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Optimization of well placement and operating conditions for various well patterns in CO2 sequestration in the Pohang Basin, Korea
International Journal of Greenhouse Gas Control 90 (2019) 102810
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Optimization of well placement and operating conditions for various well patterns in CO2 sequestration in the Pohang Basin, Korea Changhyeok Jun, Min Kim, Hyundon Shin
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Department of Energy Resources Engineering, INHA University, 100 Inha-Ro, Michuhol-Gu, Incheon 22212, Republic of Korea
A R T I C LE I N FO
A B S T R A C T
Keywords: CO2 sequestration Pohang Basin Storage capacity Well patterns Optimization
The aquifer consists of multi-layers and has pre-existing faults and heterogeneous reservoir properties that restrict CO2 injection to a certain amount. To store large amounts of CO2 and maintain storage security, it is important to define the optimal injection well pattern, placement, and operating conditions. This study applied various well patterns and optimized their locations and fluid injection rates with monitoring the pressure buildup in the aquifer to improve the storage capacity. Four well patterns in this study were employed: (1) a single vertical injection well (SVI), (2) two vertical injection wells (TVI), (3) a single horizontal injection well (SHI), and (4) two vertical wells for brine extraction and CO2 injection (TVEI). The results showed TVEI at the optimal location and fluid rate that allowed an almost eight times larger volume of CO2 to be stored compared to the base case (simulation result of SVI drilled for the CO2 storage pilot project in the Pohang basin, Korea), and maintained the pressure within the boundary for security. When using a single well (SVI and SHI), SVI injected 126 kton of CO2, which is larger than that of SHI, but storage security of SHI is better than that of SVI due to the difference in CO2 migration. Through this research, the effects of various well patterns in CO2 geological storage in the Pohang Basin can be forecasted and the optimal well pattern and conditions for the largest storage capacity can be determined.
1. Introduction As climate change by global warming becomes a severe problem worldwide, numerous efforts are being made to reduce carbon dioxide (CO2) emissions (IPCC, 2005). Carbon capture and storage (CCS) is a promising solution to reduce CO2 emissions on a large scale (IPCC, 2005). The process involves the capture of CO2 from industrial facilities and isolating it from the atmosphere by injecting into a storage formation (IEA, 2008). Geological storage is one of the measures for CO2 sequestration, and depleted oil and gas fields, deep saline aquifers, and coal-bed methane fields have attracted the most attention for storage (Bachu, 2000). Among the candidates, the most favorable formation is a deep saline aquifer because it is globally prevailing and has a huge capacity to store the captured gas (IPCC, 2005). South Korea is one of the countries with a heavy responsibility for CO2 emissions, producing approximately 600 million tons of CO2 in 2016, which is the ninth largest amount in the world and 1.68% of global emissions (Olivier et al., 2017). The government established a greenhouse gas reduction goal that involves a 30% reduction of emissions from the business-as-usual level by 2020, and strategies to achieve the goal over various industries are in progress (Kang et al., 2012). As
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one of the strategies, the Ministry of Trade, Industry and Energy launched a pilot CO2 storage project in 2013, and an offshore reservoir in the Pohang Basin was targeted because onshore basins in Korea are unsuitable to store CO2 (Lee et al., 2014). Currently, the pilot project is preparing the technical development and demonstration of CO2 storage for a largescale CCS project in Korea (Kwon, 2018). The target aquifer for CO2 sequestration has the geological characteristics of a multi-layered reservoir, heterogeneous reservoir properties, and pre-existing faults inside the pilot area that affects the CO2 storage capacity. The geological characteristics determine the migration and storage volume of CO2. In particular, the permeability and porosity near the wellbore have a strong influence on the injectivity (Bryant et al., 2006; Kumar et al., 2004; Yang et al., 2011). During CO2 injection, there is a rapid increase in formation pressure, which can reactivate pre-existing faults and generate fractures. Fracking occurs when the injection pressure reaches the fracture pressure of the formation, and the injected CO2 can leak through the induced fracture. The increase in pressure over the area also yields high pressures near the faults, and seismic activity or CO2 leakage can occur if the reactivation pressure is exceeded. Therefore, the injection process requires the optimal well pattern, placement and operating conditions to
Corresponding author. E-mail addresses: [email protected] (C. Jun), [email protected] (M. Kim), [email protected] (H. Shin).
https://doi.org/10.1016/j.ijggc.2019.102810 Received 11 January 2019; Received in revised form 10 July 2019; Accepted 9 August 2019 1750-5836/ © 2019 Elsevier Ltd. All rights reserved.
International Journal of Greenhouse Gas Control 90 (2019) 102810
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a 20 m × 20 m grid. The depth of the model was between 609 and 809 m, and there were slopes between 70–80° between the deepest area at the middle and the western and eastern areas, which drives CO2 to migrate to the sides due to buoyancy. The formation was approximately 40–50 m thick, and has an interbedded low-permeable layer, in which injected CO2 could barely flow at all. Therefore, CO2 injection was targeted to the two layers (Res3 and Res2) with a sufficient level of permeability. Res3 was located above the low-permeable layer, and Res2 was below the low-permeable layer (Fig. 2). The vertical thickness of Res3 and Res2 was approximately 10 m and 14 m, respectively, and both were divided vertically into 12 layers. For the vertical wells, most of the fluids could only flow through Res3 and Res2, even though the completion was set for the entire formation thickness. The optimization work was implemented for Res3 and Res2 because the completion of horizontal well should be conducted in a single layer. Table 1 presents the reservoir properties of each layer. Through a seismic survey, six faults were identified inside and at the boundary of the reservoir and are described in the model: two faults on the western side (WF1 and 2) and four faults on the eastern side (EF1, 2, 3, and 4) (Fig. 3a). No flow or leaking of fluids occurred at the faults with the initial condition because they were assumed to be non-active ones, but it might be reactivated by overpressure resulting from CO2 injection (Lee et al., 2017). Two aquifers placed in the north and south directions were assumed to be no-flow boundaries to estimate the CO2 storage capacity in a conservative manner. Fig. 3b displays the distribution of vertically averaged porosity over the reservoir. To define the well locations where the storage capacity is maximized, candidate zones with relatively higher porosity were selected. On the other hand, the northern area was excluded from the candidates because the fracture WF2 was too close to drill the area, even though it appeared to be favorable due to the concentration of high porosity. The two shaded squares indicate the candidate zones, where the coordinates are provided as parameters to the optimizer for the well location. The relative permeability in the simulation follows the curves in Fig. 4, which is from the result of special core analysis (SCAL) with the core from a gas reservoir adjacent to the Pohang Basin in the East Sea (Kim et al., 2018).
increase the storage capacity and at the same time, maintain storage security. Many studies have applied a range of well patterns and determined the optimal conditions through an optimization process to improve the CO2 storage capacity and efficiency by changing the trajectory or controlling the pressure build-up. Zhang and Agarwal (2012) analyzed a variety of injection strategies for vertical and horizontal wells to increase the CO2 storage efficiency and reduce its plume migration using a developed optimizer based on a genetic algorithm. The suggested optimal WAG (water alternating gas) operation decreased CO2 migration to the top by 14% compared to the injection only operation, and the results confirmed the better performance of the horizontal well in terms of injection safety. Cameron and Durlofsky (2012) mitigated the mobile CO2 fraction in the formation during geological injection and storage by optimizing the well placement, CO2 injection rate, and brine cycling. Optimization with the Hooke-Jeeves Direct Search (HJDS) algorithm sought the best well locations and injection rate to reduce CO2 migration to the top and increase immobile trapping. Cihan et al. (2015) presented a constrained differential evolution (CDE) algorithm for solving global optimization problems involving pressure management of geologic CO2 sequestration in a deep sandstone reservoir in the Southern San Joaquin Basin in California, USA. Jeong et al. (2018) considered pressure monitoring wells as one of the most cost-effective technologies for early leakage detection in CCS projects and studied optimal design of the pressure monitoring network to minimize leakage and monitoring costs. As for Pohang Basin, Hwang et al. (2016) analyzed the CO2 storage capacity using brine extraction from the formation with the optimal location of the brine extraction well and CO2 injection rate. In the study, by easing the pressure build-up, it was possible to increase the CO2 injection rate four-fold and the cumulative storage capacity by approximately 50% compared to the injection without the pressure relief. This study examined the application of various well patterns for CO2 sequestration in the Pohang Basin, and optimized the well placement and operating conditions to achieve the maximum storage capacity with respect to the four well patterns; a single vertical injection well (SVI), two vertical injection wells (TVI), a single horizontal injection well (SHI), and two vertical wells for brine extraction and CO2 injection (TVEI). The injection process was continued until the constraints reached the limit of the safety boundary, at which point, the fracture pressure of the formation was exceeded and the reactivation pressure of pre-existing faults was reached. The increase in injection and fault pressures were monitored, and the designed exploration and controlled evolution (DECE) optimizer in CMG’s CMOST was used to determine the optimal parameters that maximize the cumulative amount of injected CO2. The simulation results of the four different well patterns were analyzed in terms of the storage capacity, efficiency, and security.
