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Christopher P. Paolini Computational Science Research Center San Diego State University CO 2 Capture and Sequestration COMP696 Thursday November 10, 2011.

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Presentation on theme: "Christopher P. Paolini Computational Science Research Center San Diego State University CO 2 Capture and Sequestration COMP696 Thursday November 10, 2011."— Presentation transcript:

1 Christopher P. Paolini Computational Science Research Center San Diego State University CO 2 Capture and Sequestration COMP696 Thursday November 10, 2011 · 4:00 PM – 5:15 PM · SLHS 201

2  Frio Brine Pilot experimental location is 30 miles northeast of Houston, in the South Liberty oilfield.  1,600 tons of CO 2 were injected into a mile- deep well in October  Injection well is 5,753 feet deep.  Injection zone is from 5,053 to 5,073 feet.  Injection Zone is a brine-sandstone system with a top seal of 200 feet of Anahuac shale.  Injection began on October 4, and ran for several days.  Location is representative of the subsurface from coastal Alabama to Mexico.

3  Chemical analysis performed after several days.  U-shaped tube with an opening at the bottom is fed into the well.  High pressure N 2 is pumped into one side of the tube which forces reservoir gasses and fluids from the bottom up and into the other side.  ORNL and LLBL performed an analyses using a chromatograph.

4  Significant findings: injected CO 2 causes the brine at depth to become acidic.  Acidic brine dissolves some of the rock and minerals it comes into contact with, adding iron and other metals to the salt water.  Acidic brine can also allow the brine/CO 2 mixture to open new pathways through the sandstone rock and shale cap (via calcite dissolution).  Y.K. Kharaka, D.R. Cole, S.D. Hovorka, W.D. Gunter, K.G. Knauss and B.M. Freifeld, Gas-water-rock interactions in Frio Formation following CO2 injection: Implications for the storage of greenhouse gases in sedimentary basins, Geology; July 2006; v. 34; no. 7; p

5  Theory: rapid dissolution of calcite CaCO 3 and iron oxyhydroxides (Fe(OH) 3 ) is caused by low pH values of the brine coming into contact with injected ScCO 2 :  Fear: rapid mineral dissolution could create pathways in rock seals and well cements that could permit unwanted leakage of CO 2 and brine.  Brine leakage containing dissolved toxic species (Fe, Mn) into an overlying drinking water supply poses a health hazard.  Mobilization of toxic organic compounds (benzene, toluene) poses an environmental hazard.

6  Water samples from Frio Brine Pilot experiment showed a pH decrease before the arrival of a high concentration of bicarbonate ions (HCO 3 - ).  The purpose of our study was to develop a reactive transport modeling (RTM) code that could simulate the injection of CO 2 charged water and show this pH drop and help provide an explanation for it.  Simulation of reservoir far from injection well; model interaction between the formation water and CO 2(aq) charged effluent. (Y.K. Kharaka et al., 2006) (Havorka and Knox, 2002)

7 Model the chemical interaction between solutes in water and minerals, mediated by water (solvent) Mineral reactions: dissolution and precipitation Solve a kinetic mechanism that governs mineralization rate (dependence on water composition, mineral surfaces and shape, temperature) Speciation among solutes (complexation reactions) Solve for solute concentration assuming thermodynamic equilibrium, i.e. CO 2(g) + H 2 O  H 2 CO 3 H 2 CO 3  H + + HCO - 3 HCO 3 −  CO 3 2− + H + H 2 O  OH − + H + Transfer of solutes through connecting pores: advection (solute moving with water) diffusion (solute moving through water)

8 Evolution of chemical elemental mass depends on mass-transfer from diffusive and advective forces as well as the precipitation and dissolution of minerals governed by kinetic reaction rates Elemental mass rate of change term: rate of increase of concentration of a solute atom β in a fluid element Advective term: net rate of flow of solute activity out of a fluid element due to advective forces Diffusive term: net rate of increase of solute activity in a fluid element due to diffusive forces Source term: net rate of the increase or decrease of a mineral in a fluid element due to chemical kinetics (Park, in Revision, AJS) β solute atom index α aqueous solute species index γ mineral index ρ γ mineral solid molar density

9 Reference: National Energy Technology Laboratory, Department of Energy, rage.html Depth and Temperature Surface temperature Resident water properties Injectant water properties Lithology properties

