers [45,48,49,52,53] and depleted gas reservoirs [54–57]. Oldenburg & Pan [46] estimated that approximately 12.5 million tons of CO₂ CG could be stored within a particular CH₄ storage reservoir, thereby saving $120 million of upfront costs. Tahmasebi et al. [50] estimated that using N₂ as a CG could save up to $2.6 billion USD in a separate case. The use of CO₂ as a CG can also potentially transform future CO₂ storage sites into dual-purpose reservoirs with long-term H₂ storage. Huang et al. [42] found that greater volumes of CG will lead to greater WG rates from the reservoir. Saeed & Jadhawar [48] studied the effects of CO₂, CH₄, and N₂ CG on H₂ storage in an aquifer formation and stated that CG type directly impacted reservoir WG recovery efficiencies (i.e., the ratio of withdrawn H₂ to the volume of H₂ injected) and H₂ purity. CO₂ increased reservoir capacity; however, N₂ and CH₄ exhibited a better H₂ recovery efficiency. Zhao et al. [45] studied the effects of CO₂, CH₄, and N₂ CG on H₂ storage and determined that CH₄ and N₂ were more effective at isolating H₂ at the top of the reservoir. The use of CO₂ CG increased brine densities, initiating density-driven convection and increasing H₂ dissolution into the aqueous phase [51]. Bahrami et al. [51] estimated a decrease in H₂ recovery efficiencies of approximately 5% due to N₂ CG mixing. He et al. [47] determined that the maximum reservoir threshold pressure has the most significant impact on H₂ WG capacity.

Mixing within a porous media occurs due to the combined effect of convective spreading (dispersion) and diffusion [58]. While diffusion is a slow process and may become more pronounced over extended timescales, its impact will decrease as concentration gradients diminish [59]. Diffusion is commonly neglected in reservoir modelling studies due to the known reduction of its effects by high pressures and tortuosity and the dominance of dispersion [60–64]. Mixing in relevant subsurface environments (i.e., with injection and withdrawal) will be primarily governed by dispersive effects, due to gas flows [59,62,65–67]. Dispersion is scale-dependant and increases over greater distances [68]. It is therefore difficult to translate laboratory results across to reservoir scales, as lab-based tests identify dispersion coefficients on the order of cm [59]. Tracer tests can be used to predict dispersion coefficients at field scales; however, the reliability of measurements reduces with increasing scale [69]. There is therefore great uncertainty regarding the appropriate dispersion coefficient to use in field-scale simulation studies.

In contrast to physical dispersion, numerical dispersion is a phenomenon associated with finite-difference methods and it results in the artificial mixing of fluids [70]. Numerical dispersion increases with increasing reservoir grid sizes, producing an artificially wide mixing zone [71]. Many large-scale reservoir simulation studies use coarse grid sizes to increase computational efficiency; therefore, numerical dispersion often overpredicts gas-phase mixing.

Practical experiences with H₂ storage in porous media have been limited to the storage of H₂ blends with other gases, such as CO₂ and CH₄ [8]. The Underground Sun Storage pilot [72] project stores a mixture of CH₄ (90%) and H₂ (10%) in a depleted gas reservoir in Gampern, Austria, and is the world's first H₂ test site exploring H₂ storage in sandstone reservoirs. Results demonstrated that H₂ storage in porous
media was possible without damaging the integrity of the reservoir and cap rock [8]. The project has since injected pure H₂; however, the results from a recent withdrawal phase have not yet been published.

Valuable lessons can also be learned from the storage of “town gas” (i.e., comprising 50–60% H₂, 15–20% CO₂+CO, and 10–20% CH₄ by volume) [73]. During town gas storage, increases in CH₄ volumes were recorded alongside a decrease in H₂ and CO₂ volumes, with a small reduction in reservoir pressure [34]. The cause of this phenomena has been explained via the Sabatier reaction in Equation (1), i.e., where methanogenic bacteria consumed the carbon from CO₂ and used the electrons from the H₂ to produce CH₄ [73].

$$4H_2 + CO_2 \rightarrow CH_4 + 2H_2O \quad (1)$$

The storage of CO₂ alongside H₂ can therefore have significant negative effects when methanogenic bacteria are present within the reservoir near the mixed gases. Because it is very challenging to control microbial populations in reservoirs, it is therefore important to consider operational methods that limit gas mixing.

Density differences between different gases residing in a reservoir separately (i.e., not mixed) allow them to remain segregated as they stratify within a reservoir due to gravity. Studies have reported that when the density contrast is large between H₂ and CG, the storage leads to more gas mixing [49,55,74]. That is, large density differences increase the effect of gravity override. Gravity override is the uncontrolled migration of a lighter fluid over a denser fluid, often influenced by dynamic factors such as gas volumes, fluid properties, and reservoir geometries. Macro-scale effects may include (i) an increase in surface area interface between gases, increasing mixing effects [68], (ii) unrecoverable pockets of H₂ far from the withdrawal wells [75,76] (iii) up-coning of CG into the withdrawal well [49,77–79]. Macro-scale heterogeneity (e.g., rock layering), can mitigate the impact of gravity override, as low vertical permeabilities prevent upward fluid migration [59,80]. Operational techniques can also mitigate gravity override, such as increasing WG injection and withdrawal rates [59,65–67,76,81]. Horizontal permeability is the main parameter controlling the height of up-coning. When horizontal permeabilities are high relative to vertical permeabilities, up-coning is reduced [82].

Multiple conceptual models are available for geological H₂ storage, each highlighting the role of reservoir geometry to restrict gas mixing. Early studies by Carden & Paterson [83] determined that the best shape of an aquifer would be if the aquifer’s height was equal to its diameter, giving the largest volume for the least outer surface area, thereby minimising diffusive losses out of the reservoir. Ma et al. [84] determined that increasing the reservoir thickness reduced gas mixing between CO₂ CG and CH₄ by enhancing pore space, thereby promoting natural segregation through buoyancy. Chai et al. [49] studied H₂ storage in a steeply dipping anticlinal aquifer using CO₂ and N₂ CG. The accumulation of buoyant H₂ at the crest of the formation reduced the surface area between gases and reduced mixing. These studies demonstrated strategies to leverage fluid properties and aquifer features to minimise mixing.

Ma et al. [84] also investigated mixing effects in synclinal and anticlinal structures in a CO₂ (CG) – CH₄ (WG) system. The mixing region in the synclinal structure was larger than in a horizontal reservoir and the mixing rate increased with increasing dip angle. Density differences between CO₂ and CH₄ caused the CH₄ to override, increasing the surface area of the CO₂–CH₄ interface, and thereby increasing mixing. The mixing region in the anticlinal structure was the smallest of all scenarios investigated and was reduced further by increasing the dip angle, which promoted gravitational segregation with a reduced gas-gas interface. These results were supported by Refs. [76,77,85], who suggested that reservoirs with steeply dipping anticlinal trap structures are ideal to reduce H₂ losses across the boundary of a trap structure. Bo et al. [86] determined that a steeper cap rock dip will improve the vertical displacement of H₂; however, the steeper cap rock dip will also lead to an increase in the withdrawal of connate CH₄.

These studies all demonstrated the importance of limiting the gas-gas interface surface area to reduce mixing. However, upon examination of Southern North Sea gas reservoir geometries, these conceptual models might not be best to limit gas mixing. The geometries of these hydrocarbon reservoirs are often laterally extensive with a relatively small reservoir thickness. The characteristic lateral lengths of Southern North Sea gas reservoirs have been collated and shown in Fig. 1. The characteristic lateral lengths of Southern North Sea gas reservoirs are shown to be at least 10× greater than their corresponding thicknesses. The gravity segregation of H₂ and CG with such formation geometries would expose a large gas interface surface area, and therefore increase mixing effects.

This work proposes a reservoir operational strategy to facilitate the dual storage of H₂ and CO₂ in a depleted gas reservoir, appropriate for laterally extensive reservoirs. This strategy was investigated by simulating the use of CO₂ as an alternative CG and exploring how mixing with H₂ WG can be minimised by taking advantage of reservoir geometry. Specifically, the CG and WG were kept separate through injections at opposing ends of a reservoir to reduce the surface area of the CG-WG interface. A capacity estimation was first conducted to assess the impact of H₂ and CO₂ quantities on reservoir WG capacity. The extent of gas mixing was then determined through analysing CO₂ and CH₄ withdrawal quantities. The reservoir geometry simulated does not depict a specific “real-world” storage site, but depicts the characteristics of laterally extensive reservoirs, which are commonly found in the Southern North Sea. Hence, this study’s general trends – rather than exact results – will support further research and development in H₂ storage projects. The findings from this study are anticipated to be widely useful in planning future long-term H₂ operations worldwide to support the global transition to Net-Zero.

## 2. Methodology

For this study, a 3D reservoir model was developed on CMG Builder [87]. The reservoir design and properties aimed to replicate a laterally extensive and thin gas reservoir found in the Southern North Sea [88] (see the properties detailed in Table 1). The reservoir was sealed with no-flow boundaries on all sides, i.e., representative of a compartmentalised gas field located in the Southern North Sea [89,90]. The model comprised 72 200 cells (100 in length x 38 in width and x 19 in depth). The reservoir was located at a sub-sea depth of 2 700 m at a uniform temperature of 95 °C, replicating conditions found in the Rough Gas Field [88]. The rock properties were assumed homogeneous and reflect common values used in reservoir simulation studies [48,52,74]. The water-gas contact was set to 50 m below the reservoir, located at 2 750 m in depth. The gas cap was made up of CH₄, representing a natural gas reservoir with 80% gas saturation [49]. Reservoir pressures were calculated from a hydrostatic pressure gradient of 0.1045 bar/m [91]. A justification of reservoir values is included in the Supplementary Material (SM).