2.2. Various well patterns The well patterns can have a different number of wells, different trajectories, and different purposes. The number of wells is one of the options for the different well patterns, and as more than one well is installed, the speed of the injection and production can be increased compared to the pattern with a single well. The trajectory of the well is changeable for special purposes or geological characteristics. A slanted or horizontal well can increase the area where the wellbore and reservoir formation is contacted, which has a direct impact on the injection mechanism. An additional well for different purposes, such as brine extraction well for brine production, is also applicable to provide a new storage volume for injected CO2. Many researchers have applied a range of well patterns for CO2 sequestration to enhance the storage capacity, such as a horizontal well and a brine extraction well for brine production, and the effects of each well pattern have been demonstrated. Injecting CO2 with a horizontal well secures a larger contact area between the CO2 plume and formation brine compared to a vertical well, and restricts the migration of the CO2 plume to the top, which may compromise the storage security (AlKhdheeawi et al., 2017). The effects of the well configuration on improving the storage capacity and trapping efficiency were examined. Adding a well for producing residual brine also has a substantial impact on the storage capacity. Brine extraction controls the influence of buoyancy and affects the pressure buildup and CO2 migration (Buscheck et al., 2011). Therefore, the brine extraction well allows the aquifer formation to provide a much larger volume for CO2 storage. In this study, four different well patterns (SVI, SHI, TVI, and TVEI)
2. Methods 2.1. Geological model of the Pohang Basin The Pohang Basin is located in the southeastern part of the Korean peninsula, and extends onshore and offshore in the East Sea (Fig. 1a). The analysis with cores from the offshore site proved that the lower part of the Pohang Basin has a favorable sandstone formation with a sufficient level of porosity and permeability, as well as a relatively impermeable caprock (Kim et al., 2013; Shinn et al., 2018). When the safety problem is considered, the site also had an advantage of a remote location from the residual areas. Therefore, the study area near Yeongil Bay was finally selected (Fig. 1b). To apply and optimize various well patterns in CO2 injection in the Pohang Basin, a geological model was developed based on the seismic survey and exploration well data from the Korea Institute of Geoscience and Mineral Resources (KIGAM) (Choi et al., 2017). The grid system of the model consisted of 152 × 95 × 36 grid cells, and the resolution was 2
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Fig. 1. Geological location of the Pohang Basin and the study area for the CCS pilot project (modified from Choi et al., 2017).
Fig. 2. Cross-section of the porosity distribution in the geological model and the target reservoirs.
wells is determined by the optimal location of the wells during the optimization process. The SHI needs to be installed in each target reservoir. Thus, it is divided into two cases: the SHI in Res3 and SHI in Res2 (Fig.5c). The SHI can secure a larger perforated area to inject more CO2 than through vertical wells, but it has only one reservoir for storage because it is disconnected from the other target reservoir. In the case of the SHI, placing the well at favorable vertical location and horizontal direction, as well as in the horizontal location is important. The optimization process searches the vertical and horizontal locations, and the direction of the SHI with a fixed well length of 500 m. TVEI is a well pattern installing both SVI and brine extraction well to inject CO2 and extract the residual brine of the reservoir at the same time (Fig. 5d). Depending on the location of the injection well, this study considers two cases of the TVEI pattern where one is fixing the location of the injection well at the same location as the base case, and the other is searching for the optimal location of the injection well and brine extraction well. Although the other well patterns only have the constraint of the injection and formation pressure to shut-in the wells, the TVEI has another constraint that stops both injection and brine extraction when the injected CO2 reaches the brine extraction well, which is called breakthrough, to prevent the production of CO2. The minimum bottom hole pressure at brine extraction was assumed to be 7 MPa.
Table 1 Properties for each reservoir in the geological model of the Pohang Basin.
Depth of top (m) Thickness (m) Average porosity Average permeability (mD) Vertical-horizontal permeability ratio Temperature (°C) Pressure at 750 m (MPa) Salinity (mol NaCl/Kg H2O) Fracture pressure (MPa) Reactivation pressure of faults (MPa)
Res3 (Upper reservoir)
Interbedded lowpermeable layer
Res2 (Lower reservoir)
746 12 0.157 67.5
758 28 0.071 0.849
786 18 0.204 32.4
0.1 55 7.5 0.1 14 13
were employed (Fig. 5). SVI is installed at a point in the candidate areas with the perforation over the entire thickness (Fig. 5a). The well injects CO2 at a certain injection rate through the entire perforated area but the target layers are Res3 and Res2 because the interbedded layer is a lowpermeable zone. In addition, base case is simulation result of SVI drilled for the CO2 storage pilot project in the Pohang basin, Korea. TVI has two perforation intervals over the entire thickness and injects CO2 through the area (Fig. 5b). The distance between the two
2.3. Optimization approaches In the optimization process, coordinates of the well location and the 3
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Fig. 3. Geological simulation model of the targeted aquifer; (a) 3D view of the geological model with preexisting faults and aquifers at the boundaries, (b) Top view of the model with the property of vertically averaged porosity and candidate sectors for well placement.
the wells are placed is an important factor for determining the injectivity and capacity. The larger volume to store CO2 and higher efficiency can then be obtained when the wells are in the most favorable area. The injection rate also needs to be considered for the maximum storage capacity. Generally, slower injection leads to the migration of mobile CO2 to the upper part of the formation (Spiteri et al., 2005), and the storage capacity increases with decreasing injection rate because the slower pressure build-up delays the injection well shutting down (Calabrese et al., 2005). Therefore, the operating condition needs to select the optimal injection rate to secure the largest volume for CO2 storage, preventing early shut-down by the high injection rate. The optimization process in this study was carried out using CMOST software of Computer Modelling Group (CMG), and CMG designed exploration and controlled evolution (DECE) optimizer was applied to solve the problem to determine the optimal well location and injection rate for four different well patterns. In the Designed Exploration, which is one of the stages of the DECE, the optimizer adopts the parameter values and generates simulation experiments through experimental design and Tabu search techniques. Fig. 6 presents the optimization process in a flow chart. The experiment employed a Latin Hypercube design to generate the initial experiments. For the additional experiments, the Tabu search technique reduces the search area. In the controlled evolution stage, through statistical analysis inspecting all the
Fig. 4. Relative permeability curves of the geological model in the Pohang Basin (Kim et al., 2018).
fluid rate were set as the optimization parameters to determine the conditions that maximize the storage capacity within the boundary of safe storage in the reservoirs. Because the geological model contains a heterogeneous distribution of reservoir properties, the location where
Fig. 5. Schematic diagram of the four well patterns and trajectories applied in the study for CO2 injection. 4
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Basin. The candidate areas for CO2 injection in the geological model are selected based on the areal distribution porosity. Only the points in the candidate areas are involved in the range of optimization parameters for the well location, and the injection rate ranges from 10 ton/day to 200 ton/day. In the case of the SHI, the optimization parameters include not only the areal location and rate, but also the direction of the well and vertical location. On the other hand, the TVEI pattern adds the location and fluid rate of the brine extraction well into the optimization parameters. The objective function of the optimization for all well patterns is the mass of cumulative CO2 injection into the entire reservoir. When the location and injection rate for the maximum storage capacity are defined, the optimal parameters and simulation results of the pattern are analyzed to suggest the optimal well pattern for the Pohang Basin. For four different well patterns, this procedure was followed to determine the optimal conditions, and the results were compared with each other. 2.4. Storage efficiency The storage efficiency of the different well patterns was also investigated. The residual trapping index (RTI) and solubility trapping index (STI) are the indices for the trapping efficiency of CO2 storage. Each RTI and STI indicates the portion of stored CO2 by residual trapping and solubility trapping, and the total efficiency index (TEI) is sum of the two indices (Nghiem et al., 2009). These indices were calculated using the following equations:
Fig. 6. Flowchart of optimization process to maximize the CO2 storage capacity.
candidate values, the optimizer improves the quality of the solutions (Yang et al., 2007). While the process is underway, the DECE algorithm checks the rejected candidate values to determine if the previous decisions are still valid, and prevents the process from being trapped in a local optimal solution (CMG, 2016; Al-Mudhafar et al., 2018). These characteristics allow DECE to handle both continuous and discrete parameters, which is suitable to finding the optimal injection rate and location in the heterogeneous area. In a variety of studies on reservoir problems, the optimizer has been used to find the best solutions corresponding to the objective functions that the researchers pursue, such as maximizing Net Present Value (NPV) in the WAG process and increasing oil recovery for the GasAssisted Gravity Drainage process (Jeong et al., 2014; Al-Mudhafar et al., 2018). The DECE has also been used in CO2 injection and storage in the Pohang Basin to solve the optimization problem of establishing the injection and relief well placement operating conditions, which provide the largest storage capacity (Hwang et al., 2016). The flowchart in Fig. 7 presents the overall procedure for the application of various well patterns in CO2 sequestration in the Pohang
RTI =
STI =
Total
mass of Total
CO2 stored by residual trapping mass of injected CO2
Total mass of CO2 stored by solubility trapping Total mass of injected CO2
TEI = STI + RTI
(1)
(2)
(3)
For all patterns, the indices were estimated at 50 years after the end of the injection. 3. Results This section presents the optimization results of CO2 sequestration simulation for the base case and the cases in which the four different well patterns were applied (Fig. 8 and Table 2). The results for each well pattern include the optimized location of the wells and the operating conditions to maximize the storage capacity. 3.1. Single vertical injection well (SVI) The optimized SVI injected CO2 at 70 ton/day for 4.9 years, and allowed the formation to store 125.9 kton of CO2, which is the largest amount the patterns where only the injection was conducted. The injection continued until the pressure at WF2 reached the reactivation limit through propagation of the pressure build-up around the well. The optimal well location was in the middle of Sector B and only 228 m away from the well location of the base case (Fig. 8a). Although Sector A appeared to have better potential to store CO2 due to the higher porosity distribution, the middle of Sector B was adopted as the best region to inject as much CO2 as possible within the boundary of the safe condition. This is because while the injection into Sector A makes the CO2 plume develop toward WF2 directly along the steepest slope, injection into Sector B drives the plume development in the opposite direction to WF2. This phenomenon by the geological slope slows the increase in pressure at WF2, which is the most critical constraint to stopping the injection.
