Transp Porous Med (2010) 82:49–76

DOI 10.1007/s11242-009-9396-z

Investigation of CO2 Plume Behavior for a Large-Scale

Pilot Test of Geologic Carbon Storage in a Saline

Formation

Christine Doughty

Received: 15 December 2008 / Accepted: 9 April 2009 / Published online: 9 May 2009

© The Author(s) 2009. This article is published with open access at Springerlink.com

Abstract The hydrodynamic behavior of carbon dioxide (CO2) injected into a deep saline

formation is investigated, focusing on trapping mechanisms that lead to CO2 plume stabilization. A numerical model of the subsurface at a proposed power plant with CO2 capture is

developed to simulate a planned pilot test, in which 1,000,000 metric tons of CO2 is injected

over a 4-year period, and the subsequent evolution of the CO2 plume for hundreds of years.

Key measures are plume migration distance and the time evolution of the partitioning of

CO2 between dissolved, immobile free-phase, and mobile free-phase forms. Model results

indicate that the injected CO2 plume is effectively immobilized at 25 years. At that time, 38%

of the CO2 is in dissolved form, 59% is immobile free phase, and 3% is mobile free phase.

The plume footprint is roughly elliptical, and extends much farther up-dip of the injection

well than down-dip. The pressure increase extends far beyond the plume footprint, but the

pressure response decreases rapidly with distance from the injection well, and decays rapidly

in time once injection ceases. Sensitivity studies that were carried out to investigate the effect

of poorly constrained model parameters permeability, permeability anisotropy, and residual

CO2 saturation indicate that small changes in properties can have a large impact on plume

evolution, causing significant trade-offs between different trapping mechanisms.

Keywords Geologic carbon storage · CO2 sequestration · Multiphase flow modeling ·

CO2 trapping mechanisms · Plume stabilization

1 Introduction

Understanding the hydrodynamic behavior of large-volume CO2 plumes is critical for advancing the technology of geologic carbon storage in deep saline formations. This behavior is

examined by developing a numerical model of the subsurface at the proposed Kimberlina

C. Doughty (B)

Earth Sciences Division, Lawrence Berkeley National Laboratory, University of California,

Berkeley, CA 94720, USA

e-mail: cadoughty@lbl.gov

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50 C. Doughty

Fig. 1 Map of California showing potential geologic carbon storage sites in sedimentary basins (light green

shading), courtesy of the California Energy Commission. The Kimberlina pilot test is located in the Southern

San Joaquin Valley (boxed red dot). The inset shows a satellite image of the Kimberlina power plant site. The

power plant and the injection well will be located near one another in the southwestern corner of the property

advanced oxy-combustion power plant with CO2 capture in the southern San Joaquin Valley,

California (Fig. 1). For its first 4 years of operation, the power plant will provide 250,000

metric tons of CO2 per year for a large-volume CO2 geologic storage pilot. Thereafter, the

captured CO2 will be sold locally for enhanced oil recovery operations. As shown in Fig. 1,

the sedimentary basin that forms California’s Central Valley provides a huge potential capacity for geologic carbon storage; thus, lessons learned from the Kimberlina site may be widely

applicable.

The target storage formation is a high-permeability sand layer located at a depth of 2 km,

which is over- and underlain by low-permeability shales. Within the formation itself, sands

and shales are interleaved in a lenticular fashion. This geological setting provides an ideal

situation for examining the interplay of buoyancy flow, capillary forces, CO2 dissolution, and

geologic heterogeneity in controlling the behavior of the injected CO2 plume. The model

simulates the 4-year injection period, in which a total of 1 million metric tons of CO2 are

injected, and the subsequent evolution of the CO2 plume for hundreds of years. Because

specific geologic information at the site of the proposed injection well is lacking (the nearest

well penetrating the storage formation is 2.5 km away), the simulation results should not be

taken as precise predictions, but rather general indications of the key features of CO2 plume

behavior.

In the subsurface, CO2 exists as an immiscible free phase and as a solute in the aqueous

phase. For typical hydrostatic pressure gradients and geothermal temperature gradients, freephase CO2 is supercritical at depths greater than about 800 m. The present study does not

consider pressure/temperature conditions below the critical point of CO2 (73.8 bars, 31◦C),

so CO2 never exists as a free phase in liquid or gaseous form. Supercritical CO2 is lighter

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 51

and much less viscous than the native brine; hence, in a two-phase flow context, it is referred

to as gas, whereas the aqueous phase is referred to as liquid.

Trapping CO2 is a significant challenge because the low density of free-phase CO2 compared to native brine makes it strongly buoyant. Immobilizing CO2 in the subsurface for

long-term geologic storage can be accomplished by four primary mechanisms. (1) Stratigraphic or structural trapping: buoyant free-phase CO2 is trapped beneath low-permeability

layers or faults or in anticline structures. (2) Residual CO2 trapping (also known as capillary trapping, mobility trapping, or phase trapping): multiphase flow processes immobilize

free-phase CO2. In the petroleum literature (e.g., Land 1968; Holtz 2002) it is commonly

assumed that residual gas saturation (the saturation below which CO2 is immobile) is historydependent, with a zero or small value during the drainage process (CO2 displacing brine),

and a potentially large value during imbibition (brine displacing CO2), which increases as

the maximum historical gas saturation increases. (3) Dissolution trapping (also known as

solubility trapping): the CO2 that dissolves in brine is no longer buoyant so there is no driving force toward the surface. In fact, CO2-saturated brine is denser than native brine. As

CO2-laden brine sinks deeper into the formation, it can set up circulation patterns that enable

more free-phase CO2 to come into contact with native brine, enabling more dissolution to

occur (Ennis-King and Paterson 2005; Pruess and Zhang 2008). (4) Mineral trapping: CO2

reacts with rock minerals to form carbonate compounds, typically over very long time scales

(Pruess et al. 2003; Xu et al. 2003, 2005; Gherardi et al. 2007). The first three mechanisms,

collectively referred to as hydrodynamic trapping by Bachu et al. (1994), dominate plume

behavior over the hundred-year time scale and are the focus of the present paper. Because

trapping mechanisms are scale-dependent, understanding large-volume pilots is a necessary

step between existing studies involving small-scale CO2 injection tests and actual commercial CO2 storage operations. Additionally, predicting the spatial and temporal evolution of the

CO2 plume and the attendant pressure increase can help optimize design of the monitoring

methods used for the pilot.

2 Model Development

2.1 Numerical Simulator

Numerical modeling is conducted using TOUGH2 (Pruess et al. 1999), a general-purpose

numerical simulator for multiphase, multicomponent fluid and heat flow in porous and fractured media. TOUGH2 incorporates accurate phase-partitioning and thermophysical properties of all fluid phases and components and uses a multiphase extension of Darcy’s law

that includes relative permeability and capillary-pressure effects. The present studies utilize

an equation of state package called ECO2N (Pruess and Spycher 2007; Spycher and Pruess

2005), designed to treat a two-phase (liquid, gas), three-component (water, salt (NaCl), CO2)

system in pressure/temperature regimes above the critical point of CO2 (P = 73.8 bars,

T = 31◦C), and a hysteretic formulation for capillary pressure and relative permeability

(Doughty 2007). Chemical reactions among CO2, brine, and rock minerals are not considered in TOUGH2, but a companion code, TOUGHREACT (Xu et al. 2006), is available for

such studies.

In TOUGH2, dissolution of both CO2 and NaCl in the aqueous phase is modeled as an

equilibrium process. That is, in any grid block where one or both of these components exist,

there is instantaneous partitioning between the aqueous phase (dissolution) and the free phase

(supercritical for CO2 and solid for NaCl). Partitioning is controlled by the solubility of each

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Fig. 2 CO2 solubility (plotted as mass fraction of CO2 in the aqueous phase) as a function of salinity (plotted

as mass fraction of NaCl in the aqueous phase) for various depths, assuming a hydrostatic pressure gradient

P(z) = 1 + 0.1 z and a geothermal temperature gradient T (z) = 15 + 0.025z

component in the aqueous phase. NaCl solubility depends only on temperature, whereas CO2

solubility depends on temperature, pressure, and salinity, as illustrated in Fig. 2 for typical

CO2 storage conditions. CO2 solubility increases with increasing pressure and decreases with

increasing temperature and salinity. Because pressure and temperature are usually correlated,

both increasing with depth, their effect on CO2 solubility tends to cancel out, leaving salinity

as the primary controlling factor.

If the amounts of CO2 and NaCl in a given grid block are each below their respective

solubility, then no free phase exists. If the amount of NaCl exceeds its solubility (e.g., as the

grid block dries out), then solid salt precipitates. If the amount of CO2 exceeds its solubility (e.g., as CO2 is injected), then a supercritical phase develops. An important distinction

between these two free phases is that solid salt is always immobile, whereas supercritical

CO2 may be mobile or immobile. Additionally, a small amount of liquid water evaporates

into the supercritical phase, whereas the solid phase is pure NaCl. The fraction of pore space

occupied by each phase is the saturation S, with Sg denoting the supercritical phase (primarily CO2, with a small amount of water vapour), Sl denoting the aqueous phase (primarily

water, with dissolved CO2 and NaCl), and Ss denoting the solid salt precipitate. For each

grid block, Sg + Sl + Ss = 1.

Together, capillary pressure Pc, liquid relative permeability krl , and gas relative permeability krg variation as a function of saturation are known as characteristic curves; they control

the way the brine (the wetting phase, also called the liquid phase) and supercritical CO2 (the

non-wetting phase, also called the gas phase) interact. In a hysteretic formulation, Pc, krl ,

and krg depend not only on the saturation of the grid block, but also on the history of the

saturation of the grid block. When gas saturation Sg increases because more CO2 enters a grid

block than leaves it, the process is known as drainage. Alternatively, when liquid saturation

Sl increases because more brine enters a grid block than leaves it, the process is known as

imbibition. The most critical parameter of the characteristic curves is the residual gas saturation, denoted as S

gr, which is the saturation below which gas is immobile (i.e., the saturation

below which immiscible CO2 is trapped). TOUGH2 uses the conceptualization common in

the petroleum literature (Land 1968) in which it is assumed that under drainage conditions,

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 53

Fig. 3 Capillary pressure and relative permeabilities as a function of saturation for primary drainage and

for imbibition when S

gr =Sgrmax . Smaller values of Sgr would produce curves within the envelope formed

by these two curves. The curve labeled krg shows relative permeability for supercritical CO2 and the curve

labeled krl shows relative permeability for brine

S

gr = 0, but for imbibition, Sgr increases as maximum historical gas saturation increases.

Thus, grid blocks that once contained the most CO2 are those which trap the most CO2. The

maximum value of S

gr, known as Sgrmax , is a material property dependent on rock porosity

(Holtz 2002). Figure 3 shows the capillary pressure and relative permeability curves under

primary drainage conditions and for imbibition when S

gr = Sgrmax . Smaller values of Sgr

would produce curves within the envelope formed by these two curves. Figure 3 illustrates

that CO2 mobility can be much smaller under imbibition than under drainage.

During a CO2 injection period, drainage is the dominant process because the CO2 plume is

growing in all directions; hence S

gr= 0 and no CO2 is trapped as residual gas. After injection

ends, the leading edge of the CO2 plume may still undergo drainage as the plume moves

upward and up-dip by buoyancy forces, but at the trailing edge of the plume imbibition

occurs, S

gr >> 0, and a significant fraction of the CO2 plume may be trapped as residual

gas.

Although TOUGH2 has the capability of solving fully coupled fluid and heat flow problems, temperature is assumed to remain constant for the present simulations, to increase computational efficiency. Previous studies (Doughty and Myer 2009) have shown that thermal

effects of CO2 injection are minor if the injected CO2 is pre-heated to near in situ temperature.

Additionally, the slow flow process of aqueous-phase diffusion of dissolved species is not

included in these simulations. For a typical CO2 diffusivity of D = 2.

10−9m2/s (Pruess and

Zhang 2008), the characteristic diffusion length (Dt)1/2 is only 0. 5 m for 4 years, 2.5 m for

100 years, and 8 m for 1,000 years, all small compared to CO2 plume dimensions. Finally,

TOUGH2 has the capability to decrease intrinsic permeability due to salt precipitation, but

it is not invoked for the present simulations because the amount of salt that precipitates is

small.

2.2 Geologic and Facies Models

A geologic model of the Southern San Joaquin Valley surrounding the Kimberlina power

plant (Wagoner 2009) is shown in Fig. 4. The target CO2 storage formation is the Vedder

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Fig. 4 Geologic model of the southern San Joaquin Valley (adapted from Wagoner 2009). The location of

the Kimberlina power plant is shown by the red dot near the center

Formation, a lower Miocene, fine- to coarse-grained massive marine sandstone with subordinate siltstone and shale. At the Kimberlina site, the Vedder Formation depth is 2 km, and

its thickness is about 160 m. The overlying Freeman–Jewett Formation, a 100-m thick lower

Miocene marine shale and siltstone, provides the upper seal.

A facies model of the Vedder Formation surrounding the Kimberlina site (J. Wagoner, personal communication, 2007) provides the basis for the TOUGH2 model. The facies model

(Fig. 5) is centered at the proposed Kimberlina power plant and covers an area of 125 km2.

Over the entire model area, Vedder Formation thickness ranges from 110 m to 187 m, but

within the 2 km surrounding the power plant, thickness only ranges from 150 m to 164 m.

The Vedder Formation dips 7◦ to the WSW.

The facies model uses 180 layers, of equal thickness, to represent the Vedder Formation.

Each layer contains 2,500 cells: 50 cells each 250 m wide in the E–W (x) direction by 50

cells each 200 m long in the N–S (y) direction. A facies (either sand or shale) is assigned

to each cell, by interpolating sand/shale picks obtained from eight well logs. Because of

the limited information available from such a small number of wells, no attempt is made to

represent heterogeneity within the individual facies. Overall, the facies model contains about

50% sand and 50% shale, interleaved in a lenticular fashion, with typical lens size 15 m thick

and several kilometers in lateral extent. At the location of the proposed injection well, the

Vedder Formation is 158 m thick and consists of five sand layers with total thickness 79 m,

separated by four shale lenses with total thickness 79 m.

2.3 Numerical Model

The TOUGH2 model (Fig. 6) covers roughly the same spatial extent as the facies model.

Because the formation dip and thickness are nearly uniform in the vicinity of the power plant

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 55

Fig. 5 Three views of the facies model of the Vedder Formation. The perspective view (top) has no vertical exaggeration, whereas the two cross sections (bottom) have five times vertical exaggeration, to enable

sand/shale layering to be seen. In the perspective view, the thick black line segments show the locations of the

eight wells used to develop the facies model, the thin black lines are depth contours, and the intersection of

the two cross sections marks the location of the injection well in the TOUGH2 simulations

(note that depth contour lines in the perspective view of Fig. 5 are essentially equidistant

and linear), the TOUGH2 model is constructed as a tilted plane, with just a single value of

thickness (157.5 m) and dip (7◦). The up-dip direction is 30◦ counter-clockwise from the

+x-axis (ENE), corresponding to the WSW down-dip direction. Each TOUGH2-model layer

is formed by combining six facies-model layers, resulting in 30 layers, each 5.25 m thick.

At the (x, y) location of each facies-model cell, the facies of the TOUGH2-model layer is

taken to be the facies that occurs the most times among the six facies-model layers that are

combined to form it. As can be seen by comparing Figs. 5 and 6, this combining scheme

captures the essential features of the lenticular sand/shale structure of the facies model.

The computational grid for the TOUGH2 model is shown in Fig. 7. Laterally, the TOUGH2

model grid-block size varies, with finest grid blocks in the vicinity of the injection well

(5 m × 5 m), increasing to 55 m × 55 m in the region where the CO2 plume is expected to go

(roughly an ellipse with a major axis <2 km), and gradually increasing further beyond that

region. The lateral extent of the active portion of the TOUGH2 model is 11 km × 11 km,

beyond which additional grid blocks are added to represent lateral boundary conditions. The

vertical discretization of the TOUGH2 model into 30 layers results in at least two model

layers per sand layer, to enable vertical flow arising from buoyancy forces to be resolved.

The 5-m width of the grid-block used for the injection well is much greater than an actual

well diameter, so the simulation is not expected to accurately reproduce all near-wellbore

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Fig. 6 Three views of the TOUGH2 model of the Vedder Formation. The perspective view (top) has no

vertical exaggeration, whereas the two cross sections (bottom) have five times vertical exaggeration, to enable

sand/shale layering to be seen. In the perspective view, the thin black lines are depth contours, and the intersection of the two cross sections marks the location of the injection well in the TOUGH2 simulations. Note

that the coordinate system has been translated so that the origin is where the injection well intersects the top

of the Vedder Formation

effects arising during CO2 injection. For example, the modeled pressure increase will not be

the actual pressure increase in the wellbore, but an average over 5m of formation surrounding the well. However, the focus of the present paper is on plume-scale effects, and using a

grid fine enough to represent an actual wellbore would greatly slow down the simulations.

Two features that are not included in the present simulations, thermal effects and intrinsic

permeability decrease due to salt precipitation, have their main effect within or close to the

wellbore, so neglecting them is consistent with the use of the present grid.

The top and bottom boundary of the TOUGH2 model are no-flow boundaries, to represent

regionally extensive, continuous shale layers over- and underlying the Vedder Formation. In

the x-direction, the lateral boundaries are constant pressure boundaries and in the y-direction the lateral boundaries are no-flow boundaries. These boundary conditions are chosen

for numerical convenience rather than geological accuracy. The actual extent of the Vedder

Formation is estimated to be 55 km in the east–west direction and 90 km in the north-south

direction, far beyond the lateral extent of the TOUGH2 model. As shown in the “simulation

results” section, the lateral boundaries are so far away from the injection well and the region

the CO2 plume occupies that they have little impact on the evolution of the CO2 plume. Table 1

summarizes the geometric properties and boundary conditions of the TOUGH2 model.

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 57

Fig. 7 Three views of the TOUGH2 model of the Vedder Formation showing the computational grid

The initial conditions for the CO2 injection are a brine-saturated formation with a hydrostatic pressure distribution, and a pressure of 220 bars at the injection well location. Initial

temperature and salinity are uniform at 81◦C and 50,000 TDS, respectively. This temperature

is calculated assuming a surface temperature of 15◦C and a geothermal gradient of 30◦C per

km, both of which are rough estimates considered reasonable for Southern California. In the

absence of specific information on salinity for the Vedder Formation, a moderate value of

50,000 TDS is chosen. The primary impact of the initial pressure and temperature is to define

the density and viscosity of the CO2 plume in the subsurface. Density controls not only the

volume of the plume, but also the strength of the buoyancy force, which is proportional to the

density difference between injected CO2 and native brine. In conjunction with permeability,

viscosity controls how mobile the CO2 is. The effects of initial pressure and temperature on

plume migration are examined elsewhere (Jordan and Doughty 2008). According to Fig. 2,

salinity is inversely related to CO2 solubility. If actual salinity turns out to be lower than

50,000 TDS (values as low as 20,000 TDS have been proposed), a greater fraction of the

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Table 1 Geometric properties and boundary conditions of the TOUGH2 model for the Vedder Formation at

the Kimberlina power plant site

Parameter Value Comment

Depth at injection well (m) 2,200 Same as facies model

Thickness (m) 157.5 Facies model thickness ranges from 110 m to 187 m

Percent sand/shale 50/50 Sand occurs in five distinct layers, with interleaving

shales

Number of model layers 30 Each model layer 5.25 m thick, combines 6

facies-model layers

Lateral extent (km) 11 × 11 Comparable to facies model

Lateral grid spacing Varies 5 m × 5 m at injection well; maximum 55 m × 55 m

within CO2 plume footprint

Formation dip 7◦ Up-dip direction is ENE, 30◦ counter-clockwise

from +x-axis

Boundary Conditions

Top and bottom No flow Represent continuous, extensive shale layers

Lateral, x-direction Constant pressure

Lateral, y-direction No flow

Table 2 Initial conditions and flow properties of CO2 and brine

Initial condition Value

Initial pressure Hydrostatic pressure distribution;

average 220 bars at injection well

Initial temperature 81◦C

Initial salinity 50,000 mg/L

CO2 solubility in brine 43,000 mg/L

Flow property C O2 Brine

Density (kg/m3) 632 1,014

Viscosity (Pa-s) 5·10−5 4·10−4

injected CO2 will dissolve and the free-phase plume will be correspondingly smaller. Additionally, lower salinity means smaller brine density, which decreases the driving force for

buoyant flow of free-phase CO2. Thus, the present simulation results may be considered to

be conservative in terms of predicting plume extent and migration. Table 2 summarizes the

initial conditions used for the Kimberlina simulations, and the resulting density and viscosity

of the injected CO2 and the native brine. It shows that the injected plume will be strongly

buoyant in the subsurface.

The material properties used in the base-case TOUGH2 model are summarized in Table 3.

Porosity and permeability values are consistent with the geologic model, but relative permeability and capillary pressure parameters are not known for the Kimberlina site, so parameter

values are adapted from other studies of CO2 geologic storage in saline formations (Doughty

2007; Doughty et al. 2008). Sensitivity studies then examine the impact of varying permeability, permeability anisotropy (both vertical and lateral), and maximum residual gas saturation.

Table 3 shows that the permeability contrast between the sand and shale facies is large; thus

CO2, which is injected only into sand layers, is expected to remain in the sand layers. The

functional forms of the hysteretic characteristic curves (Doughty 2007) are based on the van

Genuchten (1980) formulation.

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 59

Table 3 Material properties of the base-case TOUGH2 model

Property Sand Shale

Porosity 28% 15%

Horizontala permeability, kx , ky 200 md 0.1 md

Verticala permeability kz 20 md 0.01 md

Relative permeability parameters

Residual liquid saturation Slr 0.2 0.3

Maximum residual gas saturation Sb

grmax 0.27 0.29

van Genuchten parameter m 0.917 0.917

Capillary pressure parameters (same for drainage and imbibition branches)

Capillary pressure strength Pc0 1.88·

104 Pa 8.41·105 Pa

van Genuchten parameter m 0.412 0.412

a “Horizontal” means parallel to layering; “vertical” means perpendicular to layering

b Residual gas saturation S

gr is zero during drainage and non-zero during imbibition, where it depends on

saturation history and has a maximum value of Sgrmax

The CO2 injection well is located at the center of the model and penetrates the entire Vedder Formation thickness. Because the TOUGH2 model does not include an actual wellbore

model (recall that lateral grid spacing at the injection well location is 5m × 5m), injection

is modeled as a mass source distributed among the sand layers, with source strength proportional to layer thickness. Altogether, 250,000 T/year is injected for a period of 4 years,

resulting in 1,000,000 metric tons of CO2 injected.

3 Simulation Results

The TOUGH2 simulations cover the 4-year injection period and at least 100 years thereafter,

when CO2 is subject only to gravity and capillary forces. All simulations use the computational grid as shown in Fig. 6 and the properties shown in Tables 1 and 2. Base-case simulations

use the properties as shown in Table 3, while sensitivity studies consider alternative values

whose ranges reflect the uncertainty of our knowledge of actual properties.

3.1 Base Case

3.1.1 Supercritical CO2

Figures 8 and 9 show snapshots of the supercritical CO2 plume at various times. Figure 8

shows a plan view of the uppermost layer of the model, which is the layer in which the

greatest lateral extent of CO2 occurs. Figure 9 shows x −z cross-sections through the model,

and illustrates the formation of five sub-plumes in the five sand layers within the Vedder

Formation. Note from Fig. 8 that the x − z plane does not show the maximum lateral extent

of CO2, which occurs in the up-dip direction. Together, Figs. 8 and 9 illustrate the strong

buoyancy flow that moves CO2 to the top of each sand layer, and from there moves the plume

up-dip.

Key measures of the CO2 plume are its up-dip extent at stabilization and the time evolution of the partitioning of CO2 between dissolved, immobile-gas, and mobile-gas forms. In

the present study, plume stabilization is defined as occurring when two successive snapshots

show no advance of the leading edge of the plume. Figure 8 shows that the base-case plume

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Fig. 8 Top view of the base-case supercritical CO2 plume at a series of times, shown by plotting Sg, saturation of supercritical CO2, in the uppermost model layer. During injection, the rectilinear grid produces minor

numerical artifacts in the plume distribution by enabling enhanced flow along the grid axis directions

Fig. 9 East–west cross section of the base-case supercritical CO2 plume at a series of times, shown by plotting

Sg, saturation of supercritical CO2, in the plane y = 0

has stabilized by 25 years, at which time it is about 1,500 m long, 900 m wide, and extends

1,300 m up-dip of the injection well.

Quantification of the trapping and stabilization process is presented in Fig. 10, which

shows the time evolution of the CO2 mass distribution for the entire model. The total amount

of CO2 injected is divided into two parts, i.e., a gas-like supercritical phase and a dissolved

phase. The supercritical phase is further divided into mobile and immobile portions, with

CO2 immobile when its saturation is below residual gas saturation S

gr. Throughout the

injection period, about 20% of the CO2 dissolves, and essentially all the supercritical-phase

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 61

Fig. 10 Time evolution of the CO2 mass distribution for the entire model for the base-case (thick lines) and

sensitivity-study case SH4, which models the Vedder Formation as a homogeneous, isotropic sand (thin lines)

CO2 is mobile. After injection ends, the dissolved fraction increases gradually to 38% as the

plume moves up-dip and encounters new under-saturated brine. This up-dip movement is

accompanied by residual CO2 trapping, and Fig. 10 shows how the mobile fraction of supercritical CO2 decreases concurrent with the increase of the immobile fraction. By 25 years

the supercritical CO2 is largely immobile, coinciding with the stabilization of the plume as

shown in Fig. 8. Thereafter, the plume does not move as a whole, but subtle redistributions

of the immiscible phase further decrease the mobile fraction and dissolution of supercritical

CO2 continues, slowly increasing the dissolved fraction. The supercritical plume has nearly

completely dissolved by 10,000 years.

Insight into residual CO2 trapping can be obtained by examining the spatial distribution

of drainage and imbibition at a series of times during and after injection. Figure 11 displays

ICURV, the variable identifying which branch of the capillary pressure curve is being followed, for each grid block in the uppermost model layer. Recall that residual CO2 trapping

requires a non-zero value of residual gas saturation, which only occurs during imbibition.

Nearly the entire plume is undergoing drainage just after the injection period ends, except for

a narrow imbibition zone at the trailing (down-dip) edge of the plume. The imbibition zone

grows steadily until 25 years, when drainage is limited to a few grid blocks at the leading

(up-dip) edge of the plume, at which time the plume has stabilized. Thereafter, the zone of

drainage gradually shrinks further, until it has disappeared by 100 years.

Because imbibition dominates the plume for most of the post-injection period, the residual

gas saturation S

gr is non-zero over much of the plume (Fig. 12), enabling significant residual

CO2 trapping. The S

gr distribution does not change after the plume stabilizes at 25 years.

Figure 13 shows the spatial distribution of (Sg − S

gr), the difference between gas saturation and residual gas saturation. The larger the value of (Sg − S

gr), the more mobile the

plume is (Fig. 3). There is a sharp decrease in mobility at the transition from drainage (S

gr=

0) to imbibition (S

gr > 0) at 4, 5, and 7 years (compare to Figs. 11 and 12). From 10 years

on, (Sg − S

gr) is very small throughout the plume. Beginning at 20 years, negative values

of (Sg − S

gr) develop, which can only happen if immobile free-phase CO2 is dissolving.

Continued dissolution of immobile CO2 implies that the brine must be moving, because quiescent brine adjacent to immobile free-phase CO2 would quickly saturate, precluding further

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Fig. 11 Top view of base-case distribution of drainage and imbibition at a series of times: ICURV = 0—singlephase liquid, 1—primary drainage, 2—first-order imbibition, 3—second-order drainage, and 4—third-order

imbibition

dissolution. The present simulations do not include regional groundwater flow, so the only

driving force for brine movement is natural convection, arising from the small brine density

increase that occurs when CO2 dissolves. The banded character of the negative (Sg − S

gr)

values evident at 500 and 1,000 years suggests the formation of convection cells in the brine

underlying the free-phase CO2, with the top of each cell (where lighter CO2-free native brine

up-wells) coincident with a band of enhanced dissolution.

3.1.2 Dissolved CO2

Before investigating the natural convection of CO2-laden brine, it is worthwhile to examine further how the free-phase CO2 and dissolved CO2 interact. Figure 14 shows a vertical

cross-section of the storage formation in the vicinity of the injection well at 4 years, the

end of the injection period. The top frame shows free-phase CO2, the second frame shows

CO2 dissolved in the brine, the third frame shows the NaCl dissolved in the brine, and the

bottom frame shows precipitated NaCl. Dissolved species are shown as mass fractions in

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 63

Fig. 12 Top view of base-case distribution of residual gas saturation S

gr at a series of times (colors). Contour

lines show supercritical CO2 saturation Sg, illustrating the spatial distribution of the plume itself

the aqueous phase, whereas precipitated NaCl is shown as solid saturation Ss (i.e., the pore

volume fraction of precipitated NaCl).

For the most part, the spatial distribution of dissolved CO2 coincides with that of freephase CO2. The one exception is close to the injection intervals where Sg is large. In these

locations, strong capillary forces arising from large values of Sg draw brine toward the well.

Near the well, some of the water evaporates into the supercritical CO2 phase, increasing

dissolved NaCl content in the remaining brine. There is an inverse correlation between NaCl

content and CO2 solubility (Fig. 2), resulting in the regions of low dissolved CO2 near the

injection intervals. Otherwise, the close correspondence between the spatial extents of freephase and dissolved CO2 indicates that natural convection of brine is negligible at this time.

Recall that aqueous-phase diffusion is not included in these simulations. The slight extension

of the dissolved-CO2 plume beyond the free-phase plume visible in Fig. 14 is likely due to

numerical dispersion.

Figure 15 shows dissolved CO2 distributions at 25, 100, and 500 years. With time, spatial

distributions of dissolved and free-phase CO2 increasingly differ, confirming that natural

convection of CO2-laden brine is significant, and the convection cells themselves are illustrated by the irregular distribution of dissolved CO2 in the up-dip region of the top sand layer

at 100 and 500 years. The low-permeability shales separating each of the five sub-plumes,

constrain the bulk of the brine flow to the sand layers. Flow is greater down-dip, but up-dip

flow into the deeper parts of each sand layer is also evident. At times beyond 500 years

(not shown), down-dip migration of dissolved CO2 continues, but its up-dip extent does not

change appreciably. At the final simulation time (10,000 years) the dissolved CO2 plume

extends about 4 km down-dip from the injection well.

3.1.3 Pressure Response

Figure 16 compares the lateral extent of the pressure response to CO2 injection with the lateral

extent of the CO2 plume itself. The profiles show pressure change and gas saturation in the

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64 C. Doughty

Fig. 13 Top view of base-case distribution of (Sg − S

gr) at a series of times (colors). Contour lines show Sg,

saturation of supercritical CO2, illustrating the spatial distribution of the plume itself. Note that different color

maps are used for the first four frames and for the final eight frames, where all negative values of (Sg − S

gr)

are shown in dark blue

uppermost layer in the model, along a transect beginning at the injection well and extending

in the up-dip direction. During the injection period, pressure close to the injection well does

not increase monotonically with time. This occurs because the viscosity of injected CO2 is

much lower than that of the native brine (Table 2), and as the CO2 plume grows there is less

resistance to flow, so less pressure increase in response to the constant CO2 injection rate.

After injection ends, CO2 saturation decreases as the plume stretches out, with the leading

edge of the CO2 plume moving up-dip and the maximum pressure increase moving along with

it. Although the pressure response extends far beyond the CO2 plume, the pressure response

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 65

Fig. 14 East–west cross-section of the base-case plume in the plane y = 0 at 4 years: a Sg shows saturation

of supercritical CO2; b XCO2L shows the mass fraction of CO2 dissolved in the aqueous phase; c XNaCl

shows the mass fraction of NaCl dissolved in the aqueous phase; d Ss shows saturation of precipitated NaCl.

The black contour lines show Sg = 0, illustrating the maximum extent of the supercritical plume

beyond the CO2 footprint is small (<1.5 bars). Moreover, pressure response decreases as

distance from the injection well increases, and quickly dissipates after injection ceases (<1

bar everywhere 1 year after injection ends).

Recall that the base-case model assumes partially open (constant-P), partially closed

(no flow) boundary conditions. Two additional simulations, assuming either all-open or allclosed lateral boundary conditions, produce identical CO2 plumes, and only slightly different pressure responses. During the injection period, pressure responses are similar for all

the cases. Only near the lateral boundary does the all-closed case differ significantly, with

a pressure increase of just over 0.2 bars (the pressure response at the open boundaries is

guaranteed to be zero). After injection ceases, the pressure change at all distances decreases

to near zero for the base case (Figure 16) and the all-open case (not shown) within 20 years.

In contrast, for the closed case, the pressure change becomes uniform in space at a value just

below 0.3 bars.

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66 C. Doughty

Fig. 15 Late-time (i.e., post-stabilization) distributions of base-case dissolved CO2, shown by plotting

XCO2L , the mass fraction of CO2 dissolved in the aqueous phase, in the plane y = 0. The black contour lines

show Sg = 0, illustrating the maximum extent of the supercritical plume

3.2 Sensitivity Studies

Most of the material properties used as input to the base-case numerical simulation are not

well known. To assess the impact of parameter uncertainty on plume evolution and trapping

mechanisms, sensitivity studies are carried out using alternative parameter choices for poorly

known parameters. Table 4 summarizes the cases and the key performance measures for each.

Figure 17 shows a plan view of the top of the stabilized plume for each case.

The time variation of the mass of mobile CO2 (Fig. 10) shows an initial rapid decrease

after injection ends followed by a very slow approach to zero, which does not provide a

convenient means for determining when a plume has stabilized. It is clear from the time

series of CO2 distributions (Fig. 8) that the plume does not move perceptibly after 25 years,

even though mobile CO2 remains. Rather than trying to find a threshold mass of mobile

CO2 that defines stabilization, the CO2 distributions are used directly, and stabilization is

defined as occurring when two successive distributions are indistinguishable. However, it is

also useful to compare among cases how long it takes to reach a given amount of mobile

CO2. The “time to 3% mobile CO2” entry in Table 4 serves this purpose. The value of 3% is

used because all the cases reach it within the simulation period (typically 100 years). Table 4

indicates that there is generally a good correlation between the “time to 3% mobile CO2”

and “time of plume stabilization” entries; therefore, they are often referred to collectively as

time measures for plume mobility.

3.2.1 Sand Anisotropy Studies

The base-case model assumes that vertical permeability is 1/10th of horizontal permeability, a

common assumption for sands with permeability in the hundred millidarcy range. Assuming

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 67

Fig. 16 Pressure change and supercritical CO2 saturation Sg versus up-dip distance from the injection well

at a series of times, for the base-case

an isotropic medium (Case AN1) produces only subtly different plume evolutions: comparable time measures for plume mobility, only 50 m more up-dip migration, and similar percent

dissolved CO2. This insensitivity largely arises from the sand/shale layering, which creates

five sub-plumes in the sand layers, and thereby limits the amount of buoyancy flow that can

occur. A change by a factor of ten in permeability anisotropy has a much greater effect for a

homogeneous sand formation (see Cases SH3 and SH4 below).

The region surrounding the Kimberlina site contains numerous small faults trending generally north–south. Whether these faults act as conduits or barriers to flow, their net effect

is likely to be a lateral (x : y) anisotropy in sand permeability with a greater permeability

in the north–south (y) direction. Cases AN2 and AN3, with a 3:1 and 10:1 y : x anisotropy

ratio, respectively, show that the direction of plume migration shifts dramatically from the

up-dip direction (30◦ north of due east) toward the north. For the 10:1 anisotropy ratio, the

time measures for plume mobility are shorter and up-dip plume extent and percent dissolved

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68 C. Doughty

Table 4 Summary of sensitivity studies

Case Key

Features

Time to

3% mobile

CO2

(years)

Time of

plume stabilization

(years)

Up-dip

migration

distance at

stabilization

(km)

Percent

dissolved

at stabilization

Base-case kx = ky = 200 md, 23 25 1.30 38

kz = 20 md,

Sgrmax = 0.27

Sand anisotropy studies

AN1 Isotropic 22 25 1.35 39

permeability

kx = ky = kz =

200 md

AN2 Lateral permeability 23 25 1.50 39

anisotropy

kx = ky /3,

< kx ky >g = 200 md,

kz = 20 md

AN3 Lateral permeability 21 20 2.50 41

anisotropy

kx = ky /10,

< kx ky >g = 200 md,

kz = 20 md

Sand permeability studiesa

SA1 Very low 94 85 0.70 32

permeability

kx = ky = 20 md,

kz = 2 md

SA2 Low 37 50 1.00 34

permeability

kx = ky = 66 md,

kz = 6.6 md

SA3 High 16 20 2.00 45

permeability

kx = ky = 500 md,

kz = 250 md

SA4 Very high 12 15 2.50 52

permeability

kx = ky = kz =

1,000 md

Shale permeability studiesa

SH1 Medium-permeability 29 25 1.30 39

shale

kx = ky = 2 md,

kz = 0.2 md

SH2 High-permeability 20 40 1.50 38

shale

kx = ky = 20 md,

kz=2 md

SH3 No shale 27 25 1.80 33

kx = ky = 200 md,

kz=20 md

SH4 No shale 32 40 2.20 33

kx = ky = kz =

200 md

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 69

Table 4 continued

Case Key Features Time to

3% mobile

CO2

(years)

Time of

plume stabilization

(years)

Up-dip

migration

distance at

stabilization

(km)

Percent

dissolved

at stabilization

Residual gas saturation studiesb

SG1 High residual gas saturation 10 15 1.05 32

Sgrmax = 0.40

SG2 Medium-high residual gas saturation 19 25 1.20 37

Sgrmax = 0.30

SG3 Medium-low residual gas saturation 45 25 1.45 43

Sgrmax = 0.20

SG4 Low residual gas saturation 114 30 1.80 53

Sgrmax = 0.10 a When permeability decreases, capillary pressure strength Pc0 and Sgrmax increase

b Here, only Sgrmax is varied

CO2 are greater, which are features common to the high sand permeability cases described

below.

3.2.2 Sand Permeability Studies

Sand horizontal permeability values ranging from 20 md to 1000 md are considered here

(Cases SA1, SA2, SA3, and SA4). In our conceptual model, when sand permeability k

increases, the vertical to horizontal permeability ratio kz/kx increases, capillary pressure

strength Pc0 decreases as Pc0 ∼ k−1/2, and maximum residual gas saturation Sgrmax

decreases as Sgrmax = 0.48 − 0.04 ln(k), with k in md, which is adapted from correlations

developed by (Holtz, 2002, personal communication, 2003), based on Gulf Coast sandstone

literature.

Increasing sand permeability has a strong effect on the plume performance measures

shown in Table 4, with up-dip plume extent and percentage of dissolved CO2 increasing,

whereas time measures for plume stability and maximum CO2 saturation decrease. All these

effects are a consequence of the greater buoyancy flow enabled by larger permeability. Larger

up-dip plume extent means more brine is encountered by the plume, and so more dissolution

occurs. Since the trailing (down-dip) edge of the plume is trapped, larger up-dip extent means

the plume is stretched out more, and hence CO2 saturation is lower, leading to greater residual

CO2 trapping, less mobile CO2, and earlier stabilization. It should be noted that while well

logs from the Kimberlina region do show sand permeabilities even higher than 1000 md and

even lower than 20 md, it is not known how regionally extensive such extreme features are.

3.2.3 Shale Vertical Permeability Studies

Shale vertical permeability largely controls the vertical distribution of CO2 within the storage formation, as shown in Fig. 18. In the base case (Fig. 9), shale permeability is so low

and capillary pressure strength is so high that supercritical CO2 is effectively excluded from

shale lenses. Cases SH1, SH2, SH3, and SH4 consider larger shale permeabilities, which

are intended to represent sub-grid-scale heterogeneity in which sand and shale interfinger at

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70 C. Doughty

Fig. 17 Top view of stabilized supercritical CO2 plumes for all cases, shown by plotting Sg, saturation of

supercritical CO2, in the uppermost model layer. The time to stabilization is shown for each case

scales that are less than the 55-m grid size. Pc0 and Sgrmax values are correlated to permeability using the same relations given for sand above. In the limiting case (Cases SH3 and

SH4), shale lenses are assigned pure sand properties; therefore, shale is actually absent, and

the Vedder Formation is modeled as a homogeneous sand layer. In these cases, buoyancy flow

is much stronger, resulting in much greater upward migration of CO2. This is especially true

for Case SH4, in which the vertical permeability equals the horizontal permeability. For Case

SH2, with shale permeability ten times smaller than that of sand permeability, supercritical

CO2 preferentially flows into sand layers, but does move into shale lenses as well. The Case

SH2 plume shows more buoyancy flow than the base case, but not nearly as much as when

the shale lenses are absent. For Case SH1, with a shale permeability 100 times smaller than

that of sand permeability, the CO2 distribution is indistinguishable from that of the base case,

which has a shale permeability 2000 times smaller than that of sand permeability.

Increasing shale permeability has a strong effect on the plume performance measures

shown in Table 4, with up-dip plume extent increasing and percent dissolved CO2 decreas123
Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 71

Fig. 18 East–west cross-section of the supercritical CO2 plume at two times for sensitivity-study cases with

different values of shale vertical permeability, shown by plotting Sg, saturation of supercritical CO2, in the

plane y = 0. Compare to base-case cross sections in Fig. 9

ing. Both these effects are a consequence of the more localized flow that occurs when the

shale lenses do not divide the CO2 into multiple plumes. CO2 saturation in the single plume is

higher than that in the five individual plumes, and so residual CO2 trapping is diminished and

up-dip migration is enhanced. Dissolution trapping also decreases, which is a consequence

of the smaller CO2/brine contact area.

Since the presence or absence of shale lenses so strongly impacts the evolution of the

supercritical CO2 plume, it is useful to examine the behavior of dissolved CO2, in the noshale case as well. Figure 19 shows dissolved CO2 distributions for the Case SH4, in which

the Vedder Formation is modeled as a homogeneous isotropic sand layer. As for the base

case (Fig. 14), at the end of the injection period, the dissolved CO2 distribution correlates

closely with the supercritical CO2 distribution. Thereafter, the two distributions differ significantly, as natural convection of the brine begins. Comparing Fig. 19 with Fig. 15 shows

that the absence of shale lenses greatly enhances natural convection compared to the base

case, which in turn enhances late-time dissolution. The integrated mass distribution in Fig. 10

illustrates how the Case-SH4 dissolved fraction, which is less than the base-case dissolved

fraction when the plumes stabilize, later becomes significantly greater than it. The supercritical plume has nearly completely dissolved by 1,300 years, far sooner than the base-case

dissolution time of 10,000 years.

Numerical studies of brine convection (Pruess and Zhang 2008) using much finer grid

resolution than this study indicate that the details of convection (e.g., how many convection

123
72 C. Doughty

Fig. 19 East–west cross-section of the dissolved CO2 plume at a series of times for sensitivity-study Case

SH4, shown by plotting XCO2L , mass fraction of CO2 in the aqueous phase, in the plane y = 0. Case SH4

models the storage formation as a homogeneous isotropic sand layer. The black contour lines show Sg = 0,

illustrating the maximum extent of the supercritical plume

cells, individual cell locations) are quite sensitive to grid spacing, but integrated measures,

such as how much CO2 crosses a given horizontal interface, are not. Since the lateral grid

resolution (55 m over most of the plume) is so coarse, the results shown in Fig. 19 should

not be considered as precise predictions of dissolved CO2 movement, but rather provide an

indication of the overall magnitude of convective transport.

3.2.4 Residual Gas Saturation Studies

Unlike permeability sensitivity studies, in which a range of property values are used because

of limited knowledge of subsurface property distributions, for residual gas saturation, there

is even significant uncertainty in our conceptual model. To a large extent, we rely on experience with other multiphase systems, primarily from the petroleum literature, in which maximum residual gas saturation Sgrmax is significantly above zero. The relatively few studies of

CO2/brine systems (e.g., Bachu and Bennion 2008; Benson et al. 2007; Doughty et al. 2008)

support this approach, but residual CO2 trapping is such an important process for immobilizing plumes in the absence of structural traps that further study is needed. Therefore, Sgrmax is

treated as an independent parameter, and the effect of decreasing it from the base-case value

is examined (Cases SG1, SG2, SG3, and SG4). Decreasing Sgrmax has a strong effect on

the plume performance measures shown in Table 4, producing greater up-dip migration and

increased time measures for plume mobility because of the diminished residual CO2 trapping

ability. In contrast, the additional up-dip migration enables more dissolution to occur.

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Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 73

4 Conclusions

The evolution of the CO2 plume formed during a large-scale pilot test for geologic CO2 storage in a moderately dipping saline aquifer has been modeled using the numerical simulator

TOUGH2. Simulation results show that for the base-case, about 20% of the 1,000,000 metric

tons of injected CO2 is in dissolved form at the end of the 4-year injection period, and this

percent increases to 38% by the time the CO2 plume stabilizes at 25 years. At stabilization,

of the 62% of the plume that exists as supercritical free phase, only 3% is mobile. From this

time onward, plume evolution consists solely of slow dissolution, aided by natural convection of dissolved-CO2-laden brine. The stabilized plume footprint is roughly elliptical, and is

strongly asymmetric about the injection well, extending 1,300 m in the up-dip direction and

200 m in the down-dip direction. The pressure increase in response to CO2 injection extends

far beyond the plume footprint, reaching the model boundaries 8 km away from the injection

well. However, the pressure response decreases rapidly with distance from the injection well,

and decays rapidly in time once injection ceases.

Sensitivity studies show that uncertain model parameters permeability anisotropy, permeability itself, and maximum residual gas saturation strongly affect the direction and extent of

CO2 plume movement, demonstrating the importance of site characterization efforts to better

constrain these parameters prior to CO2 injection. Even a subtle sand lateral permeability

anisotropy strongly affects plume migration direction. Sand vertical permeability anisotropy

does not have much effect on plume shape when shale lenses are present, but the opposite

is true for a storage formation composed solely of sand, where vertical anisotropy plays a

dominant role controlling buoyancy flow of both light free-phase CO2 and heavy dissolvedCO2-laden brine. Even the presence of a small amount of shale, as represented by shale

lenses with permeability only ten times smaller than that of sand, greatly diminishes upward

buoyancy flow of free-phase CO2.

Figure 20 summarizes the results shown in Table 4 graphically, demonstrating the tradeoffs in trapping mechanisms that occur as sand permeability, shale permeability, and residual

gas saturation are varied. As sand permeability increases (Fig. 20a), up-dip buoyancy flow is

enhanced so up-dip plume migration increases. Dissolution trapping increases as more brine

is exposed to free-phase CO2. Residual CO2 trapping ability decreases insofar as Sgrmax

decreases with increasing permeability, but the two time measures for plume mobility—time

to 3% mobile CO2 and time to plume stabilization—decrease significantly as sand permeability increases. This indicates that the lower CO2 saturation resulting from greater spreading

of the plume leads to more rapid residual CO2 trapping, despite the lower Sgrmax values.

As shale permeability increases (Fig. 20b), enhanced upward flow enables the five individual plumes to coalesce into a single plume that rises to the top of the formation, and

thereafter spreads up-dip (Fig. 18). This more localized flow enables CO2 saturation in the

single plume to remain higher than in the five individual plumes, and so residual CO2 trapping

is diminished and up-dip migration is enhanced. Dissolution trapping also decreases slightly

in response to the coalescence into a single plume, as the higher CO2 saturation results in a

more compact plume and thus smaller CO2/brine contact area. The time measures for plume

mobility still roughly track together, and show only a slight increase with shale permeability.

Finally, if Sgrmax values are typically smaller than the presently-accepted ones (Fig. 20c),

residual CO2 trapping decreases, leading to greater up-dip migration, increased time measures for plume mobility, and more dissolution trapping. For small values of Sgrmax , time to

3% mobile CO2 becomes much longer than time to plume stabilization, because the threshold for absolute immobility (Sgrmax ) becomes much harder to reach even though the relative

permeability of the plume as a whole is small enough for the plume to stabilize.

123
74 C. Doughty

Fig. 20 Summary of the sensitivity study results for (a) sand horizontal permeability when low-permeability

shale layers are present; (b) shale vertical permeability; and (c) residual gas saturation Sgrmax

123
Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon 75

The sedimentary basin that forms California’s Central Valley provides a huge potential

capacity for geologic carbon storage, and the geologic stratigraphy suggests that the dipping

planar structure of interleaved sands and shales that characterizes the Kimberlina model is

likely very common. For the longer injection periods and much greater CO2 volumes associated with full-scale CO2 storage, plume migration distance will be greater and time to

stabilization will be longer, but the conclusions about the interaction of trapping mechanisms

drawn from this study may still be widely useful for storage locations with limited knowledge

of reservoir flow parameters.

Acknowledgements Thanks are due to Jeff Wagoner of Lawrence Livermore National Laboratory for providing the geological and facies models of the Kimberlina site, to Preston Jordan for additional information

on faulting, and to Larry Myer and Curt Oldenburg for insightful discussions. The careful review of this

article by Kenzi Karasaki and two anonymous reviewers is appreciated. This study was supported in part by

WESTCARB through the Assistant Secretary for Fossil Energy, Office of Sequestration, Hydrogen, and Clean

Coal Fuels, National Energy Technology Laboratory (NETL), and by Lawrence Berkeley National Laboratory

under U.S. Department of Energy Contract No. DE-AC02-05CH11231.

Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided

the original author(s) and source are credited.

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