The reservoir engineering software CMG-GEM [87] was used for this study. GEM is a commercially available finite-difference compositional simulator built on equation-of-state physics, often used within the energy industry to simulate large-scale reservoir systems. In this research, the Peng-Robinson cubic equation of state was used, which accurately simulates the properties of fluids and fluid mixtures under varying reservoir pressure and temperature conditions. The Peng-Robinson equation of state can describe vapor-liquid equilibria with precision when combined with appropriate mixing rules [92] and it has been used to simulate conventional hydrocarbon reservoirs [93], CCS [61], and most recently to model H₂ storage [52,65]. Gas viscosities were calculated using the Jossi, Stiel, and Thodos correlation [94]. This study utilised a two-phase model with the governing equations integrated into GEM-CMG software, as further described in Refs. [49,52,95,96]. The simulated densities and viscosities of H₂, CO₂, and CH₄ are available in Fig. S1 of the SM. This study describes all reservoir pressures in terms of the average field pressure, which were calculated by GEM-CMG.
<figure><img src="image_5.png" /><figcaption>Fig. 1. Southern North Sea gas reservoir geometries.</figcaption></figure>

<table><caption>**Table 1**
Reservoir properties.</caption><thead><tr><td>Property</td><td>Value</td></tr></thead><tbody><tr><td>Number of reservoir grid cells</td><td>100 x 38 x 19</td></tr><tr><td>Length (m)</td><td>8000</td></tr><tr><td>Width (m)</td><td>3000</td></tr><tr><td>Thickness (m)</td><td>45</td></tr><tr><td>Top depth (m)</td><td>2700</td></tr><tr><td>Top depth pressure (bar)</td><td>280</td></tr><tr><td>Temperature (°C)</td><td>95</td></tr><tr><td>Porosity (%)</td><td>20</td></tr><tr><td>Horizontal permeability (mD)</td><td>100</td></tr><tr><td>Vertical permeability (mD)</td><td>10</td></tr><tr><td>Gas saturation (%)</td><td>80</td></tr><tr><td>Gas cap composition</td><td>CH<sub>4</sub></td></tr><tr><td>Rock compressibility (1/kPa)</td><td>5.8e-7</td></tr></tbody></table>

## 2.1. Assumptions

This study concentrates on macro-scale fluid dynamics related to the density and viscosity variations among the different gases and their mixtures. Consequently, geochemical reactions and gas dissolution into reservoir brine were not simulated. Mixing within this study was approximated solely due to numerical dispersion. That is, diffusion and dispersion were not directly modelled. This approach enabled a computationally efficient methodology to approximate key mixing trends across injection/withdrawal conditions relevant to H₂ storage. As a trade-off, this approach did not provide reliable predictions of absolute mixing values. However, there are currently many uncertainties around mixing dynamics that inhibit improved predictions – primarily due to discrepancies in the use of dispersion coefficients. Consequently, many authors assume numerical dispersion is approximately equivalent to hydrodynamic dispersion and do not include a dispersion coefficient when simulating gas mixing in reservoir systems [46,49,54,57,70,90, 97]. In addition, there are compounding uncertainties from the interactions between gases with vastly different properties (e.g., supercritical CO₂ and gaseous H₂). Ongoing field studies on real H₂ storage scenarios are expected to provide clarity on which modelling approaches best capture these complicated mixing phenomena. Additional details on dissolution, diffusion, and dispersion are provided in the SM, where a sensitivity study was conducted to justify how numerical dispersion used in this study approximated key mixing trends from classical gas dispersion (further discussed in Section 4.6).

The effect of hysteresis and capillary pressure is known to be influential when considering a gas-water system. Capillary pressure will dictate gas-water displacement and hysteresis will lead to an increase in the gas-water transition zone length. Both mechanisms will affect the calculated reservoir storage capacity [98]. In this study, the reservoir model represents a closed reservoir system with a residual water

saturation, which is representative of a Southern North Sea gas field [88]. The effects of capillary pressure and hysteresis were therefore omitted, as no movable gas-water contact exists in such environments.

This study used a simple homogeneous, anisotropic model with vertical and horizontal permeabilities of 10 and 100 mD, respectively, and a porosity of 20%. This simple model was chosen to focus on the storage dynamics associated with various fluid properties at representative storage temperatures and pressures. Further discussion on heterogeneity is included in the SM.

Due to limited experimental data on H₂-water relative permeability [51] and with varying gas compositions (H₂, CO₂, and CH₄) and reservoir conditions modelled in this study, a generic relative permeability curve previously used in H₂ storage studies [55] was used (available in Fig. S2 of the SM).

## 2.2. Base-case simulation

The reservoir initially contained CH₄, with an initial average gas saturation of 0.8 and initial average reservoir pressure of 280 bar. Fig. 2 shows the reservoir depletion (Fig. 2a), CG injection (Fig. 2b), rest period (Fig. 2c), and cyclic injection and withdrawal of WG (Fig. 2d) from the base-case simulation (Simulation 1a-20CG-25WG). Fig. 2 also shows the base-case CH₄ depletion rate, CO₂ and H₂ CG injection rates, WG injection and withdrawal rates, and the average reservoir pressure evolution. The reservoir initially contained 25.6 Mt of CH₄. During depletion, the average pressures dropped from 280 to 50 bar, as approximately 21 Mt of CH₄ (82%) was withdrawn from three depletion wells over 7 years (see well placement in Fig. 3), leaving 4.6 Mt of CH₄ (18%) in place. This depletion strategy was applied to all simulations. For the injection process, no constraints on the maximum allowable bottom hole pressure (BHP) were applied. Instead, the maximum average reservoir pressures were maintained below the reservoir fracture pressure, estimated as 308 bar (i.e., 10% above the hydrostatic pressure). All wells had radii of 0.25 m, with perforations distributed evenly along their entire 45 m lengths.

While it is accepted that deeper well perforations into the formation will promote mixing throughout the reservoir depth [99], the only gas storage site in the Southern North Sea (i.e., the Rough Gas Field) is perforated throughout the reservoir. Because the gas-water contact within the Rough Gas Field is located below the reservoir and there are no-flow boundaries on all sides, this well perforation arrangement is standard practice [100]. Full-length perforations enhance well productivity and force CG laterally away from the wells in thin reservoirs.

After reservoir depletion (Fig. 2a), CG injection commenced (Fig. 2b). Pressures increased from 50 to 150 bar, as approximately 17 Mt of CO₂ and 0.5 Mt (i.e., 20 GWh) of H₂ was injected simultaneously from opposing ends of the reservoir. H₂ volumes were converted into GWh using the H₂ higher heating value. The conversion methodology is
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Reservoir Depletion (a), CG Injection (b), Rest Period (c), Cyclic Injection and Withdrawal of WG (d). Rates of CH₄ reservoir depletion (orange), CO₂ (purple) and H₂ CG injection (light blue), cyclic H₂ WG injection (green), H₂ WG withdrawal (dark blue), and average reservoir pressure (red dashed) during the base-case simulation (Simulation 1a-20CG-25WG). Simulation 1a-20CG-25WG injected 17 Mt of CO₂ and 0.5 Mt (20 GWh) of H₂ CG with a WG capacity of 0.63 Mt H₂ (25 GWh). Reservoir depletion is followed by CG injection, followed by a rest period and subsequent cyclic injection and withdrawal of WG for 10 cycles. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Reservoir simulation model showing well locations. (a) Three reservoir CH₄ depletion wells were spaced uniformly throughout the reservoir, (b) CO₂ and H₂ CG injection wells were located at opposite ends of the reservoir, and (c) H₂ WG wells were located in a similar position as the H₂ CG wells. The colour legend represents the reservoir thickness in meters. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

included in the SM. The injection rates for H₂ CG and CO₂ CG were fixed at 3 and 1.6 million m³/day, respectively, at standard conditions (i.e., 15 °C and 1 atm). CG injection rates were held constant and desired injection amounts were controlled by injection durations, as outlined in Table 2.

After the CG injection, reservoir pressures were then allowed to equalise during a shut-in period (Fig. 2c) before WG injection (Fig. 2d).

WG was injected and withdrawn from the same location as H₂ CG injection (Fig. 3c). A seasonal (annual) storage concept was applied. This concept could represent a scenario where H₂ is produced through electrolysed wind energy in the summer, when excess energy could be generated, and stored to supply a district heating system (e.g., a gas network) in the winter months, when the energy demand is higher. WG was injected for 3 months, followed by a 3-month shut-in period.
<table><caption>**Table 2**
Summary of cases simulated.</caption><caption>Reservoir Depletion: 50 and 100 bar sensitivity</caption><thead><tr><th colspan="4">CO<sub>2</sub> CG (Mt) Scenario</th><th colspan="2">H<sub>2</sub> CG</th><th rowspan="2">Target H<sub>2</sub> WG Quantities (GWh)</th></tr><tr><th>a</th><th>b</th><th>c</th><th>d</th><th>GWh</th><th>Mt</th></tr></thead><tbody><tr><td>17</td><td>35</td><td>52</td><td>70</td><td>5</td><td>0.13</td><td>5 10 15 20 25 30 32 35</td></tr><tr><td></td><td></td><td></td><td></td><td>10</td><td>0.25</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>15</td><td>0.38</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>20</td><td>0.5</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>25</td><td>0.63</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>30</td><td>0.76</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>35</td><td>0.89</td><td></td></tr></tbody></table>

Subsequently, the WG was extracted for 3 months, followed by another 3-month shut-in period. This injection and withdrawal pattern continued for 10 cycles over a 10-year period. During the withdrawal process, a minimum BHP of 5 bar was applied. If the BHP dropped below 5 bar, the withdrawal rate slowed to allow the pressure within the well to increase. Fig. 2 shows that the withdrawal rates did not match the injection rates until the 4th cycle. With each cycle, a fraction of the WG accumulated in the reservoir. This accumulation increased the reservoir pressure, which increased the WG withdrawal rates until the injection and withdrawal rates matched. The WG accumulation was considered when quantifying the total volume of CG. Average reservoir pressures fluctuated with WG injection and withdrawal (Fig. 2). However, once rates equalled after the 4th cycle, average pressures only increased incrementally, i.e., from 265 to 267 bar from the 5th to 10th cycle, respectively.