Fig. 7. Overall procedure of application of various well patterns for CO2 sequestration with the optimization process. 5
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Fig. 8. Optimized well location of the four different well patterns in the geological model of the Pohang basin to maximize the CO2 storage capacity.
a similar plume shape and development to that of the SVI pattern. Because the effective constraint for this pattern is also the limit of pressure at WF2, the results of the optimized well locations confirm that the middle area of Sector B is the best place to delay the time for the pressure at WF2 to reach the reactivation pressure.
3.2. Two vertical injection wells (TVI) Different injection rates were assigned to each vertical well to maximize the cumulative CO2 injection; the total injection rate of the optimized case was 90 ton/day and the injection lasted for 3.8 years. The maximum allowable pressure at WF2 did not prevent injection until 124.9 kton of CO2 had been injected into the aquifer. The amount was less than the SVI pattern, but this pattern has the advantage of decreasing the time to inject CO2 compared to the other well patterns. As the optimized SVI was located in the middle of Sector B, the TVI was placed optimally in the middle area of the same sector. The distance between two wells in the TVI was only 256 m; this location makes
3.3. Single horizontal injection well (SHI) The cumulative CO2 injection in each optimization case targeting Res3 and Res2 were 124.7 kton and 121.4 kton, respectively. These amounts of CO2 could be injected with the SHI cases when the injection rate was 10 ton/day because a higher rate resulted in a too rapid
Table 2 CO2 injection performance of the simulation with the optimized cases for the four well patterns. Optimized cases of well patterns Simulation results
SHI Res3 Cumulative CO2 injection (kton) 120.5 125.9 124.9 124.7 Optimum injection rate (ton/day) 20 70 30 & 60 10 Injection time (years) 16.5 4.9 3.8 34.1 b Effective constraint Pressure at WF1 (reached reactivation pressure) Trapping efficiency at 50 years after the end of the injection Time of calculated trapping efficiency (years) 66.5 54.9 53.8 84.1 RTI (%) 38.62 39.34 39.37 37.93 STI (%) 18.85 17.54 17.96 20.33 TEI (%) 57.48 56.89 57.34 58.27 a b
Base case
SVI
TVI
Res2 121.4 10 33.2
TVEI (A)a 712.6 100 (140 for brine extraction) 19.5 CO2 breakthrough
(B)a 925.9 100 (150 for brine extraction) 25.4
83.2 37.41 20.21 57.62
69.5 38.24 13.64 51.88
75.4 33.94 12.32 46.26
(A) injection well at the location of Base case, (B) injection well at the optimized location. Effective constraint indicates the direct reason for the CO2 injection stopping. 6
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A total of 25.4 years was taken before the injection and brine extraction were stopped by CO2 breakthrough.
increase in formation pressure and shut-in much earlier than the maximized cumulative CO2 amount. Owing to the inevitable choice of the injection rate, the SHI pattern took the longest time to inject among the other well patterns. In both cases targeting different layers, the areal location of the two horizontal wells were optimized in Sector B, where the injection well could be prevented from shutting in earlier. As other well patterns acquired the optimal placement in Sector B, in this case, the location that had a positive impact on delaying pressure buildup at WF2 was selected. On the other hand, the direction and vertical location of the wells in the reservoir were determined by the permeability distribution. The favorable distribution of permeability improved the injectivity of the wells. In the case of Res3, the optimized horizontal well has a vertical location only approximately 3 m below the top because the bottom part of Res3 has poor permeability than the upper part. The horizontal well was optimized near the top of Res3 because the upper part with higher permeability is preferable to allow the injected CO2 to migrate and relieve the pressure buildup near the well. The vertical distribution of permeability was also highly influential on defining the vertical location of the well in Res2. Near the bottom, better injectivity was possible because of the favorable properties, and the optimized well was assigned 1 m above the bottom. As a result, permeability was found to be the most important factor determining the location of the wells.
4. Discussion 4.1. Optimal well pattern in Pohang Basin In the CO2 storage project, the optimal well pattern should be selected considering the reservoir conditions and the main purpose of the project. In terms of maximizing the cumulative CO2 injection, the TVEI pattern showed the best performance in improving the storage capacity, almost eight times larger, when the location of both the brine extraction and injection wells were optimized. Because the geological model is a closed system, where no fluid flow exists between the inside and outside of the model, the production of the residual brine was critical to provide new space for CO2 to be injected and stored. Furthermore, the optimized location of the brine extraction well reduced the pressure around WF2, which extended the time to inject CO2. Among the well patterns using only a single injection well, SVI at the optimal location and injection rate resulted in the highest storage capacity of 125.9 kton. The aquifer model was separated into two thin reservoirs by a low-permeable layer, and the injection was made more effectively into the two reservoirs with a vertical well than in the horizontal well into one reservoir, even though the completion area of the horizontal well was larger. In some studies, it was postulated that the accumulation of CO2 immediately under the seal at the top increases the risk to cause leakage or any other possible problems (Juanes et al., 2006; Noureldin et al., 2017). This possibility was not considered in this study, but it may be preferable to inject CO2 into the lower reservoir with a horizontal well if a geological storage project with multi-layered reservoir aims to prevent migration to the top. The case of SHI in Res2 showed the smallest cumulative CO2 injection because of the low porosity of the reservoir, but this case is most advantageous because it avoids buoyant CO2 migration to the top. The gas injected into Res2 develops its plume without moving to the top of the aquifer because of the interbedded low permeable layer (Fig. 9b), whereas in the case of injection into Res3, the CO2 plume is spread widely near the top.
3.4. Two vertical wells for brine extraction and CO2 injection (TVEI) The optimized TVEI pattern resulted in an even larger volume of CO2 stored without touching the reactivation pressure of the faults. The well placement of the case with the injection well location of the base case (Fig. 8f) performed 712.6 kton of CO2 storage, which is more than six times larger than the optimized cases of the other well patterns. CO2 breakthrough stopped the injection and brine extraction, and it took 19.2 years for the injected gas to reach the brine extraction well. 100 ton/day of CO2 and 140 ton/day of brine were found to be the optimal injection and brine extraction rate in this case, which is the best combination to decelerate the breakthrough and pressure increase at the faults. The optimized location of TVEI was at the farthest point from the injection well (Fig. 8f). As the two wells have the longest distance between them over the candidate area, the injected CO2 can migrate the longest distance. This migration makes it effective for the plume to develop and move against the slope of the geological model by the sufficient pressure difference, and to extend the time required for the pressure at the faults to reach their limit. The case with the additional optimization variable of the injection well location (Fig. 8) enhanced the storage amount of CO2 by more than 200 kton. As the distance between the wells was increased, the time for breakthrough to occur increased and more CO2 could be injected. The optimal injection rate was the same as the other TVEI case, but the brine extraction well needed to produce brine at 10 ton/day to further delay the pressure build-up at the farthest point than the previous case.
4.2. Optimal CO2 injection rate The injection rate should be considered, particularly in a multilayered formation, such as the Pohang Basin, where more than two layers with different geological properties are included. The response to the various injection rates was different from the single-layer formation. The cases of SVI and TWI optimized the injection rate not at the lowest rate, but at 70 and 90 ton/day each. This is because in a multilayered reservoir, an excessively low injection rate may prevent injection into the deeper layer, which has a higher formation pressure due to the smaller difference between the injection and formation pressure. On the other hand, the horizontal well patterns have the optimal injection rate at 10 ton/day to avoid rapid pressure buildup by the low
Fig. 9. CO2 mole fraction profiles (3-D cross-section) for SHI cases with well placement and plume development. 7
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influence the work reported in this paper.
injectivity. The injection and brine extraction rates of the TVEI pattern were optimized in a combination to inject as much CO2 as possible but not trigger CO2 breakthrough. As the location of the injection well was set as one of the optimization parameters, the distance between injection and brine extraction wells was increased, which resulted in an increase in brine extraction rate.
Acknowledgements This study was supported by the Korea Energy and Mineral Resources Engineering Program, Demonstration-scale Offshore CO2 Storage Project in Pohang Basin, Korea (20162010201980), and Development of State-of-the-Art Characterization and Assessment Methods for Shale Gas Plays in Western Canada (20178510030880) by The Ministry of Trade, Industry and Energy (MOTIE). The research was conducted through the Department of Energy Resources Engineering at Inha University, Korea.
4.3. Trapping efficiency The residual trapping index (RTI) and solubility trapping index (STI) describe the amount of CO2 stored in the formation in an immobile status to evaluate the storage security. The efficiency for each well pattern indicates the ratio calculated using Eqs. (1)–(3) at 50 years after the end of the injection (Table 2). STI and RTI are in a competing relationship where an increase in one trapping mechanism reduces the other because mobile gas in the formation can be trapped in only one mechanism. How the gas is trapped depends on the reservoir properties and operating conditions, such as permeability, residual gas saturation, wettability, salinity, and injection rate (Kumar et al., 2004; Nghiem et al., 2009; Kim et al., 2017). A small difference in TEI was noted in all the patterns except for the TVEI pattern; TVI made the largest amount of injected CO2 immobile by providing a larger contact area between the CO2 plume and formation for residual trapping. For the TVEI pattern, although this pattern injected enormous quantities of CO2, the solubility efficiency was much poorer than the other patterns. On the other hand, the residual trapping was relatively higher than the other patterns because brine production resulted in less of brine remaining in the formation, but allowed the expansion of the CO2 plume to enlarge the contact area with the formation to increase the RTI. A future study will evaluate a variety of injection and brine extraction strategies to overcome the low trapping efficiency of brine production.
