Effect of reducing irreducible water saturation in a near-well region on CO2 injectivity and storage capacity

Effect of reducing irreducible water saturation in a near-well region on CO2 injectivity and storage capacity

International Journal of Greenhouse Gas Control 86 (2019) 134–145 Contents lists available at ScienceDirect International Journal of Greenhouse Gas ...

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International Journal of Greenhouse Gas Control 86 (2019) 134–145

Contents lists available at ScienceDirect

International Journal of Greenhouse Gas Control journal homepage: www.elsevier.com/locate/ijggc

Effect of reducing irreducible water saturation in a near-well region on CO2 injectivity and storage capacity

T



Yong-Chan Parka, Seunghee Kimb, , Jang Hyun Leec, Young Jae Shinna a

Korea Institute of Geoscience and Mineral Resources, Daejeon, 34132, Republic of Korea Department of Civil Engineering, University of Nebraska-Lincoln, Omaha, NE 68182, USA c Department of Petroleum Engineering, Universiti Tecknologi PETRONAS, 32610 Perak, Malaysia b

A R T I C LE I N FO

A B S T R A C T

Keywords: CO2 geological storage CO2 injectivity Storage capacity Pressure buildup Numerical simulation Surfactant

Fossil fuels currently supply 80% of the world’s energy demands and are primarily responsible for increasing carbon concentration in the atmosphere and the associated climate change. Achieving internationally discussed goals for reducing carbon emission will be either impossible or involve significant costs without implementing the CO2 capture and storage (CCS). The volumetric CO2-storage capacity of a brine aquifer is among the most critical factors for the economically-viable & large-scale geologic CO2-storage projects. The maximum sustainable injection rate or CO2 injectivity is another important criterion that depends on many reservoir properties. Based on previous experimental studies, we hypothesized that if the sweep efficiency of CO2 is improved by using suitable additives, then a higher end-maximum CO2 saturation can be achieved that, in turn, can increase the CO2 injectivity. In this regard, a strategy to enhance the CO2 injectivity was proposed by reducing the irreducible water saturation in a near-well region. In this study, the influence of reducing the irreducible water saturation and thus improving the relative permeability of CO2 on the CO2 injectivity and storage capacity is investigated in depth. A series of numerical simulations involving two test models – a hypothetical horizontal aquifer and a pilot test site in South Korea – were conducted to examine our assumptions with the concentration of surfactants confirmed from the previous experimental study. The results help to ascertain the applicability and effectiveness of the proposed injectivity-enhancing strategy. It was observed that the pre-injection of surfactant solution slows down the well-bottom-hole pressure and increases the total CO2 injection capacity, with the effect deemed proportional to the quantity of surfactant for a hypothetical flat aquifer. However, a nonlinear relationship between the surfactant quantity and the injectivity was found in the case of the pilot test site, which revealed that the surfactant pre-injection influences the migration of CO2-plume and solubility trapping as well.

1. Introduction Fossil fuels account for more than 80 percent of the world's primary energy sources, and this high dependency does not seem to change shortly. For instance, the global energy demand is projected to be ˜40 percent higher in 2035 compared to 2010, and so the total share of fossil fuels is expected to remain at about 76 percent (IEA, 2015). Such a high dependency will lead to a continued increase in carbon emission into the atmosphere. In this situation, all the available options, such as energy efficiency and conservation, fuel shift, nuclear fission, renewable electricity, CO2 capture and storage (CCS), and afforestation (i.e., seven wedges concepts in Socolow and Pacala, 2006), need to be pursued to tackle this challenge. Notably, it was reported that achieving the internationally discussed goals of reducing carbon emission will be either impossible or involve significant costs without implementing the ⁎

CCS (IPCC, 2013). An economically viable CCS operation requires that CO2 sources are fitted with low-cost capture technologies and CO2 sinks have sufficient storage capacities as well as proximity to the emission sources. Once captured, CO2 can be pumped into deep subsurface formations such as depleted oil and gas reservoirs, saline aquifers, or deep unmineable coal beds. Geologic storage in a depleted oil/gas reservoir is advantageous because its geologic structure might be already well known and many required infrastructures are already in place. Nonetheless, saline aquifers are deemed far more applicable to CO2 storage because of their globally widespread existence (Benson et al., 2013; IPCC, 2005). Several requirements need to be met for successful geologic sequestration. Reservoirs should be deep enough so that CO2 is in the denser supercritical state. Storage capacity must suffice to accommodate CO2 captured from primary emission sources, including fossil-

Corresponding author. E-mail address: [email protected] (S. Kim).

https://doi.org/10.1016/j.ijggc.2019.04.014 Received 9 October 2018; Received in revised form 18 April 2019; Accepted 18 April 2019 Available online 08 May 2019 1750-5836/ © 2019 Elsevier Ltd. All rights reserved.

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1983):

