SPE Comparison of Chemical and Hysteresis CO 2 Trapping in the Nugget Formation 2. S. H. Behzadi, SPE, University of Wyoming

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1 SPE Comparison of Chemical and Hysteresis CO 2 Trapping in the Nugget Formation 2 S. H. Behzadi, SPE, University of Wyoming Copyright 2010, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in Florence, Italy, September This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract The Moxa Arch Anticline is a regional-scale northwest-trending uplift in western Wyoming and it has been chosen for CO 2 capture and storage. The Nugget Sandstone is a deep saline aquifer that has been a candidate for CO 2 storage. In this paper we compare the amount of mineral and solution trapping in comparison with dynamic hysteresis trapping based on compositional simulation. To the best of our knowledge this is the first paper to computationally assess the chemical trapping in the Nugget formation and to compare these three trapping mechanisms against each other. Reaction-path and kinetic modeling of CO 2 brine mineral reactions in the Nugget formation was investigated to probe the factors that affect capacity for CO 2 chemical trapping. The geochemical simulation of this system was explored in order to assess how mineralogy might change and the relative importance of mineral and solution trapping phenomena through time. Mineral trapping is simulated with both GWB and GEM-GHG. The maximum mineral trapping is 5 g of CO 2 per ton of reacted rock, and solution trapping is 3.47 g/kg rock. In comparison, a recent computational study of the Rose Run sandstone, Ohio indicates a much higher mineral trapping capacity, mainly because of reservoir pressure in addition to the presence of glauconite as an iron source for siderite formation. These results reveal that mineral trapping in the Nugget formation is not significant but that total chemical trapping might be much more than that of hysteresis trapping. Therefore, the contribution and importance of chemical trapping in CO 2 sequestration should be taken into account for assessment of CO 2 sequestration. Introduction This paper is extension to our former paper, SPE Much deeper depth is targeted here and also all trapping mechanisms are integrated in one simulator which means we can see the effect of different trapping mechanisms on each other. In addition, simulated mineral trapping with GEM-GHG, multiphase flow simulator, is compared with results of GWB, single phase simulator. CO 2 sequestration is becoming one of the hot topics cross all disciplines. Most of countries in the world are spending large amount of money to investigate CO 2 sequestration feasibility and shortcomings e.g. cap rock leakage. Underground formation became the target for CO 2 -sequestraion such as abundant oil and gas fields, coal bed methane and saline aquifer. The saline aquifers have the maximum capacity. For instance in North America, saline aquifers capacity is 8±4 Billion metric tons, around 94% of total capacity while the mature hydrocarbon reservoirs has 4% of total capacity (DOE and NETL, Carbon and Sequestration Atlas for the USA and Canada, 2008). All saline aquifers which have salinity above ppm are acceptable for CO 2 -sequestration based on U.S. Environmental Protection Agency. There have been a lot of researches on CO 2 -Sequestration in last decades all over the world; The Netherlands (Lohuis, 1993), Alberta basin, Canada (Bachu et al., 1994; Gunter et al., 2004; Cantucci et al., 2009), North Sea (Korbol and Kaddour, 1995) and USA (Zerai et al., 2006; Han et al., 2009). Once CO 2 is injected it might be trapped in different ways. Significant portion of CO 2 might be trapped beneath caprock if caprock

2 2 SPE integrity is not compromised. CO 2 can be dissolve in water which also donated as solubility trapping and also it might hydraulically trapped (hysteric trapping) and/or it might react with a rock and produce carbonate minerals (mineral trapping). Mineral trapping is the most stable trapping mechanism and there are a few studies examine the reaction of CO 2 with host rock. These studies are mostly done by geologist while engineers have generally probe the other trapping mechanisms. In fact, there is not robust interdisciplinary study that combines these two main disciplines and compares them. However, Nghiem (2009) simulated the trapping mechanisms with GEM software (CMG package). In this paper we simulate the solubility and hysteresis trapping and compare it with mineral trapping. The Duan (2006) solubility model is used to have more realistic estimation of CO 2 solubility in saline systems. The relative permeability data set are extracted from Bennion s (2008) measurements. In comparison with our former paper (Behzadi, 2010) the mineral trapping is much less while the dissolution trapping is more due to higher reservoir pressure. Numerical modeling Reservoir model We used a simple cubic model to estimate the amount of solution and hysteresis trapping in Nugget formation. It should be noticed that our objective was to compare different trapping mechanisms in Nugget formation rather than calculating the trapping amount in Nugget. The essential static reservoir data are provided in table 5, and figure 3 shows our 3D model. This model has three layers which were observed in wells and at Anschutz Ranch East field. Table 1, Reservoir static parameters. Parameter value Irreducible water saturation Porosity 0.09,0.13, 0.09 Gas endpoint relative permeability Water endpoint relative permeability 1 Critical gas saturation 0.05 Formation thickness (ft) 1000 Residual gas saturation 0.3 Salinity (ppm) Formation permeability (md) 1, 5, 1 Formation pressure (PSI) 5800 Temperature ( F) 200 Figure 1, Aquifer 3D model. Mineral trapping Geochemist s Workbench (GWB TM ) is geochemistry software which can simulate equilibrium, path of reaction, and kinetic modeling of CO 2 brine mineral reactions (Zerai et al., 2006). This software can simulate the reactions in equilibrium and kinetic conditions which enables us to consider the effect of time. However, it requires kinetic rate data. Equilibrium and path of reaction models are based on the thermodynamic data for the minerals involved in the reaction. The rate of reaction is calculated based on following equation. Table 2 shows the kinetic data that is employed in this simulation. Rate = dn i t = KA min exp E a RT Q K eq 1 (1)