References Al-Khdheeawi, E.A., Vialle, S., Barifcani, A., Sarmadivaleh, M., Iglauer, S., 2017. Influence of injection well configuration and rock wettability on CO2 plume behaviour and CO2 trapping capacity in heterogeneous reservoirs. J. Nat. Gas Sci. Eng. 43, 190–206. https://doi.org/10.1016/j.jngse.2017.03.016. Al-Mudhafar, W.J., Rao, D.N., Srinivasan, S., 2018. Robust Optimization of cyclic CO2 flooding through the gas-assisted gravity drainage process under geological uncertainties. J. Pet. Sci. Eng. 166, 490–509. https://doi.org/10.1016/j.petrol.2018.03. 044. Bachu, S., 2000. Sequestration of CO2 in geological media: criteria and approach for site selection in response to climate change. Energy Convers. Manage. 41 (9), 953–970. https://doi.org/10.1016/S0196-8904(99)00149-1. Bryant, S.L., Lakshminarasimhan, S., Pope, G.A., 2006. Buoyancy-dominated multiphase flow and its impact on geological sequestration of CO2. Presented at the SPE/DOE Symposium on Improved Oil Recovery. https://doi.org/10.2118/99938-MS. Buscheck, T.A., et al., 2011. Combining brine extraction, desalination, and residual-brine reinjection with CO2 storage in saline formations: implications for pressure management, capacity, and risk mitigation. Energy Procedia 4, 4283–4290. https://doi. org/10.1016/j.egypro.2011.02.378. Calabrese, M., Masserano, F., Blunt, M.J., 2005. Simulation of physical-chemical processes during carbon dioxide sequestration in geological structures. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/ 95820-MS. Cameron, D.A., Durlofsky, L.J., 2012. Optimization of well placement, CO2 injection rates, and brine cycling for geological carbon sequestration. Int. J. Greenh. Gas Control. 10, 100–112. https://doi.org/10.1016/j.ijggc.2012.06.003. Cihan, A., Birkholzer, J.T., Bianchi, M., 2015. Optimal well placement and brine extraction for pressure management during CO2 sequestration. Int. J. Greenh. Gas Control. 42, 175–187. https://doi.org/10.1016/j.ijggc.2015.07.025. Choi, B.Y., Shinn, Y.J., Park, Y.C., Park, J., Kwon, Y.K., Kim, K.Y., 2017. Simulation of CO2 injection in a small-scale pilot site in the Pohang Basin, Korea: effect of dissolution rate of chlorite on mineral trapping. Int. J. Greenh. Gas Control. 59, 1–12. https://doi.org/10.1016/j.ijggc.2017.02.001. CMG, 2016. User’s Guide (Version 2016.10). Computer Modelling Group Ltd., Calgary, AB, Canada. Hwang, J., Baek, S., Lee, H., Jung, W., Sung, W., 2016. Evaluation of CO2 storage capacity and injectivity using a relief well in a saline aquifer in Pohang Basin, offshore South Korea. Geosci. J. 20 (2), 239–245. https://doi.org/10.1007/s12303-015-0038-x. IEA, 2008. Energy Technology Analysis—CO2 Capture and Storage, Energy. https://doi. org/10.1087/9789264108820-en. IPCC (Intergovernmental Panel on Climate Change), 2005. IPCC Special Report on Carbon Dioxide Capture Storage. Cambridge University Press, Cambridge, UK. Jeong, M.S., Cho, J., Lee, K.S., 2014. Optimized WAG cycle and well pattern of CO2 EOR projects for maximum NPV in heterogeneous reservoirs. Presented at the TwentyFourth International Ocean and Polar Engineering Conference. Jeong, H., Sun, A.Y., Zhang, X., 2018. Cost-optimal design of pressure-based monitoring networks for carbon sequestration projects, with consideration of geological uncertainty. Int. J. Greenh. Gas Control. 71, 278–292. https://doi.org/10.1016/j.ijggc. 2018.02.014. Juanes, R., Spiteri, E.J., Orr Jr., F.M., Blunt, M.J., 2006. Impact of relative permeability hysteresis on geological CO2 storage. Water Resour. Res. 42 (12). https://doi.org/10. 1029/2005WR004806. Kang, S.I., Oh, J., Kim, H., 2012. Korea’s low-carbon green growth strategy. OECD Dev. Cent. Work. Pap. 310, 1–43. Kim, H., Song, I., Chang, C., Lee, H., Kim, T., 2013. Relations between physical and mechanical properties of core samples from the Bukpyeong and Pohang Basins. J. Eng. Geol. 23 (4), 329–340. https://doi.org/10.9720/kseg.2013.4.329. Kim, N.H., Jung, H.S., Kim, G.D., Jeong, H., Shin, H., Kwon, Y., Choe, J., 2018. The stability assessment of an aquifer in Pohang Yeongil bay due to CO2 injection. J. Eng. Geol. 28 (2), 183–192. https://doi.org/10.9720/kseg.2018.2.183. Kim, Y., Jang, H., Kim, J., Lee, J., 2017. Prediction of storage efficiency on CO2 sequestration in deep saline aquifers using artificial neural network. Appl. Energy 185, 916–928. https://doi.org/10.1016/j.apenergy.2016.10.012. Kumar, A., Noh, M., Pope, G.A., Sepehrnoori, K., Bryant, S., Lake, L.W., 2004. Reservoir simulation of CO2 storage in deep saline aquifers. Presented at the SPE/DOE Symposium on Improved Oil Recovery. https://doi.org/10.2118/89343-MS. Kwon, Y.K., 2018. Demonstration-scale offshore CO2 storage project in the Pohang Basin,
5. Conclusions This paper proposed the application of four different well patterns for CO2 sequestration into the Pohang Basin, and implemented an optimization process for each well pattern to maximize the cumulative CO2 injection under the safety boundary of injection and fault pressure. As a result, the optimal well location and injection rate were suggested, and the injection performance of the well patterns were compared to select the most suitable well pattern to achieve this purpose. The following presents the conclusions of this study. (1) The optimized location of the injection well for all well patterns was in Sector B, where it is in the middle of the model, which can delay the formation pressure reaching the reactivation pressure of the fault called the WF2. (2) TVEI allowed the optimal case to achieve the largest storage capacity, which was approximately eight times larger than the other well patterns. The injection and brine extraction rates were optimized at 100 and 150 ton/day each, and the wells were located with as long distance as possible in the candidate area. (3) The SVI injected 125.86 kton, which is the largest amount of CO2 the patterns without a brine extraction well. The optimal injection rate to secure the sufficient volume from the two target reservoirs was 70 ton/day. (4) For additional considerations regarding storage security, SHI is an effective well pattern preventing the upward-migration of CO2, and TVI is also an effective pattern providing higher efficiency than the other well patterns by increasing the amount of immobile CO2 in residual trapping. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to 8
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Shinn, Y.J., Kwon, Y.K., Yoon, J.R., Kim, B.Y., Cheong, S., 2018. Result of CO2 geological storage site survey for small-scale demonstration in Pohang Basin, Yeongil Bay, SE Korea. J. Pet. Sci. Eng. 28 (2), 161–174. https://doi.org/10.9720/kseg.2018.2.161. Spiteri, E., Juanes, R., Blunt, M.J., Orr, F.M., 2005. Relative-permeability hysteresis: trapping models and application to geological CO2 sequestration. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/ 96448-MS. Yang, C., Nghiem, L.X., Card, C., Bremeier, M., 2007. Reservoir model uncertainty quantification through computer-assisted history matching. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/109825-MS. Yang, F., Bai, B., Dunn-Norman, S., 2011. Modeling the effects of completion techniques and formation heterogeneity on CO2 sequestration in shallow and deep saline aquifers. Environ. Earth Sci. 64 (3), 841–849. https://doi.org/10.1007/s12665-0110908-0. Zhang, Z., Agarwal, R.K., 2012. Numerical simulation and optimization of CO2 sequestration in saline aquifers for vertical and horizontal well injection. Comput. Geosci. 16 (4), 891–899. https://doi.org/10.1007/s10596-012-9293-3.
Korea. J. Eng. Geol. 28 (2), 133–160. https://doi.org/10.9720/kseg.2018.2.133. Lee, G.H., Lee, B., Kim, H.J., Lee, K., Park, M.H., 2014. The geological CO2 storage capacity of the Jeju Basin, offshore southern Korea, estimated using the storage efficiency. Int. J. Greenh. Gas Control. 23, 22–29. https://doi.org/10.1016/j.ijggc.2014. 01.014. Lee, H., Shinn, Y.J., Ong, S.H., Woo, S.W., Park, K.G., Lee, T.J., Moon, S.W., 2017. Fault reactivation potential of an offshore CO2 storage site, Pohang Basin, South Korea. J. Pet. Sci. Eng. 152, 427–442. https://doi.org/10.1016/j.petrol.2017.03.014. Nghiem, L.X., Yang, C., Shrivastava, V.K., Kohse, B.F., Hassam, M.S., Chen, D., Card, C., 2009. Optimization of residual gas and solubility trapping for CO2 sequestration in saline aquifers. Presented at the SPE Reservoir Simulation Symposium. https://doi. org/10.2118/119080-MS. Noureldin, M., Allinson, W.G., Cinar, Y., Baz, H., 2017. Coupling risk of storage and economic metrics for CCS projects. Int. J. Greenh. Gas Control. 60, 59–73. https:// doi.org/10.1016/j.ijggc.2017.03.008. Olivier, J.G.J., Schure, K.M., Peters, J.A.H.W., 2017. Trends in Global CO2 and Total Greenhouse Gas Emissions. PBL Netherlands Environ. Assess. Agency.