fuel based power facilities and industrial processes. Besides, the presence of a seal layer above the storage reservoir is essential to retain CO2 for predetermined storage periods. Even with large storage capacities and quality overlying seals, the CCS operation may not be economically feasible without achieving a minimum level of CO2 injectivity into a target formation. Costs of geologic CO2 storage depends on the location of a storage site (onshore or offshore), heating of CO2 (supercritical vs. cold liquid state), and the number and the type of wells for the CO2 injection, among many factors (Rubin et al., 2015; Goodarzi et al., 2015; Vilarrasa et al., 2013; Neal et al., 2011). The number of wells depends on the injectivity of the site, which is determined by its multiphase flow properties. If the injection rate is required to be higher for a low-injectivity formation, a substantial number of wells would be needed, which could dramatically increase the capital and operating costs (Hosseini et al., 2014). On the other hand, injecting large quantities of CO2 is expected to build up excess pore-pressure in the storage formation (Kim et al., 2018a; Szulczewski et al., 2012). In contrast to depleted oil/gas reservoirs whose pressures are already much lower than their initial levels, the pressure in saline aquifers during the CO2 injection can rise rapidly and approach its limit, requiring the termination of the procedure, as was observed in Snohvit, Norway (Hansen et al., 2013). Note that it targeted Tubåen formation is compartmentalized, which even might facilitate the pore pressure buildup. Among many physical factors that affect the CO2 injectivity, two critically important properties are the absolute permeability of storage formation and the relative permeability of CO2. Even when other factors remain same, any change in the relative permeability can lead to a considerable variation of the injectivity by as much as a factor of four, as shown in the measurements at seven formations (Burton et al., 2009). Interfacial tension and rock wettability control the relative permeabilities and residual saturation of the water and CO2 phases in the reservoir rock (Bennion and Bachu, 2006; Chalbaud et al., 2009; Owens and Archer, 1971). It was reported that if the capillary factor, which is the multiplication of interfacial tension and contact angle, is lowered then the sweep efficiency of CO2 invasion can be significantly enhanced (Kim and Santamarina, 2014; note: it denotes the microscopic sweep efficiency). The capillary factor can be effectively reduced by using additives, such as nanoparticles, synthetics surfactants, or biosurfactants (Park et al., 2017). If the sweep efficiency is improved by adopting those additives, a higher end-maximum CO2 saturation can be achieved that, in turn, can increase the CO2 injectivity. Based on this heuristic, this manuscript proposes a new strategy that enhances the CO2 injectivity via reducing the irreducible water saturation (i.e., increasing the CO2 saturation) in a near-well region. There is no previous study to date that investigated this idea in depth. In this regard, we performed numerical simulations to examine the impact of irreducible water saturation reduction on the CO2 injectivity and flow in deep saline aquifers and thus to verify the suggested strategy. A concentration of surfactants used by Kim and Santamarina (2014) is adopted for this study to simplify the implementation of numerical simulations.

II =

ρ 2πkCO2 h Q = r (Pinj − Pres ) ρs ln re +S μ CO2 r

(

w

)

(1)

Where Q is the injection flow rate, Pinj is the injection bottom-hole pressure (BHP), Pres is the average reservoir pressure, ρr is the density of injected fluid (i.e., CO2 for CCS) under reservoir conditions, ρs is the density of injected fluid under standard conditions, kCO2 is the effective CO2 permeability, h is the thickness of the reservoir, rw is the wellbore diameter, re is the radius of an outer boundary, S is the skin factor, and μCO2 is the CO2 viscosity. Primary factors that affect the injectivity index, II, include the effective CO2 permeability, the reservoir thickness, the CO2 density, and the contact area between the wellbore and the formation (Lombard et al., 2010; Miri, 2015). Among those factors, the reservoir thickness, h, cannot be changed. The wellbore radius, rw , can be enlarged through the use of a horizontal well or a vertical well of larger diameter, but at the expense of significantly increased drilling cost. Flow rate, Q , can be increased by injecting CO2 in a denser liquid state or imposing a higher CO2 injection pressure, but the injection pressure must be kept below the fracturing pressure or fault-reactivating pressure to preserve the mechanical integrity of sealing layers. Those maximum limit (or critical) pressure is determined based on the shear stress, the coefficient of friction, and the normal stress on faults to account for their hydro-mechanical behavior (Rutqvist et al., 2007). Fig. 1 implies that the critical pressure lies between the hydrostatic and lithostatic pressure values. CO2 injection into an aquifer involves more than one fluid transport; as a result, the ability of one fluid to flow is hampered by the presence of the other fluid. Effective permeability describes the simultaneous flow of multiphase systems and is calculated by multiplying the absolute permeability of the rock with the relative permeability of each phase. Laboratory-based experiments are needed to determine these values quantitatively. Absolute permeabilities are usually obtained from laboratory experiments and/or in-situ well testing (Honarpour and Mahmood, 1988). Unlike the contact area and injection flow rate, there is a promising potential to enhance the relative permeability of CO2, thus the effective permeability, with a minimum technological and economic burden.

2. Strategy to improve CO2 injectivity 2.1. CO2 injectivity Injectivity is defined as the ability of a geological formation to accept fluids via their injection through a well. It is considered to be a crucial component for sequestration in an aquifer, even with a significant storage potential, from both technical and economic perspectives. Conceptually, injectivity can be expressed by an index, II, that is represented by the ratio of the injection flow rate to the pressure difference between the reservoir and the wellbore. It can be described as in Eq. (1) for the radial geometry under the steady state condition (Dake,

Fig. 1. Key pressures as a function of depth, and the rock-failure pressure at a specific depth. 135

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applied, which otherwise would remain constant. Addition of lipopeptide biosurfactant (i.e., surfactin) was also experimentally shown to reduce the CO2-water IFT by about 50% and increase the contact angle up to 62° (Park et al., 2017). Several nanoparticles are also known to reduce CO2-water IFT to as low as about 10 mN/m when they are added to water (Zheng and Jang, personal communication). By any of these additives, the capillary factor can be reduced significantly, which encourages CO2 to invade smaller pores and to occupy more pore spaces. On the basis of the above observations, we set up following logics: (a) a proper additive (e.g., chemical surfactants, biosurfactants, or nanoparticles) injection prior to CO2 injection will cause a reduction in the capillary factor that consequently improves sweep efficiency of CO2, that is, higher CO2 saturation; (b) enhanced sweep efficiency leads to a more drainage of water displaced by the injected CO2; (c) more pore spaces and flow channels occupied by CO2 contributes to enhancing the endpoint CO2 relative permeability; and (d) the enhanced endpoint relative permeability of CO2 leads to improving CO2 injectivity and storage capacity. To investigate the viability of the proposed strategy for improving CO2 injectivity, we conducted numerical simulations with a two-dimensional simplified model and a three-dimensional real field model. Details are provided in the following sections.

Fig. 2. Experimental data in the literature: Maximum CO2 saturation and the endpoint CO2 relative permeability of sandstone specimens.

2.2. Relative permeability Relatively few data on the relative permeability of CO2-brine system has been published, compared to the richness of data for the oil and water systems. The majority of these data were generated by a research group in Canada during the early stage of CCS research (Bachu and Bennion, 2008; Bennion and Bachu, 2005, 2006, 2007, 2008, 2010). Since then, data from several other experiments in other regions of the world have been added (Kim et al., 2018b; Krevor et al., 2012; Mackay et al., 2010; Perrin and Benson, 2010; Shell, 2011; Shi et al., 2011). Benson et al. (2013) and Burnside and Naylor (2014) summarized and reviewed those previous experimental studies on CO2-brine relative permeability. In particular, Burnside and Naylor (2014) analyzed published endpoint-relative permeability of CO2 along with CO2 saturation (i.e., irreducible water saturation) to provide insight into the injectivity and the storage capacity. Fig. 2 displays the collected data from tests using sandstones: the observed trend is that the relative endpoint permeability of CO2 increases with the higher value of CO2 saturation (Bennion and Bachu, 2006; Burnside and Naylor, 2014). Noticeably, maximum CO2 saturations are in the range of 0.34–0.80, but mainly below 0.6, and about 40% (13 out of 32 data points) shows that their maximum CO2 saturation is less than 0.5. Endpoint CO2 relative permeabilities are more densely populated near the lower values, with 40% is less than 0.2 and only ˜30% (9 out of 32 data points) is higher than 0.4. In the following study, it was reported that the endpoint CO2 relative permeability is reduced with increasing CO2-brine interfacial tension (IFT) (Bennion and Bachu, 2006). Larger IFT hinders CO2 invasion into smaller pores and thus contributes to a higher irreducible water saturation (Chalbaud et al., 2009). Therefore, CO2 saturation is expected to increase with reduced IFT.

3. Simulation methodology 3.1. Numerical simulator The numerical simulation in this study was implemented using the commercial software CMG-GEM, which is a general equation-of-state compositional reservoir simulator and has been commonly used in the oil and gas industry. The software is capable of modeling a range of miscible gas injection processes, including the CO2 injection into saline aquifers (Jong et al., 2016; Lins Jr. et al., 2011; Nghiem et al., 2009a, b). It has been verified by a benchmark study (Class et al., 2009) and many other theoretical and field applications (Kumar et al., 2005; Uddin et al., 2013; Choi et al., 2011; Sato et al., 2011) on CO2 geologic storage problems. CO2 dissolution and residual trapping are considered during the simulation, but the chemical reaction with minerals is generally not incorporated. CMG-GEM has also been used to simulate the surfactant concentration around an injection well and to examine the effects of surfactant-altered relative permeability on the injectivity and storage capacity. Note that even though CMG-GEM is also capable of calculating geomechanical and thermal effects, these mechanically and thermally coupled phenomena were not considered during the simulations in this study. 3.2. Surfactant and relative permeability We selected the surfactant used by Kim and Santamarina (2014) for the following in-depth numerical simulations in this study. The selected surfactant, SURFONIC POA-25R2, is water soluble, and its concentration in water should be carefully maintained below the CMC (1 wt%) to avoid the formation of micelles (da Rocha et al., 1999). Given its molar mass of 4167 g/mol, we chose to dilute the surfactant in water to the concentration of 0.99 wt%. That is, adding the surfactant would require at least the co-injection of 100 times its mass of water, which could result in the decrease of available pore volumes. For this reason, it may be preferred to inject as small amounts of the surfactant as possible. More detailed analysis is given later in the following section. We artificially set the 0.4 wt% of surfactant concentration as the criterion that alters the relative permeability of CO2 in the zone during the simulation to reflect the influence of surfactant on the permeability improvement. Note that even 0.1 wt% of the selected surfactant was shown to reduce the capillary factor (Kim and Santamarina, 2014), but we selected the higher percentage, 0.4 wt%, as the criterion to be conservative in this study.

2.3. Enhancing CO2 injectivity IFT can be altered by actively imposing an electromagnetic field (Francisca et al., 2008) or through the use of surfactants (da Rocha et al., 1999; Kim and Santamarina, 2014; Ryoo et al., 2003). For example, a surfactant composed of hydrophilic polyoxyethylene and CO2philic polyoxypropylene is capable of changing interfacial tension when it is located between CO2 and water/brine. It was experimentally ascertained that addition of the surfactant lowered the CO2-water IFT from 50 mN/m (at the atmospheric pressure) to a stable 4 mN/m at pressures over 7 MPa, while the IFT hovered around 30 mN/m at the same high pressures in the absence of the surfactant (at the concentration of 0.4 wt%; Kim and Santamarina, 2014). Also, the CO2-H2OSiO2 contact angle increased from 20° to 70° when the surfactant was 136

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limitation, two curves in Fig. 3 are input to the simulation to reflect changes in the relative permeabilities in correspondence to the saturation change of each phase. Kumar et al. (2005) suggested that a higher residual and solubility trapping of CO2 can be achieved by injecting CO2 only to the lower part of an aquifer, due to the combined effect of the lengthened travel time of CO2 before reaching caprock, heterogeneity of the storage reservoir, and hysteresis of the relative permeability. Besides, we may get a thicker CO2 plume around the injection well. In this regard, CO2 was injected only in the lower part of the aquifer in the simulation to induce higher trapping of CO2. 3.3.1. Pre-injection of surfactant solution During the pre-injection of the surfactant solution, the surfactant components in the aqueous phase are mixed with existing water in the pore spaces and migrate outwards as the fluid injection continues. Hydrodynamic force is the main driver during the surfactant injection before the main CO2 injection. Note that the density difference between CO2 and the formation water would also affect the flow once the CO2 injection begins.

Fig. 3. Relative permeability curves used in this study for investigating the effect of surfactant addition on CO2 injectivity. Solid lines: original case, dashed lines: enhanced case.

3.3.2. Following CO2 injection Surfactant injection, followed by the CO2 injection, gradually extends the altered region with a higher surfactant concentration in it. To reflect such an alteration during the numerical simulation, firstly it is needed to identify the range of altered region before the main injection of CO2. For this purpose, a small amount of CO2 (200 t) was injected right after the injection of the surfactant solution. After that, the main CO2 injection with a constant rate is applied at the injection well until it is terminated.