### 2.3. Capacity estimations and gas withdrawal purity

Capacity estimation methodology is based on work conducted by Heinemann et al. [101]. To assess the impact of H₂ and CO₂ CG quantities on reservoir WG capacity, numerous scenarios were simulated and are summarised in Table 2. During each scenario, the reservoir was depleted of CH₄ to a pressure of 50 bar. Reservoir conditions for each simulation are summarised in Table 1. There were four scenarios with varying quantities of CO₂ CG (i.e., 1a, 1b, 1c and 1d), each of which included different amounts of H₂ CG (Table 2). These scenarios were then simulated to evaluate whether the target WG capacities could be attained. After 10 cycles, the reservoir pressures and WG quantities were calculated. The reservoir WG capacity was calculated from the withdrawal rate attained at the 10th cycle, along with the average reservoir pressure. That is, if the desired withdrawal rate was not achieved by the 10th cycle – or the average pressure reached the fracture pressure (i.e., 308 bar) – then the simulation “failed”, and the results were not presented. Subsequently, CH₄ and CO₂ gas withdrawal volumes and gas mole fractions were calculated for each scenario to assess the impact of varying quantities of both H₂ and CO₂ CG on H₂ purity. A flow diagram demonstrating the capacity estimation methodology is included in the SM.

An additional sensitivity study with 100 bar depletion was conducted to investigate the influence of different reservoir depletion levels on WG capacities, CO₂ storage volumes, H₂ CG:WG ratios, and H₂ purity. This sensitivity scenario depleted the reservoir down to 100 bar, which reduced the CH₄ withdrawal from 21 Mt (82%) to 16 Mt (62%), and left 9.6 Mt of CH₄ within the reservoir. These simulations are summarised in Table 2.

Overall, a total of 448 scenarios were simulated in this study, providing a thorough investigation into the effects of CG variations on reservoir WG capacity and H₂ purity. Given the large number of simulated scenarios, a code was used to summarise of the sensitivities explored. For instance, Simulation 1a-20CG-20WG had a 50 bar depletion with 17 Mt of CO₂ CG, 20 GWh (0.5 Mt) of H₂ CG, and 20 GWh of H₂ WG. Simulation 2a-20CG-20WG followed the same conditions, but with

a 100 bar depletion (i.e., initial pressure of 100 bar, due to in-situ CH₄). Additional details on all simulations are provided in Figs. S4-S7 of the SM.

## 3. Results

### 3.1. Reservoir cross sections

CH₄, CO₂, and H₂ gas fraction distributions in reservoir cross sections after the first and tenth (i.e., last) withdrawal cycles are shown in Fig. 4.

### 3.2. Capacity estimation

The cumulative mass of H₂ WG withdrawn during one cycle, relative to the mass of injected H₂ CG with varying CO₂ CG masses is shown in Fig. 5a. The results show that an increase in CO₂ CG reduced the overall volume of H₂ WG withdrawn. Table 3 shows the maximum WG capacity with varying CO₂ and H₂ CG amounts. An increase in H₂ CG also increased the H₂ WG capacity. However, greater amounts of CO₂ CG required less H₂ CG for successful operation. Fig. 5b demonstrates the reservoir pressure differences from each scenario. These pressures were governed by the total volume of injected CG and WG. That is, initial pressures increased with greater CO₂ CG volumes and reached the limiting fracture pressure (i.e., 308 bar) with less H₂ CG. In most simulations, the WG withdrawal reached the greatest efficiency as reservoir pressures reached approximately 308 bar.

In addition to the core results, each pane in Fig. 5 includes overlain simplified analytical solutions to highlight the factors governing key trends. See the SM for the derivation and additional details on these analytical solutions. In Fig. 5c, the increasing H₂ WG with increasing H₂ CG can be explained using a scale analysis with a simplified 1D and steady approximation using Darcy’s Law and the Ideal Gas Law:

$$MGW = \frac{kAM_{H_2}RT_t}{V^2\mu L} \left( \sum n_{i,o} + n_{H_2,CG} \right)^2 \quad (2)$$

Where MWG represents the total WG mass withdrawn during an operation cycle; k is the reservoir permeability; A is the total surface area of all withdrawal wells; M<sub>wH2</sub> is the molecular weight of H₂; R is the ideal gas constant; T is the reservoir temperature; t is the total time of gas withdrawal; V is the reservoir volume accessible for the gases, i.e., V = V<sub>total</sub>φ(1 − S<sub>r</sub>), where V<sub>total</sub> is the total reservoir volume, φ is the porosity, and S<sub>r</sub> is the residual liquid saturation; μ is H₂ viscosity; L is a defined length scale within the reservoir that exhibited the characteristic pressure drop from average reservoir pressure to well pressure; Σ n<sub>i,o</sub> is this initial number of CH₄ and CO₂ moles in the system, n<sub>H₂,CG</sub> is the amount of H₂ CG moles. All values used in the analytical calculations were derived from the reservoir properties and are included in the SM; except L, which was unknown and used to calibrate model results. The analysis in Fig. 5c shows the relationship between increased CG and WG. The increase in CG results in higher reservoir pressures, which subsequently leads to higher flow rates into the well.

In Fig. 5d, the Ideal Gas Law was used to estimate the pressure response in the reservoir with additional H₂ CG. This analysis approximates the relationship between the change in gas moles within the reservoir and the change in reservoir pressure.

$$\Delta P = \frac{\Delta nRT}{V} \quad (3)$$

Where ΔP is the change in reservoir pressure and Δn is change in H₂ CG. In Fig. 5e, the decrease in H₂ WG capacity can be explained by the following relationship:

$$\Delta n_{wg} = - \Delta n_{cg} \quad (4)$$

Where Δn<sub>wG</sub> is a change in WG quantity; and Δn<sub>CG</sub> is a change in the H₂ CG quantity. The downslope in Fig. 5e shows that an increase in H₂ CG is
<figure><img src="image_8.png" /><figcaption>Fig. 4. Gas mole fraction distributions from the base-case simulation (Simulation 1a-20CG-25WG) in a 2D horizontal reservoir cross-section after the withdrawal phase of the (a) 1st and (b) 10th cycle. The gases mole fractions are shown, i.e., CH₄ (1a, 1b), CO₂ (2a,2b), and H₂ (3a,3b). Simulation 1a-20CG-25WG contained 17 Mt of CO₂ and 0.5 Mt (20 GWh) of H₂ CG with a WG capacity of 25 GWh of H₂ (0.63 Mt). CO₂ was injected at one side of the reservoir and H₂ is injected at the other. See well placements in Fig. 3.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Fig. 5. (a) WG capacities (b) and maximum average pressures during simulation runs 1a, 1b, 1c and 1d, with varying with CO₂ CG and H₂ CG. Note that (c, d) and (e, f) show simulations with low and high operating pressures relative to the reservoir fracture pressure, respectively. The coloured trendlines on graphs (c) and (d) represent the simulations where an increase in reservoir pressure, as a result of an increase in H₂ CG, leads to an increase in H₂ WG. The coloured trendlines on graphs (e) and (f) represent simulations where pressure does not increase with increasing CG, and leads to a reduction of H₂ WG in order to maintain pressures below the reservoir fracture pressure. The trends governing the key results in these two cases differ due to the pressure sensitivities, as given by the trendlines showing deviations from the ideal gas law (coloured lines on c and d) and a 1:1 M trade-off between H₂ CG and WG storage capacity (e). The simulation results are shown as coloured symbols. Simulation results that exceeded the fracture pressure, i.e., >308 bar in (f), or did not achieve the desired withdrawal rate by the 10th cycle were designated as “failed” and not shown. Note that all simulations were performed with 50 bar reservoir depletion and all WG capacities and maximum average pressures were calculated at the 10th cycle.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 6.** Gas mole fractions and total masses (kg) of withdrawn (a) CH₄ and (b) CO₂ over the 10-cycle period from the base-case simulation (Simulation 1a-20CG-25WG). Simulation 1a-20CG-25WG used 17 Mt of CO₂ CG, and 20 GWh (0.5 Mt) of H₂ CG with a WG capacity of 25 GWh (0.63 Mt).</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Fig. 7.** 50 bar reservoir depletion – (a) cumulative CO₂ and (b) cumulative CH₄ withdrawn during simulation runs 1a, 1b, 1c and 1d, with varying quantities of CO₂ and WG:CG ratios at the 10th cycle.</figcaption></figure>

inversely proportional to decrease in WG capacity.

The results from the analytical calculations show the slope of the line on Fig. 5d is governed by the increase in pressure because of the increasing H₂ CG. However, the Ideal Gas law underestimated the

<table><caption>**Table 3**
Maximum WG capacity with varying CG amounts at the 10th operational cycle.</caption><thead><tr><td>CO₂ CG (Mt)</td><td>Maximum WG Capacity (GWh)</td><td>H₂ CG (GWh)</td></tr></thead><tbody><tr><td>17</td><td>30</td><td>50</td></tr><tr><td>35</td><td>25</td><td>30</td></tr><tr><td>52</td><td>25</td><td>15</td></tr><tr><td>70</td><td>15</td><td>5</td></tr></tbody></table>

changes in pressure with increased H₂ CG in comparison to the simulated results, which used the Peng-Robinson Equation of State. This mismatch is because the Ideal Gas Law does not accurately describe density variations, especially of CO₂, from the simulations during high pressure conditions. However, the analysis overlain in Fig. 5d is still useful as the key pressure trends with increasing H₂ CG were reasonably approximated. Refer to the SM for the detailed derivation and additional commentary.