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International Journal of Greenhouse Gas Control journal homepage: www.elsevier.com/locate/ijggc
Optimization of well placement and operating conditions for various well patterns in CO2 sequestration in the Pohang Basin, Korea Changhyeok Jun, Min Kim, Hyundon Shin
T
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Department of Energy Resources Engineering, INHA University, 100 Inha-Ro, Michuhol-Gu, Incheon 22212, Republic of Korea
A R T I C LE I N FO
A B S T R A C T
Keywords: CO2 sequestration Pohang Basin Storage capacity Well patterns Optimization
The aquifer consists of multi-layers and has pre-existing faults and heterogeneous reservoir properties that restrict CO2 injection to a certain amount. To store large amounts of CO2 and maintain storage security, it is important to define the optimal injection well pattern, placement, and operating conditions. This study applied various well patterns and optimized their locations and fluid injection rates with monitoring the pressure buildup in the aquifer to improve the storage capacity. Four well patterns in this study were employed: (1) a single vertical injection well (SVI), (2) two vertical injection wells (TVI), (3) a single horizontal injection well (SHI), and (4) two vertical wells for brine extraction and CO2 injection (TVEI). The results showed TVEI at the optimal location and fluid rate that allowed an almost eight times larger volume of CO2 to be stored compared to the base case (simulation result of SVI drilled for the CO2 storage pilot project in the Pohang basin, Korea), and maintained the pressure within the boundary for security. When using a single well (SVI and SHI), SVI injected 126 kton of CO2, which is larger than that of SHI, but storage security of SHI is better than that of SVI due to the difference in CO2 migration. Through this research, the effects of various well patterns in CO2 geological storage in the Pohang Basin can be forecasted and the optimal well pattern and conditions for the largest storage capacity can be determined.
1. Introduction As climate change by global warming becomes a severe problem worldwide, numerous efforts are being made to reduce carbon dioxide (CO2) emissions (IPCC, 2005). Carbon capture and storage (CCS) is a promising solution to reduce CO2 emissions on a large scale (IPCC, 2005). The process involves the capture of CO2 from industrial facilities and isolating it from the atmosphere by injecting into a storage formation (IEA, 2008). Geological storage is one of the measures for CO2 sequestration, and depleted oil and gas fields, deep saline aquifers, and coal-bed methane fields have attracted the most attention for storage (Bachu, 2000). Among the candidates, the most favorable formation is a deep saline aquifer because it is globally prevailing and has a huge capacity to store the captured gas (IPCC, 2005). South Korea is one of the countries with a heavy responsibility for CO2 emissions, producing approximately 600 million tons of CO2 in 2016, which is the ninth largest amount in the world and 1.68% of global emissions (Olivier et al., 2017). The government established a greenhouse gas reduction goal that involves a 30% reduction of emissions from the business-as-usual level by 2020, and strategies to achieve the goal over various industries are in progress (Kang et al., 2012). As
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one of the strategies, the Ministry of Trade, Industry and Energy launched a pilot CO2 storage project in 2013, and an offshore reservoir in the Pohang Basin was targeted because onshore basins in Korea are unsuitable to store CO2 (Lee et al., 2014). Currently, the pilot project is preparing the technical development and demonstration of CO2 storage for a largescale CCS project in Korea (Kwon, 2018). The target aquifer for CO2 sequestration has the geological characteristics of a multi-layered reservoir, heterogeneous reservoir properties, and pre-existing faults inside the pilot area that affects the CO2 storage capacity. The geological characteristics determine the migration and storage volume of CO2. In particular, the permeability and porosity near the wellbore have a strong influence on the injectivity (Bryant et al., 2006; Kumar et al., 2004; Yang et al., 2011). During CO2 injection, there is a rapid increase in formation pressure, which can reactivate pre-existing faults and generate fractures. Fracking occurs when the injection pressure reaches the fracture pressure of the formation, and the injected CO2 can leak through the induced fracture. The increase in pressure over the area also yields high pressures near the faults, and seismic activity or CO2 leakage can occur if the reactivation pressure is exceeded. Therefore, the injection process requires the optimal well pattern, placement and operating conditions to
Corresponding author. E-mail addresses: [email protected] (C. Jun), [email protected] (M. Kim), [email protected] (H. Shin).
https://doi.org/10.1016/j.ijggc.2019.102810 Received 11 January 2019; Received in revised form 10 July 2019; Accepted 9 August 2019 1750-5836/ © 2019 Elsevier Ltd. All rights reserved.
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a 20 m × 20 m grid. The depth of the model was between 609 and 809 m, and there were slopes between 70–80° between the deepest area at the middle and the western and eastern areas, which drives CO2 to migrate to the sides due to buoyancy. The formation was approximately 40–50 m thick, and has an interbedded low-permeable layer, in which injected CO2 could barely flow at all. Therefore, CO2 injection was targeted to the two layers (Res3 and Res2) with a sufficient level of permeability. Res3 was located above the low-permeable layer, and Res2 was below the low-permeable layer (Fig. 2). The vertical thickness of Res3 and Res2 was approximately 10 m and 14 m, respectively, and both were divided vertically into 12 layers. For the vertical wells, most of the fluids could only flow through Res3 and Res2, even though the completion was set for the entire formation thickness. The optimization work was implemented for Res3 and Res2 because the completion of horizontal well should be conducted in a single layer. Table 1 presents the reservoir properties of each layer. Through a seismic survey, six faults were identified inside and at the boundary of the reservoir and are described in the model: two faults on the western side (WF1 and 2) and four faults on the eastern side (EF1, 2, 3, and 4) (Fig. 3a). No flow or leaking of fluids occurred at the faults with the initial condition because they were assumed to be non-active ones, but it might be reactivated by overpressure resulting from CO2 injection (Lee et al., 2017). Two aquifers placed in the north and south directions were assumed to be no-flow boundaries to estimate the CO2 storage capacity in a conservative manner. Fig. 3b displays the distribution of vertically averaged porosity over the reservoir. To define the well locations where the storage capacity is maximized, candidate zones with relatively higher porosity were selected. On the other hand, the northern area was excluded from the candidates because the fracture WF2 was too close to drill the area, even though it appeared to be favorable due to the concentration of high porosity. The two shaded squares indicate the candidate zones, where the coordinates are provided as parameters to the optimizer for the well location. The relative permeability in the simulation follows the curves in Fig. 4, which is from the result of special core analysis (SCAL) with the core from a gas reservoir adjacent to the Pohang Basin in the East Sea (Kim et al., 2018).
increase the storage capacity and at the same time, maintain storage security. Many studies have applied a range of well patterns and determined the optimal conditions through an optimization process to improve the CO2 storage capacity and efficiency by changing the trajectory or controlling the pressure build-up. Zhang and Agarwal (2012) analyzed a variety of injection strategies for vertical and horizontal wells to increase the CO2 storage efficiency and reduce its plume migration using a developed optimizer based on a genetic algorithm. The suggested optimal WAG (water alternating gas) operation decreased CO2 migration to the top by 14% compared to the injection only operation, and the results confirmed the better performance of the horizontal well in terms of injection safety. Cameron and Durlofsky (2012) mitigated the mobile CO2 fraction in the formation during geological injection and storage by optimizing the well placement, CO2 injection rate, and brine cycling. Optimization with the Hooke-Jeeves Direct Search (HJDS) algorithm sought the best well locations and injection rate to reduce CO2 migration to the top and increase immobile trapping. Cihan et al. (2015) presented a constrained differential evolution (CDE) algorithm for solving global optimization problems involving pressure management of geologic CO2 sequestration in a deep sandstone reservoir in the Southern San Joaquin Basin in California, USA. Jeong et al. (2018) considered pressure monitoring wells as one of the most cost-effective technologies for early leakage detection in CCS projects and studied optimal design of the pressure monitoring network to minimize leakage and monitoring costs. As for Pohang Basin, Hwang et al. (2016) analyzed the CO2 storage capacity using brine extraction from the formation with the optimal location of the brine extraction well and CO2 injection rate. In the study, by easing the pressure build-up, it was possible to increase the CO2 injection rate four-fold and the cumulative storage capacity by approximately 50% compared to the injection without the pressure relief. This study examined the application of various well patterns for CO2 sequestration in the Pohang Basin, and optimized the well placement and operating conditions to achieve the maximum storage capacity with respect to the four well patterns; a single vertical injection well (SVI), two vertical injection wells (TVI), a single horizontal injection well (SHI), and two vertical wells for brine extraction and CO2 injection (TVEI). The injection process was continued until the constraints reached the limit of the safety boundary, at which point, the fracture pressure of the formation was exceeded and the reactivation pressure of pre-existing faults was reached. The increase in injection and fault pressures were monitored, and the designed exploration and controlled evolution (DECE) optimizer in CMG’s CMOST was used to determine the optimal parameters that maximize the cumulative amount of injected CO2. The simulation results of the four different well patterns were analyzed in terms of the storage capacity, efficiency, and security.
2.2. Various well patterns The well patterns can have a different number of wells, different trajectories, and different purposes. The number of wells is one of the options for the different well patterns, and as more than one well is installed, the speed of the injection and production can be increased compared to the pattern with a single well. The trajectory of the well is changeable for special purposes or geological characteristics. A slanted or horizontal well can increase the area where the wellbore and reservoir formation is contacted, which has a direct impact on the injection mechanism. An additional well for different purposes, such as brine extraction well for brine production, is also applicable to provide a new storage volume for injected CO2. Many researchers have applied a range of well patterns for CO2 sequestration to enhance the storage capacity, such as a horizontal well and a brine extraction well for brine production, and the effects of each well pattern have been demonstrated. Injecting CO2 with a horizontal well secures a larger contact area between the CO2 plume and formation brine compared to a vertical well, and restricts the migration of the CO2 plume to the top, which may compromise the storage security (AlKhdheeawi et al., 2017). The effects of the well configuration on improving the storage capacity and trapping efficiency were examined. Adding a well for producing residual brine also has a substantial impact on the storage capacity. Brine extraction controls the influence of buoyancy and affects the pressure buildup and CO2 migration (Buscheck et al., 2011). Therefore, the brine extraction well allows the aquifer formation to provide a much larger volume for CO2 storage. In this study, four different well patterns (SVI, SHI, TVI, and TVEI)
2. Methods 2.1. Geological model of the Pohang Basin The Pohang Basin is located in the southeastern part of the Korean peninsula, and extends onshore and offshore in the East Sea (Fig. 1a). The analysis with cores from the offshore site proved that the lower part of the Pohang Basin has a favorable sandstone formation with a sufficient level of porosity and permeability, as well as a relatively impermeable caprock (Kim et al., 2013; Shinn et al., 2018). When the safety problem is considered, the site also had an advantage of a remote location from the residual areas. Therefore, the study area near Yeongil Bay was finally selected (Fig. 1b). To apply and optimize various well patterns in CO2 injection in the Pohang Basin, a geological model was developed based on the seismic survey and exploration well data from the Korea Institute of Geoscience and Mineral Resources (KIGAM) (Choi et al., 2017). The grid system of the model consisted of 152 × 95 × 36 grid cells, and the resolution was 2
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Fig. 1. Geological location of the Pohang Basin and the study area for the CCS pilot project (modified from Choi et al., 2017).
Fig. 2. Cross-section of the porosity distribution in the geological model and the target reservoirs.
wells is determined by the optimal location of the wells during the optimization process. The SHI needs to be installed in each target reservoir. Thus, it is divided into two cases: the SHI in Res3 and SHI in Res2 (Fig.5c). The SHI can secure a larger perforated area to inject more CO2 than through vertical wells, but it has only one reservoir for storage because it is disconnected from the other target reservoir. In the case of the SHI, placing the well at favorable vertical location and horizontal direction, as well as in the horizontal location is important. The optimization process searches the vertical and horizontal locations, and the direction of the SHI with a fixed well length of 500 m. TVEI is a well pattern installing both SVI and brine extraction well to inject CO2 and extract the residual brine of the reservoir at the same time (Fig. 5d). Depending on the location of the injection well, this study considers two cases of the TVEI pattern where one is fixing the location of the injection well at the same location as the base case, and the other is searching for the optimal location of the injection well and brine extraction well. Although the other well patterns only have the constraint of the injection and formation pressure to shut-in the wells, the TVEI has another constraint that stops both injection and brine extraction when the injected CO2 reaches the brine extraction well, which is called breakthrough, to prevent the production of CO2. The minimum bottom hole pressure at brine extraction was assumed to be 7 MPa.
Table 1 Properties for each reservoir in the geological model of the Pohang Basin.
Depth of top (m) Thickness (m) Average porosity Average permeability (mD) Vertical-horizontal permeability ratio Temperature (°C) Pressure at 750 m (MPa) Salinity (mol NaCl/Kg H2O) Fracture pressure (MPa) Reactivation pressure of faults (MPa)
Res3 (Upper reservoir)
Interbedded lowpermeable layer
Res2 (Lower reservoir)
746 12 0.157 67.5
758 28 0.071 0.849
786 18 0.204 32.4
0.1 55 7.5 0.1 14 13
were employed (Fig. 5). SVI is installed at a point in the candidate areas with the perforation over the entire thickness (Fig. 5a). The well injects CO2 at a certain injection rate through the entire perforated area but the target layers are Res3 and Res2 because the interbedded layer is a lowpermeable zone. In addition, base case is simulation result of SVI drilled for the CO2 storage pilot project in the Pohang basin, Korea. TVI has two perforation intervals over the entire thickness and injects CO2 through the area (Fig. 5b). The distance between the two
2.3. Optimization approaches In the optimization process, coordinates of the well location and the 3
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Fig. 3. Geological simulation model of the targeted aquifer; (a) 3D view of the geological model with preexisting faults and aquifers at the boundaries, (b) Top view of the model with the property of vertically averaged porosity and candidate sectors for well placement.
the wells are placed is an important factor for determining the injectivity and capacity. The larger volume to store CO2 and higher efficiency can then be obtained when the wells are in the most favorable area. The injection rate also needs to be considered for the maximum storage capacity. Generally, slower injection leads to the migration of mobile CO2 to the upper part of the formation (Spiteri et al., 2005), and the storage capacity increases with decreasing injection rate because the slower pressure build-up delays the injection well shutting down (Calabrese et al., 2005). Therefore, the operating condition needs to select the optimal injection rate to secure the largest volume for CO2 storage, preventing early shut-down by the high injection rate. The optimization process in this study was carried out using CMOST software of Computer Modelling Group (CMG), and CMG designed exploration and controlled evolution (DECE) optimizer was applied to solve the problem to determine the optimal well location and injection rate for four different well patterns. In the Designed Exploration, which is one of the stages of the DECE, the optimizer adopts the parameter values and generates simulation experiments through experimental design and Tabu search techniques. Fig. 6 presents the optimization process in a flow chart. The experiment employed a Latin Hypercube design to generate the initial experiments. For the additional experiments, the Tabu search technique reduces the search area. In the controlled evolution stage, through statistical analysis inspecting all the
Fig. 4. Relative permeability curves of the geological model in the Pohang Basin (Kim et al., 2018).
fluid rate were set as the optimization parameters to determine the conditions that maximize the storage capacity within the boundary of safe storage in the reservoirs. Because the geological model contains a heterogeneous distribution of reservoir properties, the location where
Fig. 5. Schematic diagram of the four well patterns and trajectories applied in the study for CO2 injection. 4
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Basin. The candidate areas for CO2 injection in the geological model are selected based on the areal distribution porosity. Only the points in the candidate areas are involved in the range of optimization parameters for the well location, and the injection rate ranges from 10 ton/day to 200 ton/day. In the case of the SHI, the optimization parameters include not only the areal location and rate, but also the direction of the well and vertical location. On the other hand, the TVEI pattern adds the location and fluid rate of the brine extraction well into the optimization parameters. The objective function of the optimization for all well patterns is the mass of cumulative CO2 injection into the entire reservoir. When the location and injection rate for the maximum storage capacity are defined, the optimal parameters and simulation results of the pattern are analyzed to suggest the optimal well pattern for the Pohang Basin. For four different well patterns, this procedure was followed to determine the optimal conditions, and the results were compared with each other. 2.4. Storage efficiency The storage efficiency of the different well patterns was also investigated. The residual trapping index (RTI) and solubility trapping index (STI) are the indices for the trapping efficiency of CO2 storage. Each RTI and STI indicates the portion of stored CO2 by residual trapping and solubility trapping, and the total efficiency index (TEI) is sum of the two indices (Nghiem et al., 2009). These indices were calculated using the following equations:
Fig. 6. Flowchart of optimization process to maximize the CO2 storage capacity.
candidate values, the optimizer improves the quality of the solutions (Yang et al., 2007). While the process is underway, the DECE algorithm checks the rejected candidate values to determine if the previous decisions are still valid, and prevents the process from being trapped in a local optimal solution (CMG, 2016; Al-Mudhafar et al., 2018). These characteristics allow DECE to handle both continuous and discrete parameters, which is suitable to finding the optimal injection rate and location in the heterogeneous area. In a variety of studies on reservoir problems, the optimizer has been used to find the best solutions corresponding to the objective functions that the researchers pursue, such as maximizing Net Present Value (NPV) in the WAG process and increasing oil recovery for the GasAssisted Gravity Drainage process (Jeong et al., 2014; Al-Mudhafar et al., 2018). The DECE has also been used in CO2 injection and storage in the Pohang Basin to solve the optimization problem of establishing the injection and relief well placement operating conditions, which provide the largest storage capacity (Hwang et al., 2016). The flowchart in Fig. 7 presents the overall procedure for the application of various well patterns in CO2 sequestration in the Pohang
RTI =
STI =
Total
mass of Total
CO2 stored by residual trapping mass of injected CO2
Total mass of CO2 stored by solubility trapping Total mass of injected CO2
TEI = STI + RTI
(1)
(2)
(3)
For all patterns, the indices were estimated at 50 years after the end of the injection. 3. Results This section presents the optimization results of CO2 sequestration simulation for the base case and the cases in which the four different well patterns were applied (Fig. 8 and Table 2). The results for each well pattern include the optimized location of the wells and the operating conditions to maximize the storage capacity. 3.1. Single vertical injection well (SVI) The optimized SVI injected CO2 at 70 ton/day for 4.9 years, and allowed the formation to store 125.9 kton of CO2, which is the largest amount the patterns where only the injection was conducted. The injection continued until the pressure at WF2 reached the reactivation limit through propagation of the pressure build-up around the well. The optimal well location was in the middle of Sector B and only 228 m away from the well location of the base case (Fig. 8a). Although Sector A appeared to have better potential to store CO2 due to the higher porosity distribution, the middle of Sector B was adopted as the best region to inject as much CO2 as possible within the boundary of the safe condition. This is because while the injection into Sector A makes the CO2 plume develop toward WF2 directly along the steepest slope, injection into Sector B drives the plume development in the opposite direction to WF2. This phenomenon by the geological slope slows the increase in pressure at WF2, which is the most critical constraint to stopping the injection.