10  Diffusivity is a solute specific property that depends on ion size, charge, and complexity of shape.  Our model uses solute specific, temperature adjusted diffusivity values. TempD H + (m 2 /sec) D Fe ++ (m 2 /sec) E E E E E E-09 (Li and Gregory, 1974) H+H+ OH - SiO 2(aq) K+K+ CO 2(aq) HCO 3 - CO 3 -2 Na + Al(OH) 3(aq) Ca +2 TcTc TfTf D1.6e-49.7e-53.8e-53.6e-52.7e-52.3e-51.7e-52.5e-52.0e-51.5e-5 Fe +2 Mg e-5 Values listed for D are computed at T=65°C (Boudreau, 1997) D H + is an order of magnitude greater than D HCO 3 -

11 CO 2(aq) Injection 100m Sandstone  1D horizontal simulation (T = 20°C to 120°C).  CO 2(aq) injected at seepage velocities v s of 100, 200, 300, 400, and 500 [cc/(cm 2 yr)]/φ over 5 years.  The sandstone and formation water was modeled after the Frio Formation Pilot experiment.  The CO 2 -rich injectant water was modeled as a mixture of the formation water and a 0.5M solution of CO 2(aq)  Iron as tracer with 5x the molarity (non reactive). Mineral Molecular Formula Volume FractionGrain Radius, mm Quartz SiO K-Feldspar KAlSi 3 O Anorthite CaAl 2 Si 2 O Albite NaAlSi 3 O Calcite CaCO Kaolinite Al 2 Si 2 O 5 (OH) SoluteFormation WaterCO 2 -rich Injectant Water H+H+ 2.6x x10 -5 CO 2 (aq) total 0.002total 0.5 HCO 3 - CO 3 -2 Ca Al(OH) 3 1.7x10 -6 K+K+ 5.0x10 -5 SiO 2(aq) Na Cl Fe x x10 -6 Mg x x10 -5 Lithological properties of sandstone used in our Frio formation model. Initial molar concentrations of solutes used to model the Frio formation and injectant water compositions.

12 Calculate flow field of CO 2 in a saline reservoirs or geologic formation. A reservoir is modeled as a porous medium of specified dimension Length L [m] Cross section of area A [m 2 ] Positive direction of flow Volumetric flow rate Q: Κ: permeability [m 2 ] μ: dynamic viscosity [kg/(m∙s)] Ratio called “mobility” “Darcy Flux” has units of velocity [m/s] P 2 [Pa] P 1 [Pa]

13  Characterizes the capacity of a medium to transfer a fluid.  Different geologic formations will have different permeability values since permeability is dependent on grain size.  Permeability decreases as grain size decreases.  Labeled κ, has units of area [m 2 ] or (more traditionally) millidarcy (mD)  Medium having a permeability of 1 darcy will allow passage of a fluid with flux = 1 cc/(cm 2 s) where the fluid has a viscosity μ=1 centipoise (cP) and the fluid is subjected to a ∇P=1 atm/cm.  Formations with κ ≤ 100mD form seal rock  Seals needed to contain sequestered CO 2

14  Characterizes a fluid’s resistance to flow when subjected to a force  Labeled μ, has units of Pas or (more traditionally) centipoise (cP) = 1 millipascal-second  Constant of proportionality between shear stress and a velocity gradient  Fluid having a dynamic viscosity of 1 cP will be displaced, in one second, a distance equal to the thickness of the fluid between the two plates if one of the plates is subjected to a shear stress of one millipascal.  H o C has an dynamic viscosity of 1 cP. shear stress

15  Characterizes the capacity of a geologic material to store a fluid.  Labeled φ, is a dimensionless number [0,1] and is computed by the ratio of void space to total volume  Determined by the spaces between the individual grains in the rock medium that forms a reservoir.  Porosity decreases as the individual grains that form a rock are packed more tightly together.  Function of the shape of grains, as well as the range of grain sizes present. Our simulator currently only supports the modeling of grains as spherical objects (research opportunity).  Note that a geologic material can be highly porous and still have low permeability. Why? Low effective porosity because voids are unconnected which restricts fluid movement. Pumice Sandstone

16  The average pore water velocity or seepage velocity is the ratio of Darcy flux and porosity:  Has units of [m/s]  Only a fraction of the total volume of a geologic material is available for fluid transport. Rock TypePorosity % Granite Dolerite Sandstone Shale Limestone Dolomite Quartzite  Notice that, for a constant flux, as porosity decreases, the seepage velocity increases.  The porosity (as a percentage) of some selected rock types is shown in the table to the right.  The seepage velocity is the velocity a tracer species like Fe ++ would experience if carried by resident H 2 O through a reservoir.