Table 1 Relative permeability characteristics of the CO2 flow using Brooks and Corey equation.

Irreducible water saturation, Swirr Endpoint CO2 relative permeability at Swirr, krCO2 Corey’s exponent for CO2 Residual CO2 saturation, SrCO2

Original curve

Enhanced curve

0.558 0.332

0.294 0.545

2.9 0.2

4.9 0.2

3.4. Test problems With that, once the surfactant concentration of a grid block excels 0.4 wt%, the maximum CO2 saturation and the CO2 relative permeability of the block are tapped enhanced. Fig. 3 displays the two relative-permeability curves employed in this study: one is for an unaltered original rock, and the other is for the case enhanced by the surfactant. Note that CO2 pore occupancy increases from 0.442 to 0.706 when the surfactant concentration in the altered region (primarily near the wellbore) meets the criterion, which improves the relative permeability of CO2. Table 1 presents the relative permeability characteristics obtained using Brooks and Corey equations (1966). These relativepermeability curves are hypothetically synthesized ones to provide a conservative input. That is, the maximum value of relative permeability of the original rock, 0.332, is higher than the reported data in Fig. 2 (i.e., 0.332 > range of endpoint relative CO2 permeability (0.1−0.3) for the maximum CO2 saturation = 0.3−0.4), while the maximum value of the enhanced case, 0.545, is selected from the lowest reported data in the range of the increased maximum CO2 saturation (0.6−0.7). The imbibition curves of the CO2-brine system were calculated using Land’s equation (Kumar et al., 2005; Land, 1968). The Land’s hysteresis model needs maximum residual CO2 saturation. We selected the residual saturation of 0.2 that was in the general range of the estimated residual saturation from the Otway site (LaForce et al., 2014) and the experimental values listed by Burnside and Naylor (2014).

For the in-depth numerical simulation, two different geologic structures are modeled in this study: a hypothetical horizontal aquifer and an actual pilot test site. We performed the first set of numerical simulations using the flat horizontal aquifer that idealizes a subsurface reservoir in the simplest way. On the other hand, an anticline structural trap is a more desirable hydrocarbon reservoir in that hydrocarbons can be trapped in the peak of this structure. Likewise, monoclinal structures can be used better for the CO2 storage purpose. It was even suggested that monoclinal structures have higher storage potentials than any other structural traps (Takahashi et al., 2009). In this regard, we conducted the second set of numerical simulations to represent the monoclinal-structured pilot test site in South Korea to further explore the proposed strategy and to examine its effect on realistic complex geometry. Simulated geometry and the pre-injection scenario of surfactant solution are explained next. 3.4.1. A hypothetical horizontal aquifer Our primary interest revolved around whether or not a small amount of injected surfactant would affect the CO2 injectivity. For this purpose, base-case simulations were performed with radial-cylindrical grids that contain 250 (50 × 1× 5) blocks that represent 10% of the entire horizontal aquifer with an internal angle of 36°. This hypothetical aquifer is located at a depth of 1,000 m, has a radius of 5,000 m, and a thickness of 100 m, as shown schematically in Fig. 4. No mass flux is allowed across any boundary, and the initial pressure at the injection well is set to 11.87 MPa. The allowable maximum well-bottom-hole pressure is set to 14 MPa for the simple grid model. Main simulation inputs are summarized in Table 2.

3.3. Extent of altered zone We illustrate the simulation condition and method with the surfactant injection in this section. The numerical simulator computes surfactant components in the aqueous phase whose concentrations are quantified in a grid block. However, surfactant components in CMGGEM are mainly intended for simulating foam EOR (enhanced oil recovery); and so, the concentration cannot be readily used to alter the relative permeability of each phase (CMG, 2017). To overcome such a

3.4.2. The Pohang basin pilot project The Pohang Basin is a Cenozoic sedimentary basin located in the southeastern part of the Korean Peninsula (Fig. 5). The western border faults, defined by a series of echelon normal faults, were formed during 137

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Fig. 4. A simplified grid system for simulating surfactant injection prior to CO2 injection on a hypothetical horizontal aquifer.

into two parts, namely lower coarse-grained and upper fine-grained successions. The primary target formation for CO2 injection is an approximately 14-m-thick interval in the lower succession; this target contains interbedded conglomerates and sandstones with minor mudstone beds or lenses. The target formation is a fault-bounded, N- to NNE-trending trough that gradually rises toward the east and southeast to form a gentle monocline. The injection well, which is very close to the exploration well (PHEW-1), is located near the lower limb of the monocline and approximately 500 m from the nearby fault at the upper limb of the monocline (Choi et al., 2017). The dip angle of the line B-B’ across the well (Fig. 9) is 6.5°. Based on a series of tests with various grid densities, the grid size was chosen as about 20 × 20 × 1 m, which resulted in total 98,566 active grids. Table 3 summarizes the petrophysical parameters that were used for the application of surfactant in this study. The lateral boundaries were set as closed boundary conditions for conservative prediction because the information was not sufficient regarding the boundaries in this area.

Table 2 Input parameters used in simplified grid simulations. Parameter

Value

Number of cells Aquifer thickness Aquifer depth Permeability Porosity Injection rate

250 (50 × 1 x 5) 100 m 1,000 m 100 md 18% 53,502 m3/day ( = 100.0 t/day at the surface condition) 11.87 MPa at the depth of 1,090 m 14.0 MPa 4,167 g/mol

Initial reservoir pressure Maximum injection pressure Molar mass of surfactant

the Miocene (17 Ma) and resulted in fault-controlled subsidence (Cheon et al., 2012). The shallow offshore Pohang basin was drilled during an exploration stage to identify suitable formations for a pilot-scale CO2 storage project. Sedimentary succession in the well is largely divided

Fig. 5. Pohang Basin pilot CO2-storage project: Geological map of the study area (Sohn and Son, 2004) and reservoir geometry (top depth). 138

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Table 3 Input parameters used for the Pohang Pilot site. Parameter