3 SPE Table 2, minerals kinetic data. Mineral simulations Mineral Rate constants logk (mol/m 2 s) References Albite -11 Annite Calcite -5.8 Dolomite -6.7 Kaolinite K-feldspar Quartz Anhydrite Adopted from Zerai et al. (2006) and Cantucci et al. (2009) Chopping (internal report, 2009) used Random x-ray diffraction (XRD) technique to identify Nugget formation mineralogy from three samples. It consists quartz, feldspar, calcite and clay kaolinite. However, we used the Tensleep mineralogy composition since mineral relative abundance of Nugget formation has not been measured yet. James (1992) measured the composition of Tensleep. This data are presented in Table 3. Table 3, Tensleep mineral composition (adopted from James, 1992) used for Nugget formation. Vol.% Deterital grains Cements Qtz. Feld. Dol. Others Anh. Dol. Qtz. Cal. Others Low High Average Mean 63 1 tr tr tr tr The Tensleep brine formation was reported by Shiraki and Dunn (2000). This composition is employed an analogous to Nugget brine composition. Table 4, Brine chemical composition (adopted from Shiraki and Dunn, 2000). Mineral Na K Ca Mg Fe Mn Al Sr Ba Si Cl SO4 Concentration mmol/l Hysteresis trapping Bennion and Bachu (2008) did extensive study on drainage and imbibitions relative permeability relationships for acid gas/brine systems in sandstone, carbonate and anhydrite. The Viliking sandstone drainage relative permeability data is used for Nugget formation since it has closer static properties to Nugget formation s. Figure 2 shows the relative permeability used in this simulation. It is assumed the wetting phase does not have hysteric effect and its residual saturation is fixed to The gas residual saturation is 0.3.

4 4 SPE Relative permeability 0.6 Krw 0.4 Krg Sw Figure 2, Gas/Brine relative permeability (Bennion and Bachu, 2008) Wettability and capillary effects are responsible for gas trapping in porous medium. The gas trapping is simulated by Land s model (land 1968). In this model drainage and imbibitions cures follow the primary drainage and imbibitions curves. Therefore the trapped gas saturation is function of maximum gas saturation, land s constant. However, it is better to use modified Land s model i.g. Jerauld (1997) did comprehensive study on proper trapping model. 1 1 C = (2) S gt,max S g,max S gt S g = S g 1 + C S g.. (3) Solution trapping Dissolution of gas in brine is a function of temperature, pressure, and salinity (Chang et al., 1998; Nghiem et al., 2009). This phenomenon improve trapping amount. However it is affect other trapping mechanisms (Flett et al., 2004). For instance, as solution trapping increases the hysteresis trapping reduces. Therefore optimum trapping might not happen at maximum solution trapping. The solubility trapping of CO 2 in brine might not be predicted properly if we do not use Duan (Duan et al., 2006) model. This model is employed to predict the solubility trapping. CO 2 solubility in Nugget brine is calculated as a function of pressure and salinity, figure 2. For high salinity, and ppm, only sodium chloride is assumed in solution. The Duan (Duan et al, 2006) model is used for the calculation of the solubility of carbon dioxide in aqueous solutions containing Na +, K +, Ca 2+, Mg 2+, Cl -1 and SO -4 in a wide temperature, pressure and ionic strength range. ln (m CO2 ) = ln(y CO2 Ф CO2 P) - μ 1(0) CO2 /RT m SO4-2λ CO2-Na (m Na + m K + 2m Ca + 2m Mg ) -ζ CO2-Na-Cl m Cl (m Na + m K + m Ca + m Mg ) (2) where T is absolute temperature in Kelvin, P represents the total pressure of the system in bar, R is universal gas constant, m means the molality of components dissolved in water, y CO2 is the mole fraction of CO 2 in the vapor phase, Ф CO2 is the fugacity coefficient of CO 2, μ 1(0) CO2 is the standard chemical potential of CO 2 in the liquid phase, λ CO2-Na is the interaction parameter between CO 2 and Na +, ζ CO2-Na-Cl is the interaction parameter between CO 2 and Na +, Cl -. This simple equation requires iteration algorithem for calculation of Ф CO2 which may not be very interesting programming. However, Duan in 2006 offered an equation for calculation of Ф CO2. Ф CO2 = c 1 + [c 2 + c 3 T + c 4 /T + c 5 / (T 150)] P+ [c 6 + c 7 T + c 8 /T] P 2 + [c 9 + c 10 T + c 11 /T] ln (P) + [c 12 + c 13 T]/P+c 14 /T+ c 15 T 2 (3)