### 3.3. Gas mixing

To quantify the extent of gas mixing, the total masses of CO₂ and CH₄ withdrawn were calculated. The total masses and mole fractions of CH₄ and CO₂ withdrawn throughout the base-case simulation are shown in Fig. 6. This figure shows CH₄ mole fractions reached up to approximately 0.02 during each withdrawal phase where a cumulative 0.35 Mt of CH₄ was withdrawn after the 10th cycle. The CO₂ withdrawal mole fraction rate increased sharply from ~5 x 10⁻⁷ to 4 x 10⁻⁶ over three cycles (i.e., cycles at 2051 to 2053, respectively), with a cumulative withdrawal of 13 000 kg of CO₂ after the 10th cycle. However, this total CO₂ withdrawal is essentially negligible compared to the ~5.9 Mt of H₂ withdrawn over the same ten cycles.

The cumulative withdrawal of CO₂ and CH₄ relative to the H₂ WG:CG ratio is shown in Fig. 7. This figure shows, with an increased H₂ CG:WG ratio, the withdrawal of CO₂ (Fig. 7a) and CH₄ (Fig. 7b) was reduced in all simulations. An increase in CO₂ CG volumes led to increased CO₂ withdrawal. For example, with 17 Mt CO₂ CG, negligible CO₂ was withdrawn from all H₂ CG:WG ratios. During the 35, 52, and 70 Mt CO₂
CG simulations, the maximum cumulative CO₂ withdrawn was 0.21, 3.03, and 5.6 Mt, respectively, which all occurred at low H₂ CG:WG ratios. An increase in CO₂ CG generally increased CH₄ withdrawal, where the 17 and 35 Mt CO₂ CG simulations led to 0.75 and 1.46 Mt cumulative CH₄ withdrawal, respectively. However, the cumulative CH₄ withdrawn was greater in the 52 than the 70 Mt CO₂ CG scenario, where approximately 2 and 1.7 Mt CH₄ was withdrawn, respectively.

### 3.4. Reservoir depletion sensitivity

The key results from the 100 bar reservoir depletion sensitivity study are shown in Figs. 8 and 9 and Table 4. The average pressure dropped from 280 to 100 bar, where approximately 16.2 Mt of CH₄ was withdrawn from the reservoir over 7 years. This depletion methodology was used in simulation runs 2a, 2b, 2c, and 2d. Fig. 8a shows 25 GWh H₂ WG capacity was achieved with both 17 and 35 Mt of CO₂ CG and ~10 GWh of H₂ CG (H₂ CG:WG = 0.41). During the 17 Mt CO₂ CG scenario, pressure was maintained below the fracture pressure (i.e., 308 bar) when H₂ CG volumes were increased. 15 GWh H₂ WG capacity was achieved during the 52 Mt CO₂ CG scenario with 5 GWh of H₂ CG (H₂ CG:WG = 0.34). Increased CO₂ CG reduced the reservoir H₂ WG, as the reservoir capacity for H₂ withdrawal decreased. The same simplified analytical solution from Fig. 5e is overlain on Fig. 8a to highlight the factors governing key trends (Equation (4)).

A comparison between H₂ WG capacities for 50 bar depletion (Fig. 5a) and 100 bar depletion (Fig. 8a) at 5 GWh of H₂ CG shows that increased initial CH₄ (i.e., from minimal depletion) increased the reservoir H₂ WG capacity when a relatively small amount of H₂ CG was used. That is, with 50 bar depletion and 5 GWh of H₂ CG, the maximum H₂ WG capacities were 5, 10, and 15 GWh with 17, 35, and 52 Mt CO₂ CG, respectively.

<figure><img src="image_12.png" /><figcaption>Fig. 9. 100 bar Reservoir depletion sensitivity – (a) cumulative withdrawn CO₂ and (b) CH₄ during depletion sensitivity analysis during simulation runs 2a, 2b, 2c and 2d with varying quantities of CO₂ CG, and H₂ WG:CG ratios at the 10th cycle.</figcaption></figure>

Conversely, with 100 bar depletion, the maximum H₂ WG increased to 10, 15, and 20 GWh under the same 17, 35, and 53 Mt CO₂ CG simulations, respectively. In other words, a CH₄ depletion change from 50 to 100 bar resulted in 5 GWh increases in H₂ WG capacities in all simulations.

The cumulative withdrawal of CO₂ and CH₄ relative to the H₂ WG:CG ratio from 100 bar depletion sensitivity simulation runs (2a, 2b, 2c and 2d) and varying amounts of CO₂ CG (i.e., 17, 35, and 52 Mt) is shown in Fig. 9. Generally, CO₂ withdrawal was low in all simulations and reduced with increasing H₂ CG:WG. For example, negligible CO₂ was withdrawn in the 17 Mt CO₂ CG scenario. During the 35 Mt CO₂ CG scenario, the most CO₂ (i.e., ~0.05 Mt) was withdrawn at the lowest H₂ CG:WG = 0.25. CO₂ withdrawal was greatest (i.e., 0.35 Mt) during the 52 Mt CO₂ CG scenario. Compared to 50 bar depletion simulations (Fig. 7), Fig. 9 indicates that an increase in initial CH₄ (i.e., due to minimal depletion) increases both CO₂ and CH₄ withdrawal. In all simulations, CH₄ withdrawal (i) decreased with increasing H₂ CG and (ii) increased with increasing CO₂ CG. That is, the maximum CH₄ withdrawn during the 17, 35, and 52 Mt CO₂ CG simulations with 100 bar depletion were 1.57, 2.90, and 2.91 Mt, respectively.

### 4. Discussion

The use of an alternative CG, such as CO₂, during the underground storage of H₂ presents a practical operational approach to save on investment costs and promote CO₂ storage. However, gas mixing can degrade the quality of withdrawn H₂, leading to increased separation costs post-withdrawal. Recent studies have predominantly examined the vertical displacement of H₂ and alternative CG, allowing density differences between gases to facilitate their natural segregation via gravity. In laterally extensive reservoirs, such as those found in the Southern North Sea, vertical gas segregation can increase gas mixing effects due to a large contact surface area between gases. This study suggests an alternative operational approach to minimise this contact area. Injecting CG and WG at opposite ends of the reservoir would result in a horizontal CG, respectively.

<figure><img src="image_13.png" /><figcaption>Fig. 8. 100 bar reservoir depletion sensitivity – (a) WG capacities and (b) maximum average reservoir pressures during simulation runs 2a, 2b, 2c and 2d, with CO₂ CG and H₂ CG. WG capacities and maximum average pressures are calculated at the 10th cycle. The results of simulations that exceeded the fracture pressure i.e., >308 bar in (b), or did not achieve the desired withdrawal rate by the 10th cycle were designated as “failed” and not shown. The coloured trendlines (a) represent results obtained from analytical calculations highlighting the governing trends, as indicated by the equation (a).</figcaption></figure>
<table><caption>**Table 4**
Summary of results.</caption><thead><tr><th colspan="2">Optimum Scenario</th><th colspan="3">CG Requirements</th><th colspan="2">Gas Withdrawal</th></tr></thead><tbody><tr><td rowspan="2">CO<sub>2</sub> CG</td><td>Simulation run</td><td>Max WG (GWh)</td><td>H<sub>2</sub> CG (GWh)</td><td>CG:WG ratios</td><td>CO<sub>2</sub> prod (Mt)</td><td>CH<sub>4</sub> prod (Mt)</td></tr><tr><td>Base-case</td><td>30</td><td>49</td><td>1.6</td><td>1.4x10<sup>-5</sup></td><td>0.38</td></tr><tr><td rowspan="2">17</td><td>Sensitivity</td><td>25</td><td>10–30</td><td>0.4–1.2</td><td>1.5x10<sup>-4</sup>–1x10<sup>-4</sup></td><td>1.32–1.2</td></tr><tr><td>Base-case</td><td>25</td><td>30–35</td><td>1.2–1.4</td><td>0.02–0.01</td><td>0.52–0.43</td></tr><tr><td rowspan="2">35</td><td>Sensitivity</td><td>25</td><td>10–15</td><td>0.4–0.6</td><td>0.04–0.02</td><td>2.6–2.08</td></tr><tr><td>Base-case</td><td>25</td><td>15</td><td>0.6</td><td>2.02</td><td>1.93</td></tr><tr><td rowspan="2">52</td><td>Sensitivity</td><td>15</td><td>5</td><td>0.3</td><td>0.08</td><td>2.0</td></tr><tr><td>Base-case</td><td>15</td><td>5–10</td><td>0.3–0.7</td><td>5.63–3.89</td><td>1.68–1.86</td></tr><tr><td rowspan="2">70</td><td>Sensitivity</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr></tbody></table>

gas displacement, reducing the contact surface area and mitigate gas mixing.

### 4.1. Gravity override

Fig. 4 demonstrates the migration of various gases, primarily due to density differences [84]. A layer of residual CH₄ forms a boundary between the CO₂ CG and H₂ within the reservoir. As shown in Fig. 4, the effects of gravity override increased over multiple injection and withdrawal cycles. Following the initial operational cycle, H₂ (lightest) settled above CH₄ (denser), and CH₄ over CO₂ (densest). By the 10th cycle, gravity override intensified as pressure gradients pushed CO₂ towards the withdrawal wells, beneath CH₄ and H₂. A layer of H₂ migrated towards the CO₂ withdrawal well at the top of the reservoir.

### 4.2. Capacity

The primary goal of a reservoir storage operation is to maximise the deliverability and WG capacity. Specific WG capacity will depend on the economics of the storage operation; however, higher rates and volumes of withdrawal are typically desired, as gas storage sites often have short time windows to supply the WG during peak seasonal periods. As demonstrated by Fig. 2, a portion of H₂ WG accumulates within the reservoir after each successive cycle. As a result, WG rates increased because of increased reservoir pressures. These results are consistent with similar studies [45,48,52,59]. This study aligns with findings from Heinemann et al. [52], who showed that increasing H₂ CG amounts resulted in greater WG capacity. This increase in pressure led to a greater pressure driving force and H₂ density, resulting in increased withdrawal rates (Fig. 5a and c). However, WG capacity is limited by the maximum reservoir fracture pressure. Once the reservoir pressure surpasses the maximum fracture pressure of 308 bar, any further increase in H₂ CG necessitates an equal reduction in WG to keep the reservoir pressure below the fracture pressure (see Fig. 5e and Equation (4)).

Using CO₂ as a CG was shown to be an effective replacement for H₂ CG. By increasing CO₂ CG, less H₂ CG was required, thus substituting costly H₂ CG with more economical CO₂. This approach therefore cut costs and aids CO₂ storage targets. However, there is a trade-off between the CO₂ storage volumes and the WG capacity, as an increase in stored CO₂ will decrease the H₂ WG capacity and deteriorate WG quality due to CO₂ and H₂ gas mixing. WG injection and withdrawal in a compartmentalised and closed reservoir system are facilitated by the compression and decompression of the CG. Under reservoir conditions, the specific volume of H₂ undergoes a more pronounced change compared to CO₂ and CH₄. Over relevant injection pressures, H₂ is more compressible than CO₂, thereby allowing more WG into the reservoir for a given pressure increase, ensuring reservoir pressures are kept below the maximum fracture pressure (Fig. 5f). Gas withdrawal is driven by drawdown, i.e., the pressure difference between the withdrawal well and the reservoir. Consequently, withdrawal rates exhibit their highest levels when reservoir pressures are maximised. Additionally, withdrawal rates are influenced by the decompression of CG. At these reservoir conditions, because H₂ is more compressible to CO₂, the H₂ is

more efficiently withdrawn from the reservoir. Operators must therefore evaluate the storage operation priorities, considering both economic factors and the specific objectives of the storage operation.

### 4.3. Effect of CG on purity

Alternative CG mixing within large-scale H₂ storage systems will deteriorate H₂ purity and impact the H₂ uses after storage. For example, H₂ purity is paramount when used in fuel cells, as they require high-purity H₂ to avoid issues like catalyst poisoning and performance degradation [102]. ISO 14687 [103] states that H₂ intended for fuel cells cannot have more than 2 and 100 µmol/mol of CO₂ and CH₄ impurities, respectively. Overall, a H₂ purity of 99.97% is required for safe and efficient use within a fuel cell [104]. It is therefore unlikely that H₂ stored in geological reservoirs will be used for such applications without additional purification.

When observing CO₂ withdrawal (Fig. 6b), the breakthrough of CO₂ leads to a sharp increase in CO₂ withdrawal due to gas mixing effects. While the initial CO₂ mole fraction of the withdrawn gas is initially negligible, the sharp rise in CO₂ contamination breakthrough (i.e., up to a mole fraction of $4x10^{-6}$ at the 10th cycle) could eventually lead to the significant deterioration in H₂ purity over time. This increasing contamination may govern the reservoir operational lifetime and should be investigated further.

Saeed & Jadhawar [48] compared the effect of CO₂, CH₄, and N₂ CG on WG purity. They determined that H₂ purity was dictated by the presence of CG. Consistent with this study, a greater proportion of H₂ CG will increase WG purity. The results show that H₂ CG is an important component controlling WG purity, where an increase in a H₂ CG:WG ratio reduced the mass of withdrawn CO₂ and CH₄. This improved H₂ purity is because the H₂ CG forms a separation layer between the CO₂, CH₄, and H₂ WG resulting in negligible CO₂ withdrawal during most simulations and limiting CH₄ withdrawal.

The amount of CO₂ CG in the reservoir directly corresponded to the amount of CO₂ withdrawn. That is, larger volumes of CO₂ in the reservoir occupied regions nearer to the withdrawal wells, and thereby increased CO₂ contamination. To counteract this inefficiency, more H₂ CG would be needed to provide the necessary separation between stored CO₂ and WG. Furthermore, an increase in CO₂ CG also resulted in increased CH₄ withdrawal, as increased CO₂ CG in the reservoir compressed the CH₄ towards the withdrawal wells. Therefore, while H₂ CG may require significant capital investments, it might provide important benefits in improving H₂ purity. The inclusion of a H₂ CG layer must be considered in planning H₂ storage, and the purity benefits it offers must be balanced against investment costs.

### 4.4. Sensitivity analysis

Gas reservoir depletion levels vary depending on economic considerations, reservoir infrastructure and characteristics, and global energy trends. The results (Fig. 8) show that simulations with higher remaining CH₄, i.e., from minimal reservoir depletion, required less H₂ CG to achieve maximum WG capacities, as the remaining CH₄ effectively acted
as natural CG. The use of CH₄ CG can therefore effectively replace H₂ CG. However, with greater volumes of CH₄ in place, initial reservoir pressures were higher, which limited the CO₂ storage potential of the reservoir, as the total gas storage was governed by the reservoir fracture pressure. These are key trade-offs between CH₄ CG and CO₂ storage potential.

Zhao et al. [45] compared the effect of CO₂, CH₄, and N₂ CG on WG withdrawal rates. They determined that CH₄ and N₂ produced more favourable withdrawal rates in comparison to CO₂. In contrast, this study demonstrated an increase in H₂ WG rates when using CO₂ CG, which is consistent with results from Saeed & Jadhawar [48]. This difference is due to the effect of CO₂ dissolution, which resulted in the lowering of reservoir pressures and subsequent WG rates [45]. Like Saeed & Jadhawar [48], the results here show that CO₂ CG led to greater WG capacity compared to CH₄ CG. Similarly with CO₂, H₂ is more compressible than CH₄ and undergoes a more substantial decompression effect, driving WG withdrawal more efficiently with increasing H₂ CG (i.e., with less CH₄ CG). Reservoir depletion levels also significantly affected the quality of withdrawn H₂. The most noticeable change is the significant reduction of CO₂ contamination with decreased depletion. That is, increased CH₄ within the system acted as a buffer, preventing the migration of CO₂ towards the withdrawal well, limiting CO₂–H₂ mixing. However, CH₄ mixing increased with decreased depletion, as an increase in CH₄ saturation significantly increased the volume of withdrawn CH₄. These findings indicate that, by minimising depletion, there is a notable decrease in CO₂ CG withdrawal; albeit, the trade-off is that higher volumes of CH₄ are generated. The end-use of H₂ is critical in determining the mixing limits with alternative CGs. If H₂ is intended to supplement CH₄, e.g., as H₂-enriched gaseous fuel for heating and power uses, then a certain degree of mixing with CH₄ may be permissible. On the other hand, extensive mixing of H₂ and CO₂ will almost certainly make H₂ unsuitable for fuel cells, degrade its heating value, reduce its overall usability, and impact the CO₂ storage capacity of the reservoir. It is therefore crucial to limit the mixing of H₂ and CO₂ within the reservoir, as CO₂ mixing could govern the reservoir operational lifetime. Further investigations into reservoir operations, such as well placement, should focus to reduce/postpone CO₂ breakthrough.

### 4.5. Implications on biological reactions

This study did not investigate the impact of biological reactions on H₂ purity, but instead investigated a strategy to keep both gases separate and limit CO₂ – H₂ mixing. Through the reduction of mixing and CO₂ – H₂ contact surface area, the effect biological reactions could be reduced, making CO₂ a viable option for use as an alternative CG. Future research should focus on how reduced CO₂ – H₂ mixing limit biological activity.

### 4.6. Key Recommendations

Gas mixing was solely due to numerical dispersion in this study. A sensitivity study was therefore conducted on the effect of dispersion during the base-case simulation run (Simulation 1a-20CG-25WG). Results showed that a dispersion coefficient from 0 to 10 m had little effect on the mixing zone width and CH₄ withdrawal. However, the mixing increased with dispersion values greater than 10 m, and the dispersion effects dominated over numerical dispersion effects when such high dispersion values were used. Although gas mixing increased with these high dispersion values, the gas withdrawal trends (i) over time and (ii) between select simulations matched those observed with only numerical dispersion (see results in Figs. S8-S11 of the SM). Therefore, while gas mixing was greatest with the highest dispersion values, the key mixing sensitivities to storage conditions were consistent with those observed with only numerical dispersion. This comparison shows that numerical dispersion alone is a reasonable predictor of gas mixing sensitivities to the storage conditions investigated in this study. Estimating meaningful dispersion values at reservoir scales is complicated and warrants further

research.

## 5. Conclusion

Depleted gas fields, such as the ones in the Southern North Sea, offer a dual-purpose environment in which CO₂ can be stored permanently as an alternative CG and H₂ can be stored to supply seasonal demand. However, CO₂ – H₂ gas mixing will degrade the quality of the WG. This effect will likely be amplified within laterally extensive reservoirs, where the contact surface area between gases could be very large. This study proposes an alternative storage strategy where H₂ and CO₂ are injected at opposite ends of the reservoir, maintaining separation through a horizontal displacement with a reduced contact surface area.

The type and quantity of CG directly influenced the reservoir WG capacity and quality of withdrawn H₂. CO₂ CG was demonstrated to be an effective replacement for H₂ CG; that is, by increasing CO₂ CG amounts, less H₂ CG was required. However, operators must evaluate the storage operation priorities, as there is a trade-off between the CO₂ storage volumes and the WG capacity.

The effects of gravity override are shown to increase over multiple injection and withdrawal cycles, increasing the surface area between the gases, and in turn amplifying the mixing effects. H₂ quality decreased with increased volumes of CO₂ CG. However, negligible quantities of CO₂ were withdrawn during most simulations where a layer of H₂ CG was present.

This alternative strategy therefore ensures CO₂ can be effectively separated from the H₂ to prevent mixing. H₂ storage can effectively be conducted in reservoirs with varying depletion levels, i.e. varying quantities of in-situ CH₄. Storage in reservoirs with reduced depletion levels (i.e., with more CH₄) increased CH₄ – H₂ mixing and reduced the WG capacity of the reservoir. However, greater volumes of CH₄ in the system will provide a separation layer between CO₂ and H₂, which will reduce CO₂ – H₂ mixing.

### CRediT authorship contribution statement

**Harri A. Williams:** Writing – original draft, Visualization, Validation, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Niklas Heinemann:** Writing – review & editing, Visualization, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Ian L. Molnar:** Writing – review & editing, Validation, Supervision, Resources, Methodology, Data curation, Conceptualization. **Fernanda de Mesquita L Veloso:** Methodology, Conceptualization. **Toni Gladding:** Writing – review & editing, Supervision, Project administration. **Tarek L. Rashwan:** Writing – review & editing, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgment

NH is funded by the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under grant agreement No 101006632 and the Net Zero Technology Centre. We gratefully acknowledge funding from the Royal Society (RG\R2\232528) and from The Open University through Engineering & Innovation Research Funding and the Open Societal Challenges Programme in support of the SPLICE challenge.
# Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijhydene.2024.12.371.

## References

[1] The Paris Agreement | UNFCCC. https://unfccc.int/process-and-meetings/the-p-aris-agreement/the-paris-agreement. [Accessed 7 October 2022].

[2] Bruckner T, Bashmakov I.A., Mulugetta Y., Chum H., De la Vega Navarro A., Edmonds J., Faaij A., Fungtammasan B., Garg A., Hertwich E., Honnery D., Infield D., Kainuma M., Khennas S., Kim S., Nimir H.B., Riahi K., Strachan N., Wiser R., & Zhang X. (2014). Chapter 7 - Energy systems. Climate Change 2014: Mitigation of Climate Change. IPCC Working Group III Contribution to AR5. Cambridge University Press.

[3] Kriegler E, Weyant JP, Blanford GJ, Krey V, Clarke L, Edmonds J, Fawcett A, Luderer G, Riahi K, Richels R, Rose SK, Tavoni M, van Vuuren DP. The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies. Clim Change 2014;123: 353–67. https://doi.org/10.1007/s10584-013-0953-7.

[4] BEIS. Net Zero strategy: build back greener. GOVUK. 2021. p. 368.

[5] Eveloy V, Gebreegziabher T. Excess electricity and power-to-gas storage potential in the future renewable-based power generation sector in the United Arab Emirates. Energy 2019;166:426–50. https://doi.org/10.1016/J.ENERGY.2018.10.088.

[6] Gutiérrez-Martín F, Rodríguez-Antón LM. Power-to-SNG technology for energy storage at large scales. Int J Hydrogen Energy 2016;41:19290–303. https://doi.org/10.1016/J.IJHYDENE.2016.07.097.

[7] Lyseng B, Niet T, English, Keller V, Palmer-Wilson K, Robertson B, Rowe A, Wild P. System-level power-to-gas energy storage for high penetrations of variable renewables. Int J Hydrogen Energy 2018;43:1966–79. https://doi.org/10.1016/J.IJHYDENE.2017.11.162.

[8] Jahanbakhsh A, Louis Potapov-Crighton A, Mosallanezhad A, Tohidi Kaloorazi N, Maroto-Valer MM. Underground hydrogen storage: a UK perspective. Renew Sustain Energy Rev 2024;189:141001. https://doi.org/10.1016/J.RSER.2023.114001.

[9] Clark WW, Rifkin J. A green hydrogen economy. Energy Pol 2006;34:2630–9. https://doi.org/10.1016/J.ENPOL.2005.06.024.

[10] Halder P, Babaie M, Salek F, Haque N, Savage R, Stevanovic S, Bodisco TA, Zare A. Advancements in hydrogen production, storage, distribution and refuelling for a sustainable transport sector: hydrogen fuel cell vehicles. Int J Hydrogen Energy 2024;52:973–1004. https://doi.org/10.1016/J.IJHYDENE.2023.07.204.

[11] Chiara Massaro M, Pramotton S, Marocco P, Monteverde AHA, Santarelli M. Optimal design of a hydrogen-powered fuel cell system for aircraft applications. Energy Convers Manag 2024;306:118266. https://doi.org/10.1016/J.ENCONMAN.2024.118266.

[12] Ishimoto Y, Wulf C, Schonhoff A, Kuckshinrichs W. Life cycle costing approaches of fuel cell and hydrogen systems: a literature review. Int J Hydrogen Energy 2024;54:361–74. https://doi.org/10.1016/J.IJHYDENE.2023.04.035.

[13] Cunanan C, Tran MK, Lee Y, Kwok S, Leung V, Fowler M. A review of heavy-duty vehicle powertrain technologies: diesel engine vehicles, battery electric vehicles, and hydrogen fuel cell electric vehicles. Cleanroom Technol 2021;3:474–89. https://doi.org/10.3390/CLEANTECHNOL3020028.

[14] Kamran M, Turzyński M. Exploring hydrogen energy systems: a comprehensive review of technologies, applications, prevailing trends, and associated challenges. J Energy Storage 2024;96:112601. https://doi.org/10.1016/J.EST.2024.112601.

[15] Ishaq H, Crawford C. Review of ammonia production and utilization: enabling clean energy transition and net-zero climate targets. Energy Convers Manag 2024;300:117869. https://doi.org/10.1016/J.ENCONMAN.2023.117869.

[16] Habib MA, Abdulrahman GAQ, Alquality ABS, Qasem NAA. Hydrogen combustion, production, and applications: a review. Alex Eng J 2024;100: 182–207. https://doi.org/10.1016/J.AEJ.2024.05.030.

[17] Zhang L, Jia C, Bai F, Wang W, An S, Zhao K, Li Z, Li J, Sun H. A comprehensive review of the promising clean energy carrier: hydrogen production, transportation, storage, and utilization (HPTSU) technologies. Fuel 2024;355: 129455. https://doi.org/10.1016/J.FUEL.2023.129455.

[18] Hellerschmied C, Schritter J, Waldmann N, Zaduryan AB, Rachbauer L, Scherr KE, Andiappan A, Bauer S, Pichler M, Loibner AP. Hydrogen storage and geo- methanation in a depleted underground hydrocarbon reservoir. Nat Energy 2024; 9 (9): 333–344. 3 2024. doi:10.1038/s41560-024-01458-1.

[19] Rusmanis D, O'Shea R, Wall DM, Murphy JD. Biological hydrogen methanation systems – an overview of design and efficiency. Bioengineered 2019;10:604–34. https://doi.org/10.1080/21655979.2019.1684607.

[20] Burkhardt M, Busch G. Methanation of hydrogen and carbon dioxide. Appl Energy 2013;111:74–9. https://doi.org/10.1016/j.APENERGY.2013.04.080.

[21] Li L, Lin J, Wu N, Xie S, Meng C, Zheng Y, Wang X, Zhao Y. Review and outlook on the international renewable energy development. Energy and Built Environment 2022;3:139–57. https://doi.org/10.1016/J.ENBENV.2020.12.002.

[22] Midilli A, Kucuk H, Topal ME, Akbulut U, Dincer I. A comprehensive review on hydrogen production from coal gasification: challenges and Opportunities. Int J Hydrogen Energy 2021;46:25385–412. https://doi.org/10.1016/J.IJHYDENE.2021.05.088.

[23] Magliano A., Perez Carrera C., Pappalardo C.M., Guida D., Berardi V.P. A comprehensive literature review on hydrogen tanks: storage, safety, and structural integrity. Appl Sci 2024;14:9348. Page 9348 2024;14. doi: 10.3390/APP14209348.

[24] Gahleitner G. Hydrogen from renewable electricity: an international review of power-to-gas pilot plants for stationary applications. Int J Hydrogen Energy 2013; 38:2039–61. https://doi.org/10.1016/J.IJHYDENE.2012.12.010.

[25] Ajanovic A, Haas R. On the long-term prospects of power-to-gas technologies. Wiley Interdiscip Rev Energy Environ 2019;8. https://doi.org/10.1002/WENE.318.

[26] Mazloomi K, Gomes C. Hydrogen as an energy carrier: prospects and challenges. Renew Sustain Energy Rev 2012;16:3024–33. https://doi.org/10.1016/J.RSER.2012.02.028.

[27] Barelli L, Bidini G, Gallorini F, Servili S. Hydrogen production through sorption-enhanced steam methane reforming and membrane technology: a review. Energy 2008;33:554–70. https://doi.org/10.1016/j.ENERGY.2007.10.018.

[28] Voldsund M, Jordal K, Anantharaman R. Hydrogen production with CO2 capture. Int J Hydrogen Energy 2016;41:4969–92. https://doi.org/10.1016/J.IJHYDENE.2016.01.009.

[29] Luderer G, Vrontisi Z, Bertram C, Edelenbosch OY, Pietzcker RC, Rogelj J, De Boer HS, Drouet L, Emmerling J, Fricko O, Fujimori S, Havlík P, Iyer G, Keramidas K, Kitous A, Pehl M, Krey V, Riahi K, Saveyn B, Tavoni M, Van Vuuren DP, Kriegler E. Residual fossil CO2 emissions in 1.5–2 °C pathways. Nat Clim Change 2018;8(8):626–33. https://doi.org/10.1038/s41558-018-0198-6.

[30] IRENA. World Energy Transitions Outlook: 1.5 °C Pathway. International Renewable Energy Agency, Abu Dhabi; 2021.

[31] Oni BA, Bade SO, Sanni SE, Orodu OD. Underground hydrogen storage in salt caverns: recent advances, modeling approaches, barriers, and future outlook. J Energy Storage 2024;107:114951. https://doi.org/10.1016/J.EST.2024.114951.

[32] Masoudi M, Hassanpouryouzband A, Hellevang H, Haszeldine RS. Lined rock caverns: a hydrogen storage solution. J Energy Storage 2024;84:110927. https://doi.org/10.1016/J.EST.2024.110927.

[33] Amid A, Mignard D, Wilkinson M. Seasonal storage of hydrogen in a depleted natural gas reservoir. Int J Hydrogen Energy 2016;41:5549–58. https://doi.org/10.1016/J.IJHYDENE.2016.02.036.

[34] Panfilov M. Underground and pipeline hydrogen storage. Compendium of Hydrogen Energy 2016:91–115. https://doi.org/10.1016/B978-1-78242-362-1/00004-3.

[35] Heinemann N, Alcalde J, Miocic JM, Hangx SJT, Kallmeyer J, Ostertag-Henning C, Hassanpouryouzband A, Thays EM, Strobel GJ, Schmidt-Hattenberger C, Edlmann K, Wilkinson M, Bentham M, Stuart Haszeldine R, Carbonell R. Rudloff A. Enabling large-scale hydrogen storage in porous media – the scientific challenges. Energy Environ Sci 2021;14:853–64. https://doi.org/10.1039/D0EE03536J.

[36] Heinemann N, Booth MG, Haszeldine RS, Wilkinson M, Scafidi J, Edlmann K. Hydrogen storage in porous geological formations – onshore play opportunities in the midland valley (Scotland, UK). Int J Hydrogen Energy 2018;43:20861–74. https://doi.org/10.1016/J.IJHYDENE.2018.09.149.

[37] Olabi AG, bahri A saleh, Abdelghafar AA, Baroutaji A, Sayed ET, Alami AH, Rezk H, Abdelkareem MA. Large-vscale hydrogen production and storage technologies: current status and future directions. Int J Hydrogen Energy 2021; 46:23498–528. https://doi.org/10.1016/J.IJHYDENE.2020.10.110.

[38] Shahriar MF, Khanal A, Khan MI, Pandey R. Current status of underground hydrogen storage: perspective from storage loss, infrastructure, economic aspects, and hydrogen economy targets. J Energy Storage 2024;97:112773. https://doi.org/10.1016/J.EST.2024.112773.

[39] Lysyv M, Fernø M, Ersland G. Seasonal hydrogen storage in a depleted oil and gas field. Int J Hydrogen Energy 2021;46:25160–74. https://doi.org/10.1016/J.IJHYDENE.2021.05.030.

[40] Misra BR, Foh SE, Berry RM, Labaue F. The use of inert base gas in underground natural gas storage. SPE reprint series. 1988. p. 162–7. https://doi.org/10.2118/17741-MS.

[41] Sadeghi S, Sedaee B. Mechanistic simulation of cushion gas and working gas mixing during underground natural gas storage. J Energy Storage 2022;46: 103885. https://doi.org/10.1016/J.EST.2021.103885.

[42] Huang T, Moridis GJ, Blasingame TA, Abdulkader AM, Yan B. Compositional reservoir simulation of underground hydrogen storage in depleted gas reservoirs. Int J Hydrogen Energy 2023;48:36035–50. https://doi.org/10.1016/J.IJHYDENE.2023.05.355.

[43] Talukdar M, Blum P, Heinemann N, Miocic J. Techno-economic analysis of underground hydrogen storage in Europe. iScience 2024;27:108771. https://doi.org/10.1016/J.ISCI.2023.108771.

[44] Hassanpouryouzband A, Joonaki E, Edlmann K, Haszeldine RS. Offshore geological storage of hydrogen: is this our best option to achieve net-zero? ACS Energy Lett 2021;6:2181–6. https://doi.org/10.1021/ACSENERGYLETT.1C00845_SUPPL_FILE/NZ1C00845_S1_002.XLSX.

[45] Zhao Q, Wang Y, Chen C. Numerical simulation of the impact of different cushion gases on underground hydrogen storage in aquifers based on an experimentally-benchmarked equation-of-state. Int J Hydrogen Energy 2024;50:495–511. https://doi.org/10.1016/J.IJHYDENE.2023.07.262.

[46] Oldenburg CM, Pan L. Utilization of CO2 as cushion gas for porous media compressed air energy storage. Greenhouse Gases: Sci Technol 2013;3:124–35. https://doi.org/10.1002/GHG.1332.
[47] He Y, Xie Y, Qiao Y, Qin J, Tang Y. Estimation of underground hydrogen storage capacity in depleted gas reservoirs using CO2 as cushion gas. Appl Energy 2024; 375:124093. https://doi.org/10.1016/J/APENERGY.2024.124093.

[48] Saeed M, Jadhawar P. Optimizing underground hydrogen storage in aquifers: the impact of cushion gas type. Int J Hydrogen Energy 2024;52:1537–49. https://doi.org/10.1016/J.IJHYDENE.2023.08.352.

[49] Chai M, Chen Z, Nourozieh H, Yang M. Numerical simulation of large-scale seasonal hydrogen storage in an anticline aquifer: a case study capturing hydrogen interactions and cushion gas injection. Appl Energy 2023;334:120655. https://doi.org/10.1016/J/APENERGY.2023.120655.

[50] Tahmasebi A, Nasiri A, Riazi M, Amiri M. Advantages and disadvantages of in situ N2 presence in underground gas storage (UGS) process: technical and economical evaluation of a case study. J Nat Gas Sci Eng 2020;84:103649. https://doi.org/10.1016/J.JNGSE.2020.103649.

[51] Bahrami M, Izadi Amiri E, Zivar D, Ayatollahi S, Mahani H. Challenges in the simulation of underground hydrogen storage: a review of relative permeability and hysteresis in hydrogen-water system. J Energy Storage 2023;73:108886. https://doi.org/10.1016/J.EST.2023.108886.

[52] Heinemann N, Scaffidi J, Pickup G, Thaysen EM, Hassanpouryouzband A, Wilkinson M, Satterley AK, Booth MG, Edlmann K. Haszeldine R.S. Hydrogen storage in saline aquifers: the role of cushion gas for injection and production. Int J Hydrogen Energy 2021;46:39284–96. https://doi.org/10.1016/J.IJHYDENE.2021.09.174.

[53] Pfeiffer WT, Bauer S. Subsurface porous media hydrogen storage – scenario development and simulation. Energy Proc 2015;76:565–72. https://doi.org/10.1016/J.EGYPRO.2015.07.872.

[54] Huang T, Moridis GJ, Blasingame TA, Abdulkader AM, Yan B. Compositional reservoir simulation of underground hydrogen storage in depleted gas reservoirs. Int J Hydrogen Energy 2023;48:36035–05. https://doi.org/10.1016/J.IJHYDENE.2023.05.355.

[55] Kanaani M, Sedaee B, Asadian-Pakfar M. Role of cushion gas on underground hydrogen storage in depleted oil reservoirs. J Energy Storage 2022;45. https://doi.org/10.1016/J.EST.2021.103783.

[56] Zamehrian M, Sedaee B. Underground hydrogen storage in a partially depleted gas condensate reservoir: influence of cushion gas. J Pet Sci Eng 2022;212:110304. https://doi.org/10.1016/J.PETROL.2022.110304.

[57] Liu K, Zhu W, Pan B. Feasibility of hydrogen storage in depleted shale gas reservoir: a numerical investigation. Fuel 2024;357:129703. https://doi.org/10.1016/J.FUEL.2023.129703.

[58] Jha RK, John AK, Bryant SL, Lake LW. Flow reversal and mixing. SPE J 2009;14:41–9. https://doi.org/10.2118/103054-PA.

[59] Feldmann F, Hagemann B, Ganzer L, Panfilov M. Numerical simulation of hydrodynamic and gas mixing processes in underground hydrogen storages. Environ Earth Sci 2016;75:1–15. https://doi.org/10.1007/S12665-016-5948-Z/FIGURES/9.

[60] Oldenburg CM, Webb SW, Pruess K, Moridis GJ. Mixing of stably stratified gases in subsurface reservoirs: a comparison of diffusion models. Transport Porous Media 2004;54:323–34.

[61] Rezk MG, Forozeshi J, Abdulrahman A, Gholizehad J. CO 2 diffusion and dispersion in porous media: review of advances in experimental measurements and mathematical models. https://doi.org/10.1021/acs.energyfuels.1c03552; 2021.

[62] Pfeiffer WT, Beyer C, Bauer S. Hydrogen storage in a heterogeneous sandstone formation: dimensioning and induced hydraulic effects. https://doi.org/10.1144/petgeo2016-050.

[63] Alafnan S. Factors influencing hydrogen migration in cap rocks: establishing new screening criteria for the selection of underground hydrogen storage locations. Int J Hydrogen Energy 2024;83:1099–106. https://doi.org/10.1016/J.IJHYDENE.2024.08.179.

[64] Jia Z, Cao R, Pu B, Dehghanpour H, Cheng L, Zhang Q, Awotunde AA. Pore-scale binary diffusion behavior of Hydrogen-Cushion gas in saline aquifers for underground hydrogen Storage: optimization of cushion gas type. Fuel 2024;381:133481. https://doi.org/10.1016/J.FUEL.2024.133481.

[65] Wang G, Pickup G, Sorbie K, Mackay E. Numerical modelling of H2 storage with cushion gas of CO2 in subsurface porous media: filter effects of CO2 solubility. Int J Hydrogen Energy 2022;47:28956–68. https://doi.org/10.1016/J.IJHYDENE.2022.06.201.

[66] Wang G, Pickup G, Sorbie K, Mackay E. Scaling analysis of hydrogen flow with carbon dioxide cushion gas in subsurface heterogeneous porous media. Int J Hydrogen Energy 2022;47:1752–64. https://doi.org/10.1016/J.IJHYDENE.2021.10.224.

[67] Wang G, Pickup GE, Stuart KS, MacKay EJ. Driving factors for purity of withdrawn hydrogen: a numerical study of underground hydrogen storage with various cushion gases. Society of petroleum engineers - SPE EuropEC - europe energy conference featured at the 83rd EAGE annual conference and exhibition, EURO 2022. 2022. https://doi.org/10.2118/209625-MS.

[68] Afshari S, Hejazi SH, Kantzas A. Longitudinal dispersion in heterogeneous layered porous media during stable and unstable pore-scale miscible displacements. Adv Water Resour 2018;119:125–41. https://doi.org/10.1016/J.ADVWATRES.2018.06.005.

[69] Gelhar LW, Welty C, Rehfeld KR. A critical review of data on field-scale dispersion in aquifers. Water Resour Res 1992;28:1955–74. https://doi.org/10.1029/92WR00607.

[70] Oldenburg CM. Carbon dioxide as cushion gas for natural gas storage. 2003. http://doi.org/10.1021/ef020162b.

[71] Shrivastava VK, Nghiem LX, Moore RG, Okazawa T. Modelling physical dispersion in miscible displacement - Part 1: theory and the proposed numerical scheme. J Can Petrol Technol 2005;44:25–33. https://doi.org/10.2118/05-01/32141/MODELLING-PHYSICAL-DISPERSION-IN-MISCIBLE.

[72] RAG. Underground Sun storage 2030. https://www.uss-2030.at/en/. [Accessed 25 July 2024].

[73] Panfilov M. Underground storage of hydrogen: in situ self-organisation and methane generation. Transport Porous Media 2010 85:3 2010;85:841–65. https://doi.org/10.1007/S11242-010-9595-7.

[74] Abdellatif M, Hashemi M, Azizomohammadi S. Large-scale underground hydrogen storage: integrated modeling of reservoir-wellbore system. Int J Hydrogen Energy 2023;48:19160–71. https://doi.org/10.1016/J.IJHYDENE.2023.01.227.

[75] Delshad M., Umurzakov Y., Sepehrnoori K., Eichhubl P., Batista Fernandes B.R. Hydrogen storage assessment in depleted oil reservoir and saline aquifer. Energies 2022;15:8132. 2022;15:8132. 10.3390/EN15218132.

[76] Paterson L. The implications of fingering in underground hydrogen storage. Int J Hydrogen Energy 1983;8:53–9. https://doi.org/10.1016/0360-3199(83)90035-6.

[77] Sainz-Garcia A, Abarca E, Rubi V, Grandia F. Assessment of feasible strategies for seasonal underground hydrogen storage in a saline aquifer. Int J Hydrogen Energy 2017;42:16657–66. https://doi.org/10.1016/J.IJHYDENE.2017.05.076.

[78] Luboń K, Tarkowski R. Numerical simulation of hydrogen injection and withdrawal to and from a deep aquifer in NW Poland. Int J Hydrogen Energy 2020;45:2068–83. https://doi.org/10.1016/J.IJHYDENE.2019.11.055.

[79] Ershadnia R, Singh M, Mahmoodpour S, Meyal A, Moeini F, Hosseini SA, Sturmer DM, Rasoulzadeh M, Dai Z, Soltanian MR. Impact of geological and operational conditions on underground hydrogen storage. Int J Hydrogen Energy 2022. https://doi.org/10.1016/J.IJHYDENE.2022.09.208.

[80] Azin R, Izadpanahi A, Ranbar A. Challenges of gas injection. 2022. p. 397–413. https://doi.org/10.1007/978-3-030-77200-9_0.

[81] Hagemann B, Rasoulzadeh M., Panfilov M., Ganzer L., Reitenbach V. Mathematical modeling of unstable transport in underground hydrogen storage. 2015. https://doi.org/10.1007/s12665-015-4414-7.

[82] Oldenburg CM, Finsterle S, Trautz RC. Correction: water uponing in underground hydrogen storage: sensitivity analysis to inform design of withdrawal, vol. 151. Transp Porous Media; 2024. p. 857–8. https://doi.org/10.1007/s11242-024-02066-z.

[83] Carden PO, Paterson L. Physical, chemical and energy aspects of underground hydrogen storage. Int J Hydrogen Energy 1979;4:559–69. https://doi.org/10.1016/0360-3199(79)90083-1.

[84] Ma J, Li Q, Kempka T, Kühn M. Hydromechanical response and impact of gas mixing behavior in subsurface CH4 Storage with CO2-based cushion gas. Energy Fuel 2019;33:6527–41. https://doi.org/10.1021/ACS.ENERGYFUELS.9B00518/ASSET/IMAGES/LARGE/EF-2019-005188_0015. JPEG.

[85] Luboń K, Tarkowski R. Numerical simulation of hydrogen injection and withdrawal to and from a deep aquifer in NW Poland. Int J Hydrogen Energy 2020;45:2068–83. https://doi.org/10.1016/J.IJHYDENE.2019.11.055.

[86] Bo Z, Hörning S, Underschultz JR, Garnett A, Hurter S. Effects of geological heterogeneity on gas mixing during underground hydrogen storage (UHS) in braided-fluvial reservoirs. Fuel 2024;357:129949. https://doi.org/10.1016/J.FUEL.2023.129949.

[87] Computer Modelling Group Ltd. Computer Modelling Group Ltd. Reservoir Simulation Software 2023. https://www.cmgl.ca/. [Accessed 24 April 2023].

[88] Goodchild MW, Bryant P. The geology of the Rough gas field. Geol Soc Spec Publ 1986;23:223–35. https://doi.org/10.1144/GSL.SP.1986.023.01.14.

[89] Reijnen-Mooij GCAM, Damoiseaux M, van Klaveren S, Jaarsma B. A study of underground hydrogen storage in 2D box models with properties comparable to typical depleted gas fields in The Netherlands. Day 3 Fri, June 2024 2024;28. https://doi.org/10.2118/220013-MS.

[90] Izadi Amiri I, Zivar D, Ayatollahi S, Mahani H. The effect of gas solubility on the selection of cushion gas for underground hydrogen storage in aquifers. J Energy Storage 2024;80:110264. https://doi.org/10.1016/J.EST.2023.110264.

[91] Pashin JC. Coal as a petroleum source rock and reservoir rock. Applied Coal Petrology 2008:227–62. https://doi.org/10.1016/B978-0-08-045051-3_00009-9.

[92] Wareing CJ, Woolley RM, Fairweather M, Falle SAEG. A composite equation of state for the modeling of sonic carbon dioxide jets in carbon capture and storage scenarios. AIChE J 2013;59:3928–42. https://doi.org/10.1002/AIC.14102.

[93] Khamehchi E, Rashidi F. Simulation of underground natural gas storage in sarajeh gas field. 2006. https://doi.org/10.2118/106341-MS.

[94] Jossi JA, Stiel LI, Thodos G. The viscosity of pure substances in the dense gaseous and liquid phases. AIChE J 1962;8:59–63. https://doi.org/10.1002/AIC.690080116.

[95] Ershadnia R, Singh M, Mahmoodpour S, Meyal A, Moeini F, Hosseini SA, Sturmer DM, Rasoulzadeh M, Dai Z, Soltanian MR. Impact of geological and operational conditions on underground hydrogen storage. Int J Hydrogen Energy 2023;48:1450–71. https://doi.org/10.1016/J.IJHYDENE.2022.09.208.

[96] Okoroafor ER, Sampaio L, Gasanzade F, Perez Claro Y, Zhou JD, Saltzer SD, Bauer S, Kovscek A.R., Okoroafor ER, Sampaio L, Gasanzade F, Perez Claro Y, Zhou JD, Saltzer SD, Bauer S. Kovscek A.R. Intercomparison of numerical simulation models for hydrogen storage in porous media using different codes. Energy Convers Manag 2023;292:117409. https://doi.org/10.1016/J.ENCONMAN.2023.117409.

[97] Oldenburg C.M., Pruess K, Benson S.M. Process modeling of CO 2 injection into natural gas reservoirs for carbon sequestration and enhanced gas recovery. 2001 https://doi.org/10.1021/ef000247h.
[98] Zhu S, Sun J, Wei G, Zheng D, Wang J, Shi L, Liu X. Numerical simulation-based correction of relative permeability hysteresis in water-invaded underground gas storage during multi-cycle injection and production. *Petrol Explor Dev 2021;48:* 190–200. https://doi.org/10.1016/S1876-3804(21)60015-0.

[99] Onuh, Fred T, Rotimi OJ, Enaworu E. The impact of perforation geometry on oil well productivity. *Int J Mech Eng Technol 2019;10:1900–9.*

[100] Stuart IA. The Rough gas storage field, blocks 47/3d, 47/8b, UK North Sea. *Geological Society Memoir 1991;14:477–84.* https://doi.org/10.1144/GSL.MEM.1991.014.01.59.

[101] Heinemann N., Edlmann K., Wilkinson M., Hassanpouryouzband A., Thaysen E.M, Haszeldine R.S. Dynamic hydrogen storage capacity in compartmentalised gas

fields: the UK Rough storage site as a case study. Available at: https://doi.org/10.2139/ssrn.4838402.

[102] Cheng X, Shi Z, Glass N, Zhang L, Zhang J, Song D, Liu ZS, Wang H, Shen J. A review of PEM hydrogen fuel cell contamination: impacts, mechanisms, and mitigation. *J Power Sources 2007;165:739–56.* https://doi.org/10.1016/J.JPOWSOUR.2006.12.012.

[103] ISO 14687:2019 - Hydrogen fuel quality — Product specification n.d. (accessed February 7, 2024) https://www.iso.org/standard/69539.html.

[104] Staffell I, Scamman D, Velazquez Abad A, Balcombe P, Dodds PE, Ekins P, et al. The role of hydrogen and fuel cells in the global energy system. *Energy Environ Sci 2019;12:463–91.* https://doi.org/10.1039/C8EE01157E.