Value

Number of active grids Aquifer thickness Aquifer depth Average permeability Vertical-to-horizontal ratio of permeability Average porosity Injection rate

98,566 (152 × 95 × 12) 14 m 641 m – 865 m 15.1 md 0.1

Initial reservoir pressure Maximum injection pressure Molar mass of surfactant

21.0% 8,025.34 m3/day ( = 15 t/day at the surface condition) 7,340 kPa at the depth of 800 m 11.0 MPa 4,167 g/mol

Table 4 Surfactant injection scenarios for the simplified base case. Scenario

Mass of Surfactant (t)

Volume of surfactant solution (m3)*

Pore volume of altered region (m3)

Bulk volume of altered region (m3)

Equivalent radius (m)

Baseline S1 S2

– 0.05 1.0

– 5.0 100.0

– 20.7 280.8

– 115 1,560

– 2.5 9.1

Fig. 6. Near-wellbore-region grids for the simplified base case, and altered regions for S1 and S2 (pre-injection of surfactant solution) cases.

* Note: it is assumed that the entire mass of surfactant is dissolved in the solution to estimate the volume of surfactant solution at the surface condition.

As in the previous simplified case, CO2 is injected until the BHP limit is reached during the numerical simulation. The limiting pressure of the site, 11 MPa, was determined as follows: the total major and minor principal stresses, as well as the initial pore pressure at the target depth, were estimated to be 18.8 MPa, 14.2 MPa, and 7.9 MPa, respectively, using the stress gradients provided by Lee et al. (2017). The effective friction angle of the storage basin was assumed to be 24°, which corresponds to 0.45 as the coefficient of friction. With these values, the stress state is expected to touch the Coulomb failure envelope when the pore pressure increases to about 11 MPa. It should be noted that only effective stress changes due to pore-pressure buildup were considered here for simplicity. In other words, poroelastic-stress changes are not considered; hence, the limiting pressure is a conservative estimate. 4. Results and discussion Analysis and discussion on the effect of surfactant quantity on the CO2-reservoir performances, such as pressure buildup and storage capacity, are presented for these two geologic models in the following sections. 4.1. A hypothetical horizontal reservoir 4.1.1. Surfactant injection and the size of altered zone Three cases, pre-injection of 0 (i.e., no injection), 0.05, and 1.0 t of surfactants, are investigated in this study (Baseline, S1, and S2 in Table 4). Grid blocks altered by the surfactant are shown in Fig. 6 (the near-well region was finely discretized into sub-meter scale grids considering the effect of grid sizes and numerical stability). The altered region was observed to enlarge with larger amounts of injected surfactant; the equivalent radius increased significantly, from 2.5 m in S1 to 9.1 m in S2. Moreover, distinct differences were observed in the maximum CO2 saturation.

Fig. 7. (a) Well-bottom-hole pressure evolution with time for various surfactant-injection scenarios (baselines, S1 and S2), and (b) cumulative CO2 injection for different scenarios.

cumulative injection of CO2 for three different scenarios during the CO2 injection until BHP reaches the critical pressure of 14 MPa. It was observed that the pre-injection of surfactant solution has a substantial impact on both the well BHP and the storage capacity (Fig. 7). The well BHP not only decreased upon the addition of the surfactant but also decreased further with more injected surfactant (Fig. 7a). Maintaining low well-bottom-hole pressure throughout the injection process can reduce the possibility of unexpected damage to the surrounding

4.1.2. Impact on the injectivity We investigated the bottom-hole pressure (BHP) and total 139

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Table 5 Comparison of BHP buildup and injected CO2 for three different pre-surfactantinjection scenarios. Note: permeability of storage reservoir is k = 100 md, and the injection rate is maintained at 100 t/day.

Baseline S1 S2

Pressure buildup after 1 y [kPa] (%)

CO2 Injection [kt] (% of baseline)

1,415 (100.0) 1,364 (96.4) 1,318 (93.2)

129.1 (100.0) 134.3 (104.0) 139.6 (108.1)

formations and lengthen the time before reaching the pressure limit. Moreover, the total accumulated CO2 injection increased with the amount of injected surfactant (Fig. 7b). Note that impact of injecting water with the surfactant on the system pressure before the main CO2 injection was observed to be negligible in such a large-sized reservoir. After one year from the commencement of the main CO2 injection, the surfactant-injection scenarios (S1 and S2) exhibited lower buildups of BHP compared to the baseline, by 51.2 and 96.6 kPa, respectively (Table 5). On the other hand, the total amount of injectable CO2 increased by up to 10.5 kt. That is, a 6.8% lower pressure increase was observed with 1 t of a surfactant solution (diluted in 100 m3 of water), compared to the baseline, and 8.1% more CO2 could be injected into the same reservoir. 4.1.3. Sensitivity analysis Next, we examined how the different permeability of the storage reservoir and the CO2 injection rate would influence the pressure buildup and the total CO2 injection. Permeability is one of the most critical reservoir properties that affect the pressure buildup, and it is not controllable. In contrast, the injection rate, one of the most influential operation factors, can be controlled. We first investigated the effect of reservoir permeability; our parametric analysis revealed that in all cases higher reservoir permeability results in lower pressure buildup and more CO2 injected. However, the impact of the pre-surfactant injection on the pressure buildup and the total amount of injected CO2 is more prominent for a reservoir with lower absolute permeability (Fig. 8). For example, with the maximum amount of injected surfactant, the pressure buildup associated with CO2 injection after 1 year was reduced to 92.9% of the baseline value, and the injected CO2 increased to 116.5% of the baseline value at the injection limit, for the reservoir with 80 md (Table 6 and Fig. 8). Therefore, it hints that the pre-surfactant injection could be more advantageous for a candidate reservoir with an unfavorable permeability condition. Next, we investigated the impact of the injection rate by applying three different numbers: base injection-rate (100 t/day), and two other cases with 50 t/day and 150 t/day (note: all other parameters are same). The higher CO2 injection rate resulted in a higher pressurebuildup and significantly lower CO2 storage. It is clear that the surfactant helps to maintain a lower pressure at the injection well compared to the baseline for all of these injection rates, and thus would contribute to the safer injection of more CO2, as summarized in Table 7 and Fig. 9. In particular, when a higher CO2-injection rate is needed, such as 150 t/day in our simulation, surfactant pre-injection may contribute significantly to the performance (e.g., 6.9% lower pressure buildup and 26.4% higher injected CO2, compared to the baseline in our simulation). From this sensitivity analysis, a clear observation was made that the surfactant is useful for improving injectivity, especially when the reservoir properties are not favorable or higher injection rates are needed. Therefore, surfactant injection before the main CO2 injection may contribute to maximizing the use of available pore spaces and also minimizing the risk of undesirable geomechanical failures at the same time. However, it should be noted that the percentages in Figs. 8 and 9 show only the relative improvement. The final storage capacities of those unfavorable conditions are less than those of the original case

Fig. 8. Effect of reservoir permeability on the storage capacity and pressure increase.

with the initial property input. 4.2. A pilot test site at Pohang 4.2.1. Surfactant injection and the size of altered zone Four different surfactant-injection scenarios were considered for the Pohang pilot project, as presented in Table 8. Unlike the simple onetenth grids used in the previous section, the surfactant solution is injected into the full-scale field with four different scenarios, namely Baseline (surfactant = 0 t), S1 (3 t), S2 (5 t), and S3 (20 t). The equivalent radius of the altered region varied from 13.7 m to 39.8 m (Table 8). 4.2.2. Impact on the injectivity Fig. 10 displays the evolution of pressure buildup caused by CO2 injection at the injection well. Baseline pressure was observed to be significantly different from those of other scenarios (S1, S2, and S3). The pressure at the well bottom was maintained below about ˜228 kPa for S1 and S2 scenarios and 125 kPa for S3 scenario compared to the baseline case (Table 9). Noticeably, the observation that the pressure buildup was alleviated proportional to the surfactant quantity for the simple grid system (Section 4.1) is not apparent anymore in the actual pilot test model. The time to reach the pressure limit was lengthened for all of these three scenarios, but again, it is not linearly correlated with the surfactant quantity (Fig. 10). Particularly, the least pressure buildup was observed for scenario S1, not S3. The maximum increase of CO2 storage capacity was obtained at around 114.6% (compared to the 140

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compared to the baseline. The comparison of these two different reservoir models also implies that the significance of pressure buildup by the pre-injection of surfactant solution would vary case by case depending on the hydrogeologic condition of the storage reservoir. To delve more into the effect of pre-pressure buildup by the surfactant injection, we examined BHP and storage capacity when ignoring the pressure buildup by the pre-injection (S1′, S2′ and S3′; summarized in Table 10). In comparison with Table 9, S1′ and S2′ showed 1.3% and 2.2% improvements in the storage capacity while the difference becomes noticeably large (7.9%) between S3′ and S3. And there is not a substantial difference in terms of BHP and total CO2 injected between S1′, S2′ and S3′. Therefore, the pressure buildup by the pre-injection of surfactant solution obviously would compromise the overall performance improvement of the pilot test site to some extent, with the most prominent effect in the largest injection of surfactant solution. In the following analysis, we compared the possible distribution of injected CO2 between the baseline and other scenarios at ten years after the termination of CO2 injection. The same amount of CO2 injection (12,717 t) was applied during this additional set of simulations to make a fair comparison between all four cases. Results are summarized in Fig. 11. In the baseline scenario, the CO2 migrated further in the SE direction along the monoclinal slope. With the surfactant pre-injection, the injected CO2 remained more locally around the injection well in all scenarios compared to the baseline (Fig. 11b, c, and d). This trend was more conspicuous for the S3 scenario (Fig. 11d). It implies that the largest amount of surfactant pre-injection (S3) resulted in the smallest CO2 plume, while the baseline scenario led to the farthest CO2 footprint. The assumptions reflected in the relative permeability curves can lead to two conflicting changes in the wellbore region. When CO2 occupies more pore spaces in this region, more presiding water is displaced, and consequently, CO2 migration might be retarded. On the other hand, the higher CO2 saturation results in the higher CO2 relative permeability, which might help CO2 propagate outwards faster. In the S3 scenario, the observed volume of an altered region is much greater than those of S1 and S2, by at least a factor of five (Table 8). Thus, we can anticipate that CO2 occupied far more pore spaces locally around the injection well, and subsequently, the smallest CO2 footprint developed. On the contrary, there is a relatively smaller number of grids with over 0.4 wt% surfactant in S1 and S2 scenarios, and it caused more CO2 to continue to migrate further, rather than maximizing the pore space occupancy near the injection well. Therefore, we can confirm that the surfactant pre-injection alters the spatial distribution of injected CO2 in the complex pilot storage formation. But, further investigation is needed to elucidate why the observed outcome does not correspond linearly to the quantity of surfactant used and what other reasons might be there in addition to the impact of the pre-injection. Let us adopt the Buckley-Leverett equation to explain why CO2 plume with the largest pre-injection of surfactant doesn’t spread more laterally even compared to the baseline. Fig. 12a illustrates fractional flow curves of the CO2 phase based on the relative permeabilities shown in Fig. 3. It was observed that the CO2-saturation values at the shock front (Sgf) were 0.215 and 0.465 in the unaltered and altered regions by

Fig. 9. Effect of CO2-injection rate on the storage capacity and pressure increase.

baseline) from scenario S1 as well. Let us describe more in detail the resultant pressure buildup during the injection: The well bottom-hole pressures in S1, S2 and S3 are initially higher by 27, 45 and 164 kPa, respectively, compared to the baseline scenario (initial pressure = 7,745 kPa) due to the pre-injection of surfactant solution, as shown in Fig. 10. Note that the impact of the pre-injection was almost negligible in the case of the theoretical flat horizontal reservoir probably due to its much larger size and higher permeability. On the other hand, when the reservoir size is limited and its permeability is not favorable, as the pilot test site in this study, the pre-pressure-buildup by the surfactant pre-injection turns out to be not trivial anymore. Even with that, however, the impact of improved injectivity seems to excel the side effect of the higher initial pressure caused by the surfactant pre-injection. For example, even the S3 scenario, in which the overall outcome is inferior to S1 and S2, yields the lower well bottom-hole pressure and the more capacity of CO2 storage,

Table 6 Effect of reservoir permeability on the bottom-hole pressure and CO2-storage capacity. Baseline

80 md 100 md 200 md

S1

S2

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

1,653 (100) 1,415 (100) 820 (100)

98.1 (100) 129.1 (100) 181.6 (100)

1,596 (96.6) 1,364 (96.4) 793 (96.7)

107.8 (109.9) 134.3 (104.0) 185.3 (102.0)

1,535 (92.9) 1,318 (93.1) 770 (93.9)

114.3 (116.5) 139.6 (108.1) 186.3 (102.6)

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Table 7 Effect of CO2-injection rate on the bottom-hole pressure and CO2-storage capacity. Baseline

50 t/day 100 t/day 150 t/day

S1

S2

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

Pressure buildup after 1 y [kPa] (%)

Total injected CO2 [kt] (%)

848 (100) 1,415 (100) 2,093 (100)

184.1 (100) 129.1 (100) 57.4 (100)

824 (96.9) 1,364 (97.2) 2,017 (98.4)

186.4 (101.2) 134.3 (104.0) 68.8 (120.0)

804 (94.8) 1,318 (93.1) 1,948 (93.1)

188.8 (102.5) 139.6 (108.1) 72.5 (126.4)

surfactant, respectively, at a particular time elapse (same volume of injected CO2). Fig. 12b displays the saturation profile of CO2 with distance from the injection well for the baseline and the enhanced scenarios. This difference suggests that CO2 propagates slower in the altered region compared to the untreated rock. The travel distance of CO2 did not reach even half of that in the unaltered region. In this regard, it can be conjectured that the retardation effect plays a vital role in S3 scenario where the considerable amount of surfactant is pre-injected. That is, although the higher CO2 saturation at the shock front and resulting retardation only occur in the altered radius in the limited distance from the injection well, it could yield an impact on the migration of entire CO2 plume. 4.2.3. Impact on the trapping mechanism Results shown in Figs. 11 and 12 help to understand the migration of CO2-plume in a complex storage formation with and without the surfactant pre-injection. We next investigate how this migration would affect the pressure buildup at the injection well. Injected CO2 can be stored by four trapping mechanisms in a saline aquifer, namely structural/stratigraphic-, residual-, solubility-, and mineral-trapping mechanisms (Bachu et al., 2007). The first three mechanisms were only considered during numerical simulations in this study. CO2 was injected at the lower part of the monoclinal structure, so it did not encounter any structural or stratigraphic barriers in this simulation; therefore, residual- and/or solubility-trapping mechanisms should prevail. The CO2 dissolution in the pre-existing formation water would be affected not only by the areal extent of injected CO2 propagation but also by the CO2-water contact area in a given volume. CO2 mass dissolved in brine during the simulation is summarized in Fig. 13. The total dissolved CO2 is higher in S1 and S2 scenarios compared to the baseline scenario, but the dissolved CO2 is distinctively lower in S3. Note that the baseline scenario had higher dissolved CO2 in brine than others until the termination of CO2 injection, which occurred earlier than other scenarios. We also conducted another set of simulations in which the CO2 solubility in brine is ignored to investigate its impact. As a result, total injected CO2 dramatically decreased. Baseline was most negatively affected, with a 29% decline from the condition that considers the solubility trapping (Table 11). Reduction in the storage capacity becomes less with the more pre-injection of surfactant solutions. It implies that the CO2 solubility and thus solubility trapping is more important when less surfactant solution is pre-injected. This analysis is consistent with our understanding that the dissolution of CO2 into the formation water helps to slow down the pore-

Fig. 10. Simulated well-bottom-hole pressure curves for various injection scenarios at the Pohang pilot project site.

Table 9 Comparison: total CO2 injection at the Pohang Basin pilot site.

Baseline S1 S2 S3

Pressure buildup when the baseline injection scenario terminates [kPa] (%)

Total injected CO2 [t] (%)

3,254.9 3,026.6 3,034.4 3,129.5

12,717 14,569 14,501 13,693

(100.0) (93.0) (93.2) (96.1)

(100.0) (114.6) (114.0) (107.7)

Table 10 Comparison: total CO2 injection at the Pohang Basin pilot site ignoring pressure buildup by pre-injection.

Baseline S1′ S2′ S3′

Pressure buildup when the baseline injection scenario terminates [kPa] (%)

Total injected CO2 [t] (%)

3,254.9 3,006.4 3,001.0 3,009.6

12,717 14,735 14,780 14,702

(100.0) (92.4) (92.2) (92.5)

(100.0) (115.9) (116.2) (115.6)

pressure buildup and increase the storage capacity in a given reservoir, as also observed in many previous studies (example: Gilfillan et al., 2009; Vilarrasa and Carrera, 2015). But we newly observed in this

Table 8 Surfactant-related inputs for the simulation of Pohang pilot site. Scenario

Mass of surfactant (t)

Volume of surfactant solution (m3)

Pore volume of altered region (m3)

Bulk volume of altered region (m3)

Equivalent radius (m)

Baseline S1 S2 S3

0 3 5 20

– 300 500 2,000

– 1,187 1,911 10,456

– 4,072 6,335 34,402

– 13.7 17.1 39.8

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Fig. 11. CO2-saturation profile of (a) Baseline at 10 years after termination of injection at the reservoir top and differences of CO2 saturation: (b) S1 and baseline, (c) S2 and baseline, and (d) S3 and baseline. (+) sign indicates that the surfactant-injection scenario contains more CO2 than the baseline in the area, while (-) sign denotes that the surfactant-injection scenario contains less CO2 than the baseline in the area.

additives, such as chemical surfactants, biosurfactants, or nanoparticles, before the main CO2 injection can cause a reduction in the capillary factor that consequently results in higher CO2 saturation (i.e., lower irreducible water saturation); which can improve the endpoint CO2 relative permeability, and the enhanced endpoint relative permeability of CO2 can lead to improving CO2 injectivity and storage capacity. In this study, the above strategy for improving CO2 injectivity and storage capacity by reducing the irreducible water saturation in a nearwell region was examined in depth. The effectiveness of the proposed method was explored through numerical simulations of a simplified flat aquifer and a pilot geologic storage site in South Korea. Salient observations are made as follows:

study that the relative contribution of solubility trapping would become less significant with the improved maximum CO2 saturation around the wellbore as a result of the surfactant pre-injection. In other words, injected CO2 would remain more locally around the injection well, which results in the smaller CO2 footprint and thus less interface between CO2 and pre-existing formation water. As a complementary analysis, we examined the pressure buildup and the total amount of CO2 injection when both CO2 solubility and pressure buildup by the surfactant pre-injection are neglected during the numerical simulation (Baseline″, S1″, S2″, and S3″; Fig. 14 and Table 12). Contrary to the previous results (Tables 9 and 10), the resultant BHPs and total CO2 injection are observed to be proportional to the surfactant injection. Therefore, the pre-injection of the surfactant solution, which leads to not only the improved CO2 saturation and permeability but also the slower pressure buildup near the wellbore, is associated with the solubility trapping and plays an essential role in the observed nonlinear response of the storage reservoir. In summary, the pre-injection of surfactant solution could improve the CO2 injectivity and the total CO2 storage capacity by inducing the slower pressure buildup and smaller CO2 footprint. Reduced pressure buildup and smaller footprint could also decrease the probability of leaks along any undetected faults and abandoned wells, fault reactivation, and/or induced seismicity (Kim et al., 2018a). However, the surfactant pre-injection could also increase the reservoir pressure before the main CO2 injection and might compromise the storage capacity particularly when an aquifer has a limited pore volume. Therefore, the volume of the surfactant solution to be pre-injected should be decided very carefully through an in-depth numerical simulation beforehand.

1 The potential advantage of the surfactant pre-injection before the main CO2 injection into an aquifer was evaluated by comparing pressure buildup at the injection well and total injected CO2 before reaching a pressure limit. From dynamic modeling using 2D crosssectional grids for a theoretical flat reservoir, it was evident that the addition of surfactant reduces the well-bottom-hole pressure buildup, with the effect being proportional to the quantity of surfactant. The simulation results also showed that more CO2 could be injected as a result of the reduced pressure buildup due to the lowered capillary factor with the surfactant pre-injection. 2 Two influential parameters, the intrinsic permeability of the reservoir and injection rate, were varied as a sensitivity analysis. It was observed that the surfactant improves the injectivity more effectively when the reservoir permeabilities or injection conditions are not favorable. 3 When a pilot test site that has more complex dipping geometry was simulated, the quantity of surfactant pre-injection and CO2 injectivity were found to be nonlinearly related. Rather than the largest injection of surfactant solution considered in this study, the most efficient scenario was the least injection of it - the pressure

5. Conclusions Among physical properties of a reservoir, relative permeability has a significant impact on the CO2 injectivity. Application of proper 143

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Table 11 Comparison: total CO2 injection at the Pohang Basin pilot site w/ and w/o CO2 solubility.

Baseline S1 S2 S3

Total injected CO2 w/ solubility trapping [t] (%)

Total injected CO2 w/o solubility trapping [t] (%)

12,717 14,569 14,501 13,693

9,027 (71.0) 10,897 (74.7) 10,882 (75.0) 10,577 (77.2)

(100.0) (100.0) (100.0) (100.0)

Fig. 14. Simulated well-bottom-hole pressure curves for various injection scenarios at the Pohang pilot project site, ignoring CO2 solubility and pressure buildup by the surfactant pre-injection. Table 12 Comparison of total CO2 injection at the Pohang Basin pilot site when the CO2 solubility and pressure buildup by surfactant pre-injection are neglected.

Fig. 12. (a) Fractional-flow functions derived from the relative permeabilitysaturation curves shown in Fig. 3. (b) CO2-saturation profiles with distance from the wellbore at a specific time.

Total injected CO2 [t] (%) Baseline Baseline″ S1″ S2″ S3″

12,717 (100.0) 9,027 (71.0) 11,018 (86.6) 11,093 (87.2) 11,284 (88.7)

and the contribution of trapping mechanisms in a subsurface formation with complex geometry. 4 The impact of surfactant pre-injection on the system pressure was almost negligible in case of the theoretical flat reservoir, probably due to its large size and high permeability. However, when the reservoir size is limited and its permeability is not favorable, as in the Pohang pilot test site, the pre-pressure-buildup by the surfactant pre-injection turns out to be non-trivial anymore. Therefore, the volume of the pre-injected surfactant solution should be decided very carefully when the proposed strategy is aimed for a small reservoir. Our numerical simulations help to support that the pre-injection of additives that are known to lower the residual saturation of water during CO2 invasion may contribute to improving the efficacy of available pore space usage in a storage reservoir. It may also help to lower the risk of undesirable geomechanical failures or leak by slowing down the pressure buildup and inducing smaller CO2 footprint. However, employed hypotheses involving relationships such as those between interfacial tension and maximum CO2 saturation, and between maximum CO2 saturation and relative permeability, need to be verified via appropriate laboratory-based experiments with specific additive

Fig. 13. Mass of dissolved CO2 with time in various surfactant-injection scenarios.

buildup was 7.0% lower, and the injection capacity was 14.6% higher compared to the baseline. This nonlinear relationship is ascribable to the various degree of retardation effect caused by the increased CO2 saturation near the wellbore, up-dip migration and smaller CO2 footprint, and less CO2 dissolution in formation water by the pre-injection of surfactant solution. The surfactant pre-injection was observed to substantially alter the CO2 plume migration 144

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types. And, the effect on pressure buildup shown in our study is somewhat limited, and thus more efforts are desired to find more convincing practical examples.

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