Fig. 7. Overall procedure of application of various well patterns for CO2 sequestration with the optimization process. 5
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Fig. 8. Optimized well location of the four different well patterns in the geological model of the Pohang basin to maximize the CO2 storage capacity.
a similar plume shape and development to that of the SVI pattern. Because the effective constraint for this pattern is also the limit of pressure at WF2, the results of the optimized well locations confirm that the middle area of Sector B is the best place to delay the time for the pressure at WF2 to reach the reactivation pressure.
3.2. Two vertical injection wells (TVI) Different injection rates were assigned to each vertical well to maximize the cumulative CO2 injection; the total injection rate of the optimized case was 90 ton/day and the injection lasted for 3.8 years. The maximum allowable pressure at WF2 did not prevent injection until 124.9 kton of CO2 had been injected into the aquifer. The amount was less than the SVI pattern, but this pattern has the advantage of decreasing the time to inject CO2 compared to the other well patterns. As the optimized SVI was located in the middle of Sector B, the TVI was placed optimally in the middle area of the same sector. The distance between two wells in the TVI was only 256 m; this location makes
3.3. Single horizontal injection well (SHI) The cumulative CO2 injection in each optimization case targeting Res3 and Res2 were 124.7 kton and 121.4 kton, respectively. These amounts of CO2 could be injected with the SHI cases when the injection rate was 10 ton/day because a higher rate resulted in a too rapid
Table 2 CO2 injection performance of the simulation with the optimized cases for the four well patterns. Optimized cases of well patterns Simulation results
SHI Res3 Cumulative CO2 injection (kton) 120.5 125.9 124.9 124.7 Optimum injection rate (ton/day) 20 70 30 & 60 10 Injection time (years) 16.5 4.9 3.8 34.1 b Effective constraint Pressure at WF1 (reached reactivation pressure) Trapping efficiency at 50 years after the end of the injection Time of calculated trapping efficiency (years) 66.5 54.9 53.8 84.1 RTI (%) 38.62 39.34 39.37 37.93 STI (%) 18.85 17.54 17.96 20.33 TEI (%) 57.48 56.89 57.34 58.27 a b
Base case
SVI
TVI
Res2 121.4 10 33.2
TVEI (A)a 712.6 100 (140 for brine extraction) 19.5 CO2 breakthrough
(B)a 925.9 100 (150 for brine extraction) 25.4
83.2 37.41 20.21 57.62
69.5 38.24 13.64 51.88
75.4 33.94 12.32 46.26
(A) injection well at the location of Base case, (B) injection well at the optimized location. Effective constraint indicates the direct reason for the CO2 injection stopping. 6
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A total of 25.4 years was taken before the injection and brine extraction were stopped by CO2 breakthrough.
increase in formation pressure and shut-in much earlier than the maximized cumulative CO2 amount. Owing to the inevitable choice of the injection rate, the SHI pattern took the longest time to inject among the other well patterns. In both cases targeting different layers, the areal location of the two horizontal wells were optimized in Sector B, where the injection well could be prevented from shutting in earlier. As other well patterns acquired the optimal placement in Sector B, in this case, the location that had a positive impact on delaying pressure buildup at WF2 was selected. On the other hand, the direction and vertical location of the wells in the reservoir were determined by the permeability distribution. The favorable distribution of permeability improved the injectivity of the wells. In the case of Res3, the optimized horizontal well has a vertical location only approximately 3 m below the top because the bottom part of Res3 has poor permeability than the upper part. The horizontal well was optimized near the top of Res3 because the upper part with higher permeability is preferable to allow the injected CO2 to migrate and relieve the pressure buildup near the well. The vertical distribution of permeability was also highly influential on defining the vertical location of the well in Res2. Near the bottom, better injectivity was possible because of the favorable properties, and the optimized well was assigned 1 m above the bottom. As a result, permeability was found to be the most important factor determining the location of the wells.
4. Discussion 4.1. Optimal well pattern in Pohang Basin In the CO2 storage project, the optimal well pattern should be selected considering the reservoir conditions and the main purpose of the project. In terms of maximizing the cumulative CO2 injection, the TVEI pattern showed the best performance in improving the storage capacity, almost eight times larger, when the location of both the brine extraction and injection wells were optimized. Because the geological model is a closed system, where no fluid flow exists between the inside and outside of the model, the production of the residual brine was critical to provide new space for CO2 to be injected and stored. Furthermore, the optimized location of the brine extraction well reduced the pressure around WF2, which extended the time to inject CO2. Among the well patterns using only a single injection well, SVI at the optimal location and injection rate resulted in the highest storage capacity of 125.9 kton. The aquifer model was separated into two thin reservoirs by a low-permeable layer, and the injection was made more effectively into the two reservoirs with a vertical well than in the horizontal well into one reservoir, even though the completion area of the horizontal well was larger. In some studies, it was postulated that the accumulation of CO2 immediately under the seal at the top increases the risk to cause leakage or any other possible problems (Juanes et al., 2006; Noureldin et al., 2017). This possibility was not considered in this study, but it may be preferable to inject CO2 into the lower reservoir with a horizontal well if a geological storage project with multi-layered reservoir aims to prevent migration to the top. The case of SHI in Res2 showed the smallest cumulative CO2 injection because of the low porosity of the reservoir, but this case is most advantageous because it avoids buoyant CO2 migration to the top. The gas injected into Res2 develops its plume without moving to the top of the aquifer because of the interbedded low permeable layer (Fig. 9b), whereas in the case of injection into Res3, the CO2 plume is spread widely near the top.
3.4. Two vertical wells for brine extraction and CO2 injection (TVEI) The optimized TVEI pattern resulted in an even larger volume of CO2 stored without touching the reactivation pressure of the faults. The well placement of the case with the injection well location of the base case (Fig. 8f) performed 712.6 kton of CO2 storage, which is more than six times larger than the optimized cases of the other well patterns. CO2 breakthrough stopped the injection and brine extraction, and it took 19.2 years for the injected gas to reach the brine extraction well. 100 ton/day of CO2 and 140 ton/day of brine were found to be the optimal injection and brine extraction rate in this case, which is the best combination to decelerate the breakthrough and pressure increase at the faults. The optimized location of TVEI was at the farthest point from the injection well (Fig. 8f). As the two wells have the longest distance between them over the candidate area, the injected CO2 can migrate the longest distance. This migration makes it effective for the plume to develop and move against the slope of the geological model by the sufficient pressure difference, and to extend the time required for the pressure at the faults to reach their limit. The case with the additional optimization variable of the injection well location (Fig. 8) enhanced the storage amount of CO2 by more than 200 kton. As the distance between the wells was increased, the time for breakthrough to occur increased and more CO2 could be injected. The optimal injection rate was the same as the other TVEI case, but the brine extraction well needed to produce brine at 10 ton/day to further delay the pressure build-up at the farthest point than the previous case.
4.2. Optimal CO2 injection rate The injection rate should be considered, particularly in a multilayered formation, such as the Pohang Basin, where more than two layers with different geological properties are included. The response to the various injection rates was different from the single-layer formation. The cases of SVI and TWI optimized the injection rate not at the lowest rate, but at 70 and 90 ton/day each. This is because in a multilayered reservoir, an excessively low injection rate may prevent injection into the deeper layer, which has a higher formation pressure due to the smaller difference between the injection and formation pressure. On the other hand, the horizontal well patterns have the optimal injection rate at 10 ton/day to avoid rapid pressure buildup by the low
Fig. 9. CO2 mole fraction profiles (3-D cross-section) for SHI cases with well placement and plume development. 7
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influence the work reported in this paper.
injectivity. The injection and brine extraction rates of the TVEI pattern were optimized in a combination to inject as much CO2 as possible but not trigger CO2 breakthrough. As the location of the injection well was set as one of the optimization parameters, the distance between injection and brine extraction wells was increased, which resulted in an increase in brine extraction rate.
Acknowledgements This study was supported by the Korea Energy and Mineral Resources Engineering Program, Demonstration-scale Offshore CO2 Storage Project in Pohang Basin, Korea (20162010201980), and Development of State-of-the-Art Characterization and Assessment Methods for Shale Gas Plays in Western Canada (20178510030880) by The Ministry of Trade, Industry and Energy (MOTIE). The research was conducted through the Department of Energy Resources Engineering at Inha University, Korea.
4.3. Trapping efficiency The residual trapping index (RTI) and solubility trapping index (STI) describe the amount of CO2 stored in the formation in an immobile status to evaluate the storage security. The efficiency for each well pattern indicates the ratio calculated using Eqs. (1)–(3) at 50 years after the end of the injection (Table 2). STI and RTI are in a competing relationship where an increase in one trapping mechanism reduces the other because mobile gas in the formation can be trapped in only one mechanism. How the gas is trapped depends on the reservoir properties and operating conditions, such as permeability, residual gas saturation, wettability, salinity, and injection rate (Kumar et al., 2004; Nghiem et al., 2009; Kim et al., 2017). A small difference in TEI was noted in all the patterns except for the TVEI pattern; TVI made the largest amount of injected CO2 immobile by providing a larger contact area between the CO2 plume and formation for residual trapping. For the TVEI pattern, although this pattern injected enormous quantities of CO2, the solubility efficiency was much poorer than the other patterns. On the other hand, the residual trapping was relatively higher than the other patterns because brine production resulted in less of brine remaining in the formation, but allowed the expansion of the CO2 plume to enlarge the contact area with the formation to increase the RTI. A future study will evaluate a variety of injection and brine extraction strategies to overcome the low trapping efficiency of brine production.
References Al-Khdheeawi, E.A., Vialle, S., Barifcani, A., Sarmadivaleh, M., Iglauer, S., 2017. Influence of injection well configuration and rock wettability on CO2 plume behaviour and CO2 trapping capacity in heterogeneous reservoirs. J. Nat. Gas Sci. Eng. 43, 190–206. https://doi.org/10.1016/j.jngse.2017.03.016. Al-Mudhafar, W.J., Rao, D.N., Srinivasan, S., 2018. Robust Optimization of cyclic CO2 flooding through the gas-assisted gravity drainage process under geological uncertainties. J. Pet. Sci. Eng. 166, 490–509. https://doi.org/10.1016/j.petrol.2018.03. 044. Bachu, S., 2000. Sequestration of CO2 in geological media: criteria and approach for site selection in response to climate change. Energy Convers. Manage. 41 (9), 953–970. https://doi.org/10.1016/S0196-8904(99)00149-1. Bryant, S.L., Lakshminarasimhan, S., Pope, G.A., 2006. Buoyancy-dominated multiphase flow and its impact on geological sequestration of CO2. Presented at the SPE/DOE Symposium on Improved Oil Recovery. https://doi.org/10.2118/99938-MS. Buscheck, T.A., et al., 2011. Combining brine extraction, desalination, and residual-brine reinjection with CO2 storage in saline formations: implications for pressure management, capacity, and risk mitigation. Energy Procedia 4, 4283–4290. https://doi. org/10.1016/j.egypro.2011.02.378. Calabrese, M., Masserano, F., Blunt, M.J., 2005. Simulation of physical-chemical processes during carbon dioxide sequestration in geological structures. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/ 95820-MS. Cameron, D.A., Durlofsky, L.J., 2012. Optimization of well placement, CO2 injection rates, and brine cycling for geological carbon sequestration. Int. J. Greenh. Gas Control. 10, 100–112. https://doi.org/10.1016/j.ijggc.2012.06.003. Cihan, A., Birkholzer, J.T., Bianchi, M., 2015. Optimal well placement and brine extraction for pressure management during CO2 sequestration. Int. J. Greenh. Gas Control. 42, 175–187. https://doi.org/10.1016/j.ijggc.2015.07.025. Choi, B.Y., Shinn, Y.J., Park, Y.C., Park, J., Kwon, Y.K., Kim, K.Y., 2017. Simulation of CO2 injection in a small-scale pilot site in the Pohang Basin, Korea: effect of dissolution rate of chlorite on mineral trapping. Int. J. Greenh. Gas Control. 59, 1–12. https://doi.org/10.1016/j.ijggc.2017.02.001. CMG, 2016. User’s Guide (Version 2016.10). Computer Modelling Group Ltd., Calgary, AB, Canada. Hwang, J., Baek, S., Lee, H., Jung, W., Sung, W., 2016. Evaluation of CO2 storage capacity and injectivity using a relief well in a saline aquifer in Pohang Basin, offshore South Korea. Geosci. J. 20 (2), 239–245. https://doi.org/10.1007/s12303-015-0038-x. IEA, 2008. Energy Technology Analysis—CO2 Capture and Storage, Energy. https://doi. org/10.1087/9789264108820-en. IPCC (Intergovernmental Panel on Climate Change), 2005. IPCC Special Report on Carbon Dioxide Capture Storage. Cambridge University Press, Cambridge, UK. Jeong, M.S., Cho, J., Lee, K.S., 2014. Optimized WAG cycle and well pattern of CO2 EOR projects for maximum NPV in heterogeneous reservoirs. Presented at the TwentyFourth International Ocean and Polar Engineering Conference. Jeong, H., Sun, A.Y., Zhang, X., 2018. Cost-optimal design of pressure-based monitoring networks for carbon sequestration projects, with consideration of geological uncertainty. Int. J. Greenh. Gas Control. 71, 278–292. https://doi.org/10.1016/j.ijggc. 2018.02.014. Juanes, R., Spiteri, E.J., Orr Jr., F.M., Blunt, M.J., 2006. Impact of relative permeability hysteresis on geological CO2 storage. Water Resour. Res. 42 (12). https://doi.org/10. 1029/2005WR004806. Kang, S.I., Oh, J., Kim, H., 2012. Korea’s low-carbon green growth strategy. OECD Dev. Cent. Work. Pap. 310, 1–43. Kim, H., Song, I., Chang, C., Lee, H., Kim, T., 2013. Relations between physical and mechanical properties of core samples from the Bukpyeong and Pohang Basins. J. Eng. Geol. 23 (4), 329–340. https://doi.org/10.9720/kseg.2013.4.329. Kim, N.H., Jung, H.S., Kim, G.D., Jeong, H., Shin, H., Kwon, Y., Choe, J., 2018. The stability assessment of an aquifer in Pohang Yeongil bay due to CO2 injection. J. Eng. Geol. 28 (2), 183–192. https://doi.org/10.9720/kseg.2018.2.183. Kim, Y., Jang, H., Kim, J., Lee, J., 2017. Prediction of storage efficiency on CO2 sequestration in deep saline aquifers using artificial neural network. Appl. Energy 185, 916–928. https://doi.org/10.1016/j.apenergy.2016.10.012. Kumar, A., Noh, M., Pope, G.A., Sepehrnoori, K., Bryant, S., Lake, L.W., 2004. Reservoir simulation of CO2 storage in deep saline aquifers. Presented at the SPE/DOE Symposium on Improved Oil Recovery. https://doi.org/10.2118/89343-MS. Kwon, Y.K., 2018. Demonstration-scale offshore CO2 storage project in the Pohang Basin,
5. Conclusions This paper proposed the application of four different well patterns for CO2 sequestration into the Pohang Basin, and implemented an optimization process for each well pattern to maximize the cumulative CO2 injection under the safety boundary of injection and fault pressure. As a result, the optimal well location and injection rate were suggested, and the injection performance of the well patterns were compared to select the most suitable well pattern to achieve this purpose. The following presents the conclusions of this study. (1) The optimized location of the injection well for all well patterns was in Sector B, where it is in the middle of the model, which can delay the formation pressure reaching the reactivation pressure of the fault called the WF2. (2) TVEI allowed the optimal case to achieve the largest storage capacity, which was approximately eight times larger than the other well patterns. The injection and brine extraction rates were optimized at 100 and 150 ton/day each, and the wells were located with as long distance as possible in the candidate area. (3) The SVI injected 125.86 kton, which is the largest amount of CO2 the patterns without a brine extraction well. The optimal injection rate to secure the sufficient volume from the two target reservoirs was 70 ton/day. (4) For additional considerations regarding storage security, SHI is an effective well pattern preventing the upward-migration of CO2, and TVI is also an effective pattern providing higher efficiency than the other well patterns by increasing the amount of immobile CO2 in residual trapping. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to 8
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Shinn, Y.J., Kwon, Y.K., Yoon, J.R., Kim, B.Y., Cheong, S., 2018. Result of CO2 geological storage site survey for small-scale demonstration in Pohang Basin, Yeongil Bay, SE Korea. J. Pet. Sci. Eng. 28 (2), 161–174. https://doi.org/10.9720/kseg.2018.2.161. Spiteri, E., Juanes, R., Blunt, M.J., Orr, F.M., 2005. Relative-permeability hysteresis: trapping models and application to geological CO2 sequestration. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/ 96448-MS. Yang, C., Nghiem, L.X., Card, C., Bremeier, M., 2007. Reservoir model uncertainty quantification through computer-assisted history matching. Presented at the SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/109825-MS. Yang, F., Bai, B., Dunn-Norman, S., 2011. Modeling the effects of completion techniques and formation heterogeneity on CO2 sequestration in shallow and deep saline aquifers. Environ. Earth Sci. 64 (3), 841–849. https://doi.org/10.1007/s12665-0110908-0. Zhang, Z., Agarwal, R.K., 2012. Numerical simulation and optimization of CO2 sequestration in saline aquifers for vertical and horizontal well injection. Comput. Geosci. 16 (4), 891–899. https://doi.org/10.1007/s10596-012-9293-3.
Korea. J. Eng. Geol. 28 (2), 133–160. https://doi.org/10.9720/kseg.2018.2.133. Lee, G.H., Lee, B., Kim, H.J., Lee, K., Park, M.H., 2014. The geological CO2 storage capacity of the Jeju Basin, offshore southern Korea, estimated using the storage efficiency. Int. J. Greenh. Gas Control. 23, 22–29. https://doi.org/10.1016/j.ijggc.2014. 01.014. Lee, H., Shinn, Y.J., Ong, S.H., Woo, S.W., Park, K.G., Lee, T.J., Moon, S.W., 2017. Fault reactivation potential of an offshore CO2 storage site, Pohang Basin, South Korea. J. Pet. Sci. Eng. 152, 427–442. https://doi.org/10.1016/j.petrol.2017.03.014. Nghiem, L.X., Yang, C., Shrivastava, V.K., Kohse, B.F., Hassam, M.S., Chen, D., Card, C., 2009. Optimization of residual gas and solubility trapping for CO2 sequestration in saline aquifers. Presented at the SPE Reservoir Simulation Symposium. https://doi. org/10.2118/119080-MS. Noureldin, M., Allinson, W.G., Cinar, Y., Baz, H., 2017. Coupling risk of storage and economic metrics for CCS projects. Int. J. Greenh. Gas Control. 60, 59–73. https:// doi.org/10.1016/j.ijggc.2017.03.008. Olivier, J.G.J., Schure, K.M., Peters, J.A.H.W., 2017. Trends in Global CO2 and Total Greenhouse Gas Emissions. PBL Netherlands Environ. Assess. Agency.
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