5 SPE where T is in Kelvin and P in bar.. They reproduce Ф CO2 over a wide T-P range with a single set of parameters as it was not feasible to employ only one set of parameters. Thus, they divided the T-P range into six sections and fit a set of parameters for each section (Duan et al, 2006). Table 5 lists the parameters for equation 3. The dissolution of carbon dioxide is simulated in an authors program which produces an adequate feed for GEM Table5, Parameter of equation 3 (adopted form Duan et al, 2006) Par T-P 1 a 2 b 3 c 4 d 5 e 6 f c E E E-01 c2 4.76E E E E E E-04 c3-3.36e e e E-07 c E-01 0 c c6-3.84e e e E E E-07 c E E E-10 c8 2.28E E E-04 0 c E-01 c E E E-05 c c c E c c E E E E E-07 a: 273 K < T < 573 K, P < P1 when T < 305 K, P1 equals to the saturation pressure of CO 2; when 305 K < T < 405 K, P1 = 75+(T-305)* 1.25 when T > 405 K, P1 = 200 bar b: 273 K <T <340 K, P1 <P < 1000 bar c: 273 K<T <340 K, P >1000 bar d: 340 K<T<435 K, P1 <P <1000 bar e: 340 K <T <435 K, P >1000 bar f: T >435 K, P >P1 1.5 CO2 solubility in brine (molality) Salinity Salinity eq Salinity eq Pressure (bar) Figure 3, Solubility of CO 2 in brine as function of pressure and salinity.

6 6 SPE Results Kinetic modeling is employed to understand evolution of the system through period of time. Dissolution and precipitation of minerals is function of their saturation index and their reaction rates. The CO 2 fugacity is fixed to bottom hole pressure and we tracked ph change. Dawsonite might not be precipitated based on dawsonite stability diagram, figure 4. Therefore, dawsonite was suppressed. However, some mineral might not precipitate in reality due to metastable situation. Thus different runs conducted to investigate various precipitation situations. The maximum mineral trapping is 5 g CO 2 per ton of rock. Table 6, Mineral trapping capacity for different suppressed scenarios. Scenario Suppressed Species Sequestered CO2 (g/ton Rock) Run 1 none Run 2 Gi, Ka, Al Run 3 Gi, Ka, Da,Al 0.18 Gi: Gibbsite (AlOH)3, Ka: Kaolinite (Al2Si2O5(OH)4), Al: Alunite (KAl3(SO4)2(OH)6), Da: Dawsonite (NaAlCO3(OH)2) log a NaHCO Al +++ Dawsonite Al(OH) Gibbsite C ph Simulation Sun Mar 21 Figure 1, Dawsonite stability diagram. Nghiem et al. (2009) and Flett et al. (2004) showed the residual gas trapping and solubility trapping are competitive. Therefore the optimum carbon storage by these mechanisms is function of their weighting factor. Here, the same weighting factor is used for both. However, it is appeared mineral and dissolution trapping can be competitive too. Water injection after CO 2 injection can enhance solubility and residual trapping, on the other hand, it can dissolve the precipitated minerals too. The maximum mineral trapping for this scheme is 5 g/ ton rock which reduces later on due to imbibition and its final mineral trapping is g/ ton rock. The evolution of chemical trapping is presented in figure 5. Dissolution can trap 50 times more than that of hysteresis while the share of hysteresis trapping is 2% and solubility 98%. The total injected gas is 0.11 g CO 2 /Kg rock, and 0.07 g CO 2 /Kg rock is sequestered by hysteresis. No CO 2 plume migration is observed. It is attributed to massive trapping and high reservoir pressure. Most part of injected CO 2 is trapped specially by dissolution which increases brine density; in addition, CO2 density is high due to enormous reservoir pressure, 52 lb/cu ft, while the mobile gas saturation is very low. Figure 6 shows gas saturation after 250 years.