17 TOUGHREACT is a program for non-isothermal reactive fluid flow and geochemical transport in geologic media. It is developed by introducing reactive geochemistry into the framework of the existing multi-phase fluid and heat flow code TOUGH2 V2. Developed by Tianfu Xu, Eric Sonnenthal, Nicolas Spycher,and Karsten Pruess at Lawrence Berkeley National Laboratory

18  On, invoke wget tar xf template.tar cd template emacs (or vi) chemical.inp  Add the necessary aqueous species under the 'PRIMARY AQUEOUS SPECIES‘ header  Add the necessary aqueous complexes under the 'AQUEOUS COMPLEXES‘ header  Add the necessary water mixture data under the 'INITIAL AND BOUDARY WATER TYPES‘ header  Invoke TOUGHREACT using the command./treact12_eos2  Concentration profiles will be output to prob1_conc.dat  Use MATLAB to plot concentration of H +,HCO 3 -,CO 3 2-,Fe 2+,CO 2(aq) v. time.

19 'DEFINITION OF THE GEOCHEMICAL SYSTEM' 'PRIMARY AQUEOUS SPECIES' 'h2o' 'h+' 'ca+2' 'mg+2' 'na+' 'k+' 'fe+2' 'sio2(aq)' 'hco3-' 'so4-2' 'alo2-' 'cl-' 'o2(aq)' '*' Start of input chemical.inp file Start of Primary Aqueous species section This section provides a list of aqueous species to use in the simulation. Each species must be on a new line and in single quotes. The aqueous species needs to also be in the database file (specified in Solute.inp). Each mineral has a set of aqueous species (also listed in the database file ‘databas1.dat’) that must be included in this list. Additional species can also be included, but the minerals aqueous species are required. Marks end of primary aqueous species section

20  'AQUEOUS COMPLEXES'  'oh-'  'al+3'  'halo2(aq)'  'naalo2(aq)'  'aloh+2'  'al(oh)2+'  'al(oh)3(aq)'  'naoh(aq)'  'naco3-'  'h3sio4-'  'fe+3'  'hs-'  'h2s(aq)'  'ch4(aq)'  'h2(aq)'  'acetic~acid(aq)'  'so2(aq)'  'hso3-'  '*' Start of Aqueous Complexes section in chemical.inp file This section provides a list of aqueous complexes to use in the simulation. A complex is either an ion or an electrically neutral molecule formed by the union of simpler substances (as compounds or ions) and held together by chemical (not physical) forces that depend on properties of atomic structure. Possible aqueous complexes must have its primary aqueous species defined in the 'PRIMARY AQUEOUS SPECIES' section and also be defined in the chemical database file. If you wish, this section can be omitted from the simulation and the possible aqueous complexes will automatically be generated. Marker to denote the of the aqueous complexes section

21 Forward rate constant Pre-exponential factor. Given for each reaction. Activation energy. Given for each reaction.

22 'MINERALS' 'calcite' 'quartz' e e e '*' NAMIN: Mineral name as defined in database file IKIN: indicates type of mineral 0: mineral at equilibrium 1: mineral under kinetic constraints IDISPRE: indicates kinetic constraints. 0: if IKIN = 0 1: dissolution only 2: precipitation only 3: both Not used, leave at 0 Coefficient k25, rate constant at 25C 0 = pH dependent rate constant, not considered. 1 = records 9-3 must include information on rate dependence on pH EA = Activation energy (kJ/mol) Dissolution parameters Precipitation parameters Initial volume fraction to be assumed for calculating initial effective surface area if the mineral is not present at the start of the simulation End of mineral record

23 'GASES' '*' 'SURFACE COMPLEXES' '*' 'species with Kd and decay decay constant(1/s)' '*' 0.0d0 'EXCHANGEABLE CATIONS' ' master convention ex. coef.' '*' These sections are not used in this assignment, but need to be included in the chemical.inp file for TOUGHREACT to run.

24 'INITIAL AND BOUDARY WATER TYPES' 1 0 !niwtype, nbwtype = number of initial and boundary waters !iwtype initial, temp (C) ' icon guess ctot ' 'h2o' E E+01 ' ' 0.0 'h+' E E-01 ' ' 0.0 'ca+2' E E-02 ' ' 0.0 'mg+2' E E-04 ' ' 0.0 'na+' E E+00 ' ' 0.0 'alo2-' E E-07 ' ' 0.0 'cl-' E E+01 ' ' 0.0 'o2(aq)' E E-01 ' ' 0.0 '*' ' ' 0.0 Number of initial (formation) waters Number of boundary (injection) waters Water number (initial waters are always first) Water Temperature Aqueous species in mixture ICON: flag to indicate constraint on input concentrations 1: ctot represents total moles of species 2: the total concentration of the species will be adjusted such that the saturation index (log(Q/K)) of mineral or gas NAMEQ equals QKSAT. 3: input values of CTOT represent the known activity of the specific species. ICON=4: the total concentration of the species is adjusted to yield a charge balance. CGUESS: initial guess for the concentration of the individual primary species (not total concentration), in moles/kg H2O CTOT: if ICON=1, CTOT is total moles of aqueous species, and total amount (in kg) of liquid water for H2O. Molalities are then internally computed as CTOT i /CTOT H2O. Leave as is ***Note*** All species defined in the 'PRIMARY AQUEOUS SPECIES‘ section must be included here.

25 'INITIAL MINERAL ZONES' 1 !nmtype= number of mineral zones 1!imtype 'mineral vol.frac.' 'calcite' 'quartz' E e-1 0 '*' Number of mineral zones (layers) Mineral zone number Mineral Name. It must be included in the mineral section of the input file. Initial volume fraction of the mineral, IKIN: A flag for the type of mineral, 0: mineral under equilibrium 1: mineral under kinetic constraints This line is required when IKIN=1 RAD: radius of mineral grain (in m) used to calculate surface area for initial formation of secondary phase. AMIN: specific reactive surface area. Its unit depends on the following flag IMFLG IMFLG: A flag for surface area conversion IMFLG = 0 for cm 2 /g mineral IMFLG = 1 for m 2 rock area/m 3 medium IMFLG = 2 for m 2 /m 3 mineral

26 ' ' 'INITIAL gas ZONES' 1 !ngtype= number of gas zones 1 !igtype 'gas partial pressure' !at 25 C equil w/ water 'co2(g)' 1.0E-02 ! Background Pco2 '*' 0.0 ' ‘ ' ' 'INITIAL gas ZONES' 0 !ngtype= number of gas zones '*' ' ‘ Number of gas zones Number of this particular gas zone Name of gaseous species Partial Pressure of the gaseous species For the simulation, no gas is being injected so use the configuration below:

27 'Permeability-Porosity Zones' 1 'perm law a-par b-par tcwM1' E E+00 ' ' 'INITIAL SURFACE ADSORPTION ZONES' 0 !ndtype= number of sorption zones 'zone total ad.sites (mol/l)' ' if Sden=0 Kd store retardation factor' 'INITIAL LINEAR EQUILIBRIUM Kd ZONE' 1!kdtpye=number of Kd zones 1!idtype 'species solid-density(Sden,kg/dm**3) Kd(l/kg=mass/kg solid / mass/l' '*' ' if Sden=0 Kd store retardation factor' 'INITIAL ZONES OF CATION EXCHANGE' 0 !nxtype= number of exchange zones 'zone ex. capacity' ' ' 'end' For the rest of the configuration, there is no need to change anything:

28  We developed an AJAX (Web based) application for simulating water-rock interaction that allows a user to define, run, and view the results of injecting CO 2 charged water in deep brine aquifers:  This tool was used to configure the Frio Brine Pilot experiment and simulate geochemical effects of CO 2 injection over a 5 year period.  A temperature and advection rate dependence on front separation distance was observed by using this application.

29  Access via URL and  Supports Google Chrome (recommended), Mozilla Firefox, and Apple Safari.  Does not work with Internet Explorer!  Login with your assigned username and password

30  After logging in, you will be presented with a drag-and- drop desktop showing the simulations you have configured and invoked to date.

31  The first step in configuring a simulation is to select the minerals you will be using to define one or more lithologies.  The first problem we will investigate is the injection of H 2 O with a high concentration (0.5M) of aqueous CO 2 into a single lithology having resident H 2 O with a CO 2 concentration of 0.002M.  Our single lithology will be sandstone made with the 9 minerals shown.

32  The user interface (UI) will present one with all atomically feasible kinetic (relatively slow) reactions, based on the minerals chosen in the minerals tab.  For our first problem, simply select all available reactions and click the Use Theoretical Reactions button.  One can chose empirically derived kinetic reaction data for selected minerals, but we will not use this feature for now.

33  Equilibrium reactions are relatively fast reactions that reach thermodynamic equilibrium on a much shorter time scale compared with kinetic reactions that involve the interaction of H 2 O with rock.  These reactions involve the dissolution or evolution of solutes.  For our first problem, choose reactions that control the concentration of CO 2 and the hydroxide, bicarbonate, and acetate anions.

34  In the Solutes tab, the UI lists for the user the possible species that may exist at some time in the resident H 2 O as H 2 O reacts with minerals in rock.  For our first problem, select all solutes shown in the UI.

35  The Simulation Controls tab allows a user to configure certain parameters that affect how a simulation will execute.  For our first problem, leave all the default values in place, except for the system orientation and the tortuosity model. This parameter controls how diffusion is modeled in free and porous media.  Our configuration is Horizontal: Sandstone

36  Resident H 2 O refers to the H 2 O residing in the rock prior to injection. Since we will be defining two different H 2 O compositions, one for the resident water and one for the injectant water, enter 2 for the total number of water compositions to use.  Configure Water 1 as the resident water with the concentrations given in the image to the right.

37  Injectant H 2 O refers to the CO 2 rich H 2 O we will be sequestering in the reservoir.  Configure Water 2 as the injectant water with the concentrations given in the image to the right.

38  A lithology describes the macroscopic properties of a geologic rock formation.  For our first problem, we will be injecting into a sandstone lithology composed of the nine minerals chosen in the minerals tab.  Define a sandstone lithology with the volume fraction and grain radii specified in the image to the right.  Note the volume fraction need not sum to 1 as the undefined volume will be V v.

39  The Lithology sub-tab in the Domain tab defines the physical characteristics of the reservoir into which we will be injecting CO 2 rich H 2 O.  This tab also defines the numerical grid upon which the resulting system of PDEs will be solved.  For our first problem, select Water 1 as the resident water and define a 100m long section of sandstone with 10 control volumes.  Since we define only one physical dimension, this is a 1D simulation.

40  The Water Composition in Time sub-tab defines which water composition will be used as the injectant.  It is possible to define several different water compositions and return to this sub-tab and select a different injectant mixture in successive simulations.  The mybp unit stands for millions of years before present. Using this parameter, one can simulate the injection of different water compositions at different times.

41  Subsidence is the downward motion associated with sedimentation and tectonic movements.  The flux parameter is the seepage velocity discussed in a previous slide.  For our studies, depth doesn't affect pressure and pressure doesn't affect water-rock interaction.

42  These constants define global variables used by the simulation subsystem.  For our studies, leave these constants as the default values shown.

43  After configuring a problem, click the Run Simulation button in the Calculation tab.  This button will invoke a new Java thread on the server that will launch and manage a simulation.  One can enter an arbitrary note in the description field to identify a particular configuration.

44  Right clicking on a row in the simulation table will allow one to manage a simulation.  While a simulation is running, the Thread State will be listed as WAITING.  When a simulation has finished, the Thread State will be listed as TERMINATED.  If a simulation terminated unexpectedly, view the log file to determine why.

45  When a simulation terminates after running successfully, right click in the simulation table and select View Results.  This will raise the Results tab and allow one to plot one or two variables with respect to space.

46  Results reveal the formation of a proton (H + ) diffusion front that forms ahead of a tracer iron (Fe ++ ) ion.  Diffusion front displacement is a function of initial background temperature.

47  Graphs show the evolution of the diffusion front between H + and Fe ++ with time.  The output interval was configured to be 0.5 years in the Control tab.  The total simulation time was configured to be 5 years in the Domain tab.  ⇒ each segment corresponds to half a year for years 0-5.

48 Front displacement




52 Initial reservoir formation concentrations before injection Distance from Injection Well (m) Log 10 Molarity Solute concentrations before injection  Executed 36 simulations where the seepage velocity v sx was varied from 0 to 500 cm yr -1 φ -1 in increments of 100 cm yr -1 φ -1 and the reservoir temperature was varied from 20°C to 120°C in increments of 20°C.  Initial concentrations before injection are constant across the whole formation.  Base case: v sx = 300 [cc/(cm 2 yr)]/φ T = 60°C

53  Increase in solute concentration at ~15 meters, after 1 year of injection.  The vertical lines mark the shift in concentration between the formation water and the effluent.  A ~1 meter, separation between the H + (Diffusion) front and Fe ++ (Sweep) front are visible. Distance from Injection Well (m) Diffusion Front Sweep Front Concentration profile for the v sx = 300 cm yr -1 φ -1 and T = 60°C case after year 1

54  Diffusion front has moved to ~38 meters.  Sweep front has moved to ~35 meters  The separation between the two fronts has increased to ~3 meters. Diffusion Front Sweep Front Aqueous solute concentrations after 3 years of injection Distance from Injection Well (m)

55 Diffusion Front Sweep Front  Diffusion front has moved to ~60 meters.  Sweep front has moved to ~56 meters.  The separation between the fronts has increased to ~4 meters. Distance from Injection Well (m) Aqueous solute concentrations after 5 years of injection

56  Animation shows how the separation distance changes in time as a function of reservoir temperature and seepage velocity.  Front separation occurs when advective driven solute transport is less dominant than diffusive driven transport.  Local minima at high temperatures and low injectant velocity.  Maxima propagates to a lower temperature region over time.

57 Distance from injection well (m) Diffusion Front Sweep Front Front Separation log 10 Molarity  Front separation distance likely a result of competition between advective and diffusive forces, as well as mineral dissolution and precipitation rates, all of which are affected by reservoir temperature and effluent velocity.  Separation distance is strictly positive and monotonically increasing over time.

58  “Map” is a plot of the ratio of the separation length at a given time to the maximum overall separation length for a given v s and T.  Maximum front separation occurs earlier in time at higher reservoir temperatures.  Color band progresses from green (low T R ) to black (high T R ).

59  The results of these simulations show the injection front is preceded by an acidic front that develops as a result of different diffusivities among solutes.  Abundant CO 2 in the effluent is a constant source of H + and bicarbonates.  The acidic front, marked by an increase in H + concentration, could have an adverse effect on lithologies and seals (via calcite dissolution in shale).  Does pH change have any implications on wetting angle or surface tension properties of ScCO 2, CO 2(l), oil, gas, H 2 O, etc.?  The advection front morphology may not be the same as the diffusion front morphology.  Changing pH might indirectly affect relative permeability of the fluid between the two fronts and thereby affect CO 2 storage efficiency and containment. (A. Carré and V. Lacarrière, 2006)

60  When CO 2 rich water is injected into a deep brine formation, carbonic acid is produced, which dissociates to form bicarbonate.  The bicarbonate ion also dissociates, albeit to a lesser extent, to form carbonate.  Concentrations of CO 2(aq) and HCO 3 - reverse just behind the sweep front, demonstrating that abundant CO 2 in the effluent is a constant source of H + and bicarbonate.  Protons diffuse through the sandstone formation at a much greater velocity than the other solutes in the injected effluent.  Acidic diffusion front develops ahead of the effluent.  Acidic front is a region of lower pH and varies from about one to four meters in length.  Acidic front could have complex effects on lithologies and seals (increased permeability, fracturing, containment).

61  Feldspars (KAlSi 3 O 8, NaAlSi 3 O 8, CaAl 2 Si 2 O 8 ) become strongly undersaturated in the acidic water behind the sweep front.  Results in high saturation of kaolinite (Al 2 Si 2 O 5 (OH) 4 ).  Reduced water pH suppresses calcite saturation behind the sweep front, even as additional Ca 2+ is released from the dissolving feldspars.  Possible consequence: enhanced mineralization (either precipitation or dissolution) in the sediments adjacent to the reservoir, and possible carbonate mineral dissolution in shale cap away from the site of CO 2 sequestration.

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