7 SPE CO 2 is injected for 20 years and then water is injected continuously. Figure 5, Evolution of chemical trapping. Figure 6, CO 2 saturation at the end of injection time. Conclusions These results reveal that mineral trapping in the Nugget formation is not significant, especially if reservoir pressure is high. However, dissolution trapping is dominant trapping mechanism, 50 times more than hysteresis. Therefore, the contribution and importance of chemical trapping in CO 2 sequestration should be taken into account for assessment of CO 2 sequestration. Moreover, no plume migration was observed for this particular geological setting since most part of CO 2 is dissolved in brine and the mobile gas saturation is very low. Acknowledgement We would like gratefully acknowledge the CMG Ltd for use of their package. Nomenclature A min = reactive surface area. C = Land s constant. E a = activation energy. K = rate constant.

8 8 SPE K eq = equilibrium constant. n = number of moles. Q = activity product. R = gas constant. S g,max = maximum gas saturation. S gt,max = maximum trapped gas saturation. t = time. References Bachu, S., Gunter, W.D., Perkins, E.H Aquifer disposal of CO2: hydrodynamic and mineral trapping. Energy Convers. Manag. 35: Behzadi, S. H Comparison of Chemical and Hysteresis CO2 Trapping in the Nugget Formation SPE Reservoir. Paper SPE presented at Western Regional Meeting held in Anaheim, California, USA, May. Bennion, D. B. and Bachu, S Drainage and Imbibition Relative Permeability Relationship for Supercritical CO2/Brine and H2S/Brine Systems in Intergranular Sandstone, Carbonate, Shale and Anhydrite Rocks. SPE Reservoir Evaluation & Engineering 11 (3): Canucci, B., Giordano, M., Vaselli, O., Tassi, F., Quattrocchi, F., Perkins E. H Geochemical modeling of CO 2 storage in deep reservoir: Weyburn Project case study. Chemical Geology 256: Chang, Y., Coats, B. K. and Nolen, J. S A compositional model for CO 2 floods including CO2 solubility in water. SPE Reservoir Evaluation & Engineering 1 (2): Duan, Z., Sun, R. and Chou, I An improved model for calculation of CO 2 solubility in aqueous solution containing Na +, K +, Ca 2+, Mg 2+, Cl - and SO Marine Chemistry 98: Flett, M., Gurton R., and Taggart I The function of Gas Water Relative Permeability Hysteresis in the Sequestration of Carbon Dioxide in Saline Formation. Paper SPE presented at SPE Asia Pacific Oil and Gas Conference and Exhibition, Perth, Australia, October. Han, W. S. and McPherson B. J Optimizing geologic CO 2 sequestration by injection in deep saline formation below oil reservoir. Energy Convers. Manag. 50: James, W. C Sandstone Digenesis in mixed siliciclastic-carbonate sequence: Quadrant and Tensleep formations (Pennsylvanian), Northern Rocky Mountains. Journal of Sedimentary Petrology 62 (5): Jerauld, G. R General three-phase relative permeability model for Prudhoe Bay. SPE Reservoir Evaluation & Engineering 12 (4): Korbol, R., Kaddour, A Sleipner vest CO2 disposal-injection of removed CO2 into the Utsira Formation. Energy Convers. Manag. 36 (6 9): Land, C.S Calculation of Imbibition Relative Permeability for Two and Three-Phase Flow from Rock Properties. Soc. Pet. Eng. J. 8 (2): Lohuis, J.A.O., Carbon dioxide disposal and sustainable development in The Netherlands. Energy Convers. Manag. 34 (9 11): Nghiem, L., Yang, C., Shrivatava, V., Kohse, B., Hassam, M., Chen, D., and Card, C Optimization of Residual Gas and Solubility Trapping for CO2 Storage in Saline Aquifers. Paper SPE presented at SPE Reservoir Simulation Symposium, Woodland, Texas, 2-4 February. Shiraki, R. and Dunn, T. L Experimental study on water-rock interaction during CO 2 flooding in Tensleep Formation, Wyoming, USA. Applied Geochemistry 15: