close

Вход

Забыли?

вход по аккаунту

?

j.ijggc.2018.08.001

код для вставкиСкачать
International Journal of Greenhouse Gas Control 78 (2018) 135–147
Contents lists available at ScienceDirect
International Journal of Greenhouse Gas Control
journal homepage: www.elsevier.com/locate/ijggc
Local capillary trapping in carbon sequestration: Parametric study and
implications for leakage assessment
T
Bo Ren
Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, 200 E. Dean Keeton St, Stop C0300, Austin, TX 78712, USA
A R T I C LE I N FO
A B S T R A C T
Keywords:
Local capillary trapping
Carbon sequestration
Buoyant flow
Leakage
Residual trapping
Local capillary trapping (LCT) is the trapping of CO2 by local capillary barriers. It occurs during buoyancy-driven
migration of bulk phase CO2 within a saline aquifer exhibiting spatially varying properties (permeability and
capillary entry pressure). The benefit of LCT, in the context of CO2 sequestration, is that local capillary trapped
CO2 is not susceptible to leakage through failed seals. However, it is unclear how the petrophsyical/geological
properties and flow dynamics influence LCT. Thus, the objective of this work is to evaluate the degree to which
potential local capillary traps are filled and quantify the extent of immobilization persisting after loss of seal
integrity. This paper presents a systematic and thorough study of the influential parameters of LCT. Fine-scale
capillary pressure fields are generated by using geostatistical permeability realizations and applying the Leverett
j-function. Multiple factors are examined, including injection rate, anisotropy, formation dip, aquifer types,
residual gas saturation, and capillary hysteresis. Leakage representative of wellbore failure is simulated, and LCT
after leakage is evaluated and compared to other trapping mechanisms. The results show that local capillary
traps in the near-well region can be fully filled during injection. Moreover, they remain filled after post-injection
buoyancy-driven flow ends. The filling efficiency of local capillary traps increases with the decrease in gravity
number (ratio of buoyant force over viscous force). As a result, maximizing LCT in carbon sequestration in
porous reservoirs may be achievable with the implementation of appropriate injection strategies.
1. Introduction
CO2 sequestration in saline aquifers has been widely accepted as the
promising and easily accessible way to reduce carbon emissions and
global warming in this century (Bachu, 2008). In order for CO2 to be
stored in a manner that is secure and environmentally acceptable, it is
essential to understand the behavior and migration of CO2 in geologic
formations under the effects of complicated interplaying forces (namely
buoyancy, capillary pressure, and viscous force), geologic characteristics, and operating conditions.
Typically, CO2 can be trapped by the following mechanisms: stratigraphic/structural trapping (Gupta, 2011), dissolution trapping
(Burton and Bryant, 2009), residual trapping (Pentland et al., 2008)
and mineral trapping (Pruess et al., 2003). Among these mechanisms,
dissolution, residual and mineral trapping are considered as the safest
way of immobilizing CO2 in storage media. The remaining CO2 (as free
gas), mostly in the stratigraphic and structural traps, is potentially
mobile and most likely to escape from the storage media should leakage
occur.
Recently, a new trapping mechanism – local capillary trapping
(LCT) – was proposed when considering the intrinsic heterogeneous
capillary pressure of a given storage formation (Saadatpoor et al.,
2010). LCT is a form of trapping where CO2 accumulates behind capillary barriers. It occurs during buoyancy-driven migration of bulk
phase CO2 within a saline aquifer exhibiting spatially varying properties (permeability and capillary entry pressure). Its benefit, applied
specially to CO2 sequestration, is that saturation of stored CO2 is larger
than residual phase saturation (Saadatpoor et al., 2010). In addition, in
case of leakage, CO2 in LCT does not escape from the storage formation
even if seal systems are compromised (Saadatpoor et al., 2010).
LCT is analogous to other well-known phenomena in the context of
multiphase flow through porous media. It is equivalent to the largescale “fill and spill” process used in charging hydrocarbon reservoirs
(Siddiqui and Lake, 1997). Additionally, it is analogous to pooling of
non-aqueous phase liquid spilled onto soils (Van Valkenburg and
Annable, 2002). Several mechanisms would create local capillary traps,
such as grain size variation (e.g., fining upward sequence), changes in
depositional environments over time, and non-uniform/uneven diagenetic alteration.
A number of studies (Saadatpoor et al., 2010; ; Trevisan et al.,
2017a; Li and Benson, 2015) have been conducted to investigate the
impact of LCT or capillary heterogeneity on CO2 movement and
E-mail address: boren@utexas.edu.
https://doi.org/10.1016/j.ijggc.2018.08.001
Received 15 May 2018; Received in revised form 19 July 2018; Accepted 1 August 2018
1750-5836/ © 2018 Elsevier Ltd. All rights reserved.
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
(2010).
saturation distribution. Generally, these studies originate from two
different research considerations; theoretically, under the buoyancydominated flow of CO2 in saline aquifers, buoyant force is comparable
to capillary pressure, thus, capillary heterogeneity essentially influences CO2 movement. Experimentally, researchers found that it is difficult to replicate two-dimensional (2D) and three-dimensional (3D)
CO2 saturation profiles within cores when adopting a single capillary
pressure curve for history matching. However, when appropriate
scaling laws for capillary pressure are incorporated, the saturation
profiles or fields can be better reproduced (Krause et al., 2011; Shi
et al., 2011; Kong et al., 2014; Wei et al., 2014). Apart from LCT in
cores, LCT has been studied in 2D bench-scale experiments when considering only buoyant flow (Li and Benson, 2015; Sun, 2014) and when
incorporating injection-period (Trevisan et al., 2017b). It is shown that
CO2 buoyant flow is greatly disrupted in the event of even slight heterogeneities, i.e., when the grain size becomes fine, half of the size is
enough to temporarily hinder buoyant flow (Sun, 2014). All the above
results provide important qualitative and quantitative insights on the
role of capillary heterogeneity on CO2 flow and distribution in storage
aquifers.
However, most of the researchers in this field did not explore how
LCT influences CO2 leakage, which is a significant concern in geologic
carbon sequestration (Tao, 2012). Additionally, previous work
(Saadatpoor et al., 2010; Saadatpoor, 2012) indicates that 10–50% of
local capillary traps get filled during the buoyancy-driven drainage
process. However, the previous work (Saadatpoor et al., 2010) assumed
a limiting-case initial distribution of CO2 in the storage formation. It
remains to be determined whether more realistic distributions of saturation for buoyancy-driven CO2 migration, namely the distribution of
CO2 at the end of injection, affect the extent of LCT. In addition, it is
valuable to examine the effect of both fluid/rock properties (e.g., residual phase saturation) and operating parameters (e.g., injection rates)
on LCT.
In this paper, a systematic numerical assessment of LCT is conducted to evaluate the fraction of potential local capillary traps filled as
a function of primary controls while including both the injection and
leakage periods. A series of two-dimensional synthetic domains are
built and these domains are representative of typical storage formations. Different factors are examined, including injection parameters
and reservoir static properties. Particularly, a wide range of buoyancy
numbers (i.e., ratio between buoyant force and viscous force) are
considered. At the end of post-injection, a leak conduit is introduced
along a wellbore to evaluate the effect of LCT on storage security. The
understanding thus obtained here will provide insights into post-injection leakage behaviors while the injection period is simulated realistically.
1/9.61
k ⎞
ϕ=⎛
⎝ 7E + 7 ⎠
(1)
Capillary entry pressure fields (Fig. 1c) are generated using the
Leverett j-function [Leverett (1941), Eq. (2)]. In Eq. (2), pc is capillary
pressure, σg/w is the interfacial tension between CO2 and brine water, θ
is contact angle, k is permeability, φ is porosity. The detailed procedures of generating capillary entry pressure field have been elaborated
in (Saadatpoor et al., 2010). Table 1 summarizes the properties of the
base geologic model.
J (Sw ) =
pc (Sw )
σg / w cos θ
k
ϕ
(2)
In this model (Fig. 1), the pore volume of cells in the right boundary
is adjusted to mimic different types of aquifers (i.e., an open aquifer and
a closed aquifer). This is realized by using the keyword VOLMOD in
CMG-GEM (2012). The magnitude of VOLMOD is chosen based on the
magnitude of injected CO2 volume. An extremely large VOLMOD
(1.0E + 7) is assigned to the right boundary cells to mimic an open
boundary condition. This boundary is convenient because it prevents
pressure buildup during injection. Alternatively, a small (1E + 4)
VOLMOD is used to mimic a closed aquifer system, which enables us to
study the effect of pressure buildup on LCT.
The above base storage model is varied in terms of permeability
anisotropy, dip angle, and heterogeneity. Permeability fields are set to
be anisotropic by considering the vertical component of permeability to
be a tenth, hundredth, and thousandth of the horizontal component.
Three formation dip angles (0, 5 and 25°) are examined; they represent
horizontal, moderately-deviated, and highly-deviated formations, respectively. Different horizontal auto-correlation lengths and standard
deviations of permeability are also considered. Table 3 summarizes the
settings of these parameters.
Following the storage model, a leakage model is built (Fig. 2). The
leakage conduit has a permeability of 10 Darcy (9.87 × 10−12 m2) and
width of 2 ft (0.609 m). The lower formation in Fig. 2 is the same as the
storage domain in Fig. 1. The properties of the upper formation is the
same as described in Saadatpoor et al. (2010), and the main difference
is the right boundary settings; previous work (Saadatpoor et al., 2010)
employs a closed boundary (VOLMOD = 1), but here an open boundary
condition is created through using a large VOLMOD (1E + 7).
2.2. Components and rock-fluid properties
Component properties are the same as those in previous work
(Saadatpoor, 2012; Kumar et al., 2005) with CO2 dissolution in brine
considered. Figs. 3 and 4 show the relative permeability curves and the
capillary pressure curves, respectively. They are consistent with each
other. The capillary pressure curves in Fig. 4 are assigned to the simulation cells with the arithmetic mean of permeability. The corresponding capillary pressure curves for other cells are scaled using Leverett j-function with the detailed procedures described in Saadatpoor
et al. (2010). The hysteresis in both the relative permeability and capillary pressure curves are considered. The above settings mean that
dissolution and residual trapping are modeled in simulations. However,
our main interest is on LCT. Mineral trapping is not considered.
2. Approach
The simulator used in the study, CMG-GEM (2012), is a multidimensional and equation-of-state compositional simulator. It can simulate all the important mechanisms controlling CO2 sequestration into
saline aquifers.
2.1. Reservoir properties
A series of 2D models are generated, and they are vertically oriented
since LCT occurs during buoyant flow. Fig. 1a shows the based model
with the properties detailed in Table 1. Permeability fields (Fig. 1b) are
generated using a fast Fourier transform technique (Jennings et al.,
2000). The advantages of the method are speed and global conditioning, and it can be applied in any number of dimensions. Porosity
is correlated with permeability by Eq. (1) (Holtz, 2002). In Eq. (1), the
unit of permeability is mD. The initial reservoir pressure is 2265.6 psi
(15.62 MPa) with a constant reservoir temperature of 140 °F (60 °C).
The settings of other parameters are the same as Saadatpoor et al.
2.3. Injection and leakage simulation schemes
A buoyancy number is introduced to describe the influence of
buoyancy on CO2 migration; the number is a dimensionless ratio of
buoyancy to viscous force that drives CO2 migration. Several definitions
of the buoyancy number are possible. Here, the buoyancy number (Ngr)
is defined in following form (Shook et al., 1992):
136
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 1. A 2D aquifer model. Dotted lines in (a) represents cells with a large volume modifier (1E + 7), which is used to create an open aquifer.
Table 1
Properties of the base 2D synthetic model (corresponding to Fig. 1).
Model parameters
2D
Model size, ft (m)
Grid block size, ft (m)
Permeability frequency distribution
Autocorrelation length λx, λz, ft (m)
Arithmetic mean of permeability, mD (m2)
Anisotropy of permeability field
Standard deviation of permeability, mD (m2)
Arithmetic mean of porosity
Arithmetic mean of capillary entry pressure, psi
(MPa)
Standard deviation of capillary entry pressure, psi
(MPa)
400 (121.92) × 100 (30.48)
1 (0.30)×1 (0.30)
lognormal
5 (1.52), 0 (0)
200 (1.97 × 10−13)
isotropic
340 (3.36 × 10−13)
0.27
2.07 (1.43 × 10−2)
1.36 (9.37 × 10−3)
Fig. 3. Relative permeability curves. Adapted from Saadatpoor (2012).
Fig. 2. A 2D schematic aquifer leakage model. The schematic diagram is
adapted from Saadatpoor (2012). Changes are made on the right boundary cells
that are indicated by dotted lines.
Ngr =
Δρgk v H cos α
uh μL
(3)
In the above, Δρ is the density difference between brine and CO2, g is
gravitational acceleration, kv is the mean vertical permeability, H is
perforation length, α is formation dip angle with respect to the horizontal direction, uh is the nominal horizontal flux entering formations
from wellbores, μ is CO2 viscosity, L is reservoir horizontal length.
Under the reservoir condition (15.62 MPa, 60 °C), CO2 density is
618.7 kg/m3, brine density is 1024.6 kg/m3, and CO2 viscosity is
0.0486 cp.
All terms, except for uh, in the above expression are fixed for a given
storage reservoir and well completion. uh varies with injection rate.
Thus, Ngr is essentially a dimensionless injection rate (a reciprocal
Fig. 4. Capillary pressure curves for the reference grid blocks.
injection rate). Small values of Ngr (10−2) correspond to large injection
rates, with correspondingly minimal influence of buoyancy on CO2
plume movement. For commercial scale injection rates, Ngr is small in
the portion near the wellbore. This is the region of primary interest in
this study. Table 2 shows injection rates used in this study.
The injected amount is chosen to exactly fill the pore volume (PV) of
the domain excluding the right boundary cells. The amount is determined to be 190 tonnes (1 PV). The same mass is injected under
137
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
injection parameters, reservoir static properties, and rock/fluid interaction parameters. The first group consists of well injection rate (indicated by Ngr), injected volume (in multiples of pore volume or PV),
and injection well type. The second group is comprised of permeability
anisotropy (kv/kh), formation dip angle (α), horizontal auto-correlation
length (λx), coefficient of variation (Cv), and aquifer type (i.e., the
closed or open aquifer). The third group parameters are residual gas
saturation (Sgr), relative permeability hysteresis, and capillary pressure
hysteresis. This work reports how these parameters affect LCT spatial
extent and mass fraction at the end of each process (i.e., injection, postinjection, and leakage). LCT mass fraction is defined as the ratio of LCT
mass over the total CO2 mass injected. The CO2 saturation associated
with LCT is defined in the range between residual gas saturation (Sgr) to
100%. In other words, CO2 in cells with gas saturation above residual
are categorized as LCT.
Table 2
Injection simulation scheme in 2D domains.
Injector
type
Injection
ratea, m3/s
Flux entering
formation
from wellbore,
m/s
Injection
duration,
yr
Ngr along
wellboreb,
(Eq. (3))
Dominant
force
Vertical
1.61 × 10−4
2.12 × 10−4
20
20
Vertical
Vertical
Vertical
1.61 × 10−3
1.61 × 10−2
1.61 × 10−1
2.12 × 10−3
2.12 × 10−2
2.12 × 10−1
2
0.2
0.02
2.0
0.2
0.02
Point
Point
3.47 × 10−7
3.47 × 10−5
2.12 × 10−3
2.12 × 10−1
26
0.26
2.0
0.02
Buoyant
force
Transition
Transition
Viscous
force
Transition
Viscous
force
a
b
At the surface condition.
Ngr is calculated for isotropic permeability fields.
3. Results
3.1. Injection parameters
3.1.1. Effect of injection rate on LCT
Fig. 6 shows CO2 saturation fields at the end of injection under
different injection rates. The injection eliminates the transition zone
(the zone between the bottom CO2 emplacement area and the top CO2
accumulation area) observed in Saadatpoor (2012) during buoyant flow
under an initial emplacement. This elimination occurs at least near the
wellbore for an isotropic domain. In the following section of the anisotropy effect, it is shown that such a transition zone occurs when using
very anisotropic media.
At a large injection rate (Ngr = 0.02), the immiscible displacement is
“compact”; CO2 goes into most of the cells in the domain during injection. This compact displacement leads to a widespread residual gas
trapping (cyan pixels in the right column of Fig. 6) during water imbibition into the tail edge of CO2 plume during the post-injection
period. In addition, the residual phase trapping surrounds LCT. However, when a small injection rate is employed (Ngr = 20), CO2 mostly
follows channels of auto-correlated larger-than-average permeability,
and saturation distributions for the immiscible displacement are ramified. As injection rates decrease, buoyancy stands out as the main
driving force and gravity segregation is pronounced.
Notably, for the small injection rate (Ngr = 20), the injected CO2
flows into the storage domain from only the upper portion of the perforated interval. This is because, for the lower portion, CO2 pressure
along the wellbore is less than reservoir hydrostatic pressure, which
prevents CO2 in the wellbore from flowing into the reservoir. Such a
phenomenon has also been observed in sandbox experiments (Trevisan
et al., 2014). However, this phenomenon disappears as injection rate
increases (Ngr = 0.02). This observation necessitates the optimization of
perforation intervals when using different injection rates (Kumar and
Bryant, 2008).
Obviously, among the four injection rates, the largest Ngr gives the
least filling of local capillary traps in the domain. In other words, the
filling efficiency of local capillary traps decreases as a transition from
compact displacement to capillary channeling, i.e. as injection rates
decrease.
On the other hand, the filling of local capillary traps within the
region invaded during injection is essentially the same for all injection
rates. That is, if a region contains CO2 at the end of injection and that
region corresponds to a local capillary trap, then, at steady state, that
trap will contain locally trapped CO2 at a large saturation, regardless of
buoyancy numbers during injection. This makes sense since LCT is an
equilibrium phenomenon. In other words, while the buoyancy number
strongly influences the fraction of the reservoir into which CO2 flows
during injection (essentially 100% at the smallest buoyancy number
and falling to about 50% at the largest buoyancy number in the left
column of Fig. 6), the migration that fills traps to a large saturation
Fig. 5. A schematic illustration of injectors. (Upper) a vertical well is located in
the left boundary with the perforation interval represented by small blue bars.
(Lower) a point injector is located in the middle bottom of the domain, and the
blue dot represent perforation intervals. (For interpretation of the references to
colour in this figure legend, the reader is referred to the web version of this
article.)
different injection rates, this yields injection periods shown in Table 2.
For configurations of injectors, Fig. 5 shows a schematic illustration of
well types, perforation lengths, and well locations. Two types of injector
are examined: a vertical injector and a point injector. The purpose of
using a point injector is to mimic injection from a horizontal well; the
point injection could be considered a vertical slice of a horizontal injector. Well injection rates are calculated using both the CO2 flux entering the formation from a wellbore (refer to Table 2) and the perforation length (same as the grid size for the point injection in Fig. 5b).
The flow simulation consists of three sequential processes: 1) an
injection period; 2) a post-injection storage process; and 3) a leakage
period. Injection and post-injection lasts for a total of 50 yrs. At the end
of post-injection, a leak conduit along injectors is manually introduced
with leakage lasting for another 50 yrs (refer to the aquifer leakage
model in Fig. 2).
Table 3 summarizes all cases studied with different settings of
conditions. In these cases, parameters are divided into three groups:
138
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Table 3
Summary of conditions for simulations.
λx, m
Cv
Injection rate, m3/s
Leak
Injected
volume, PV
Injector
type
Right
boundary
condition
kv/kh
Formation
dip
angle
Residual
gas
saturation
Capillary
pressure
hysteresis
Relative permeability
hysteresis
Figure
1.52
0.66
No
1
Vertical
Open
1
0
0.29
No
Yes
6
1.52
0.66
Yes
1
Vertical
Open
1
0
0.29
No
Yes
7
1.52
1.52
0.66
0.66
No
No
0.1–1
1
Vertical
Point
Open
Open
1
0.001, 1
0
0
0.29
0.29
No
No
Yes
Yes
9
10
1.52
1.52
0.66
0.66
No
No
1
1
Vertical
Vertical
Open
Open
0.001–1
1
0
0, 5, 25
0.29
0.29
No
No
Yes
Yes
11
12
60.96
0.66
No
1
Vertical
Open
1
0
0.29
No
Yes
13
60.96
0.66
Yes
1
Vertical
Open
1
0
0.29
No
Yes
14
1.52
1.52
1.52
1.52
1.52
0.66, 0.14
0.66
0.66
0.66
0.66
1.61 × 10−4 to
1.61 × 10−1
1.61 × 10−4 to
1.61 × 10−1
1.61 × 10−1
3.47 × 10−7,
3.47 × 10−5
1.61 × 10−2
1.61 × 10−4,
1.61 × 10−1
1.61 × 10−4 to
1.61 × 10−1
1.61 × 10−4 to
1.61 × 10−1
1.61 × 10−1
1.61 × 10−1
1.61 × 10−1
1.61 × 10−1
1.61 × 10−2,
1.61 × 10−1
No
Yes
NA
NA
NA
1
1
1
1
1
Vertical
Vertical
Vertical
Vertical
Vertical
Open
Open, closed
Open
Open
Open
1
1
1
1
0.001, 1
0
0
0
0
0
0.29
0.29
0.18–0.44
0.29
0.29
No
No
No
No
Yes
Yes
Yes
Yes
No
No
15
16, 17
18
19
20
occur after injection ends. Hence, the spatial distribution of LCT are
independent of buoyancy number.
Meanwhile, it is instructive to verify that the steady state post-injection CO2 distribution occupies local capillary traps. Take the largest
injection rate (Ngr = 0.02, left column of Fig. 6) for example, CO2 displaces water in every cell of the domain by the end of injection because
viscous forces are large throughout this 2D domain. Obviously, CO2 has
invaded all the regions corresponding to local capillary traps. CO2 has
also invaded all the regions corresponding to capillary barriers. This is
to be expected: the definition of a barrier is with respect to capillary
forces, not to viscous forces. None of cells have zero permeability, and
thus when viscous pressure is sufficient to overcome capillary entry
pressure, CO2 can and does invade the entire domain. The detailed
structure of heterogeneous reservoir can still be detected in the fineFig. 6. CO2 saturation fields at the end of injection (left column) and at the end of postinjection (right column) for decreasing injection rates from top to bottom. 190 tonnes
(equivalent to 1 P V) of CO2 were injected. At
the end of injection (left column), the CO2 mass
staying in the storage domain was 148, 106,
92, and 58 tonnes from top to bottom. The
difference between the injected CO2 masses
and the remaining has entered the column of
very large cells on the right side of the domain.
(For interpretation of the references to colour
in the text, the reader is referred to the web
version of this article.)
139
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
scale variation of saturation fields in the left column of Fig. 6. As an
aside, this is the reason why the simulation of conventional hydrocarbon reservoir processes, in which flow at commercial rates is driven
by viscous forces, routinely ignores the heterogeneity of capillarity
(Lake et al., 2014). In these cases, the solution, in terms of where injected and reservoir fluids go, is dictated by the structure of a permeability field, and this can be determined with sufficient accuracy by
ignoring capillarity. However, for geologic CO2 sequestration, the onset
of buoyancy-dominated migration and displacement is a crucial portion
of a storage process. This buoyant behavior cannot be described correctly unless the heterogeneity of capillary pressure is explicitly included.
The widespread filling of local capillary traps under the large rate
case is similar to behaviors observed in the large-emplaced volume limit
of the buoyancy-driven storage scenario (Saadatpoor, 2012). In the
latter emplacement scenario, all the local capillary traps get filled as the
rising CO2 forms a gas cap and then backfills non-barrier regions
downward from the reservoir seal. During the injection with large rates,
viscous forces enable CO2 to fill all the rock volume. In both cases,
essentially all the traps are filled.
The next step of the storage process, when injection ceases, is that
the injected CO2 and the remaining native brine are free to rearrange
themselves in response only to buoyant force. Since CO2 saturation in
most of the cells is greater than its residual saturation, it can be expected significant migration will occur. The right column of Fig. 6
confirms this expectation and it demonstrates that CO2 with large saturation accumulate within local capillary traps - even when the saturation in the trap at the end of injection was a moderate value. To see
this, note how many of the yellow/red pixels in the right column correspond to green pixels in the left column of Fig. 6. Evidently, postinjection migration enables CO2 to build to the drainage curve limit in
local capillary traps. Meanwhile, in regions that are neither traps nor
barriers, CO2 present at the end of injection migrates until it leaves
residual saturation behind (cyan pixels). Thus, local capillary traps in
the near-well region are filled during injection, and they remain filled
after post-injection buoyancy-driven flow ends.
To examine the robustness of LCT in the case of leakage, a leaking
conduit is introduced along the wellbore at the end of the post-injection
period and then another 50 yrs of leakage modeling is conducted to
look into the change of CO2 saturation inside LCT under buoyant flow.
CO2 saturation fields at the end of leakage are in Fig. 7. Most of the LCT
(bright yellow pixels) remain in place. This demonstrates that local
capillary trapped CO2 is stable and robust. What leaks from the formation is the CO2 in flow paths that are connected to the leakage
conduit.
Fig. 7. CO2 saturation fields at the end of leakage for two extreme buoyancy
numbers Ngr (0.02 and 20). The initial condition of leakage modeling corresponds to right column in Fig. 6. (For interpretation of the references to colour
in the text, the reader is referred to the web version of this article.)
large injection rate (refer to Table 2), respectively. Fig. 9c and d show
CO2 saturation in the anisotropic (kv/kh = 0.001) field at the end of
injection using the above two rates. Overall, as the decrease of the
buoyancy number (either by increasing injection rate or by decreasing
vertical permeability), capillary fingering gets suppressed and displacement becomes compact. This is favorable to the filling of local
capillary traps.
Compared to the vertical injector scenario, point injector gives more
dispersed CO2 flow. This is because: when the vertical injector is used,
CO2 flow velocity across the 2D domain changes negligibly. This is
because the CO2 flow across-area in the 2D domain increases marginally (∼4×) as CO2 migrates away from the injector (see Fig. 6 as an
example). However, for the point injector, the velocity is decreased as
CO2 migrates away from the middle injection point. The resultant impact on CO2 flow is similar to that of decreasing injection rates (refer to
Fig. 6). Fig. 9e and f show CO2 saturation at the end of post-injection,
which correspond to Fig. 9b and c. Injection well types do not alter the
extent of LCT, whereas, they largely influence the filling of local capillary traps.
3.1.2. Effect of injected volume on LCT
Fig. 8 shows CO2 saturation fields at the end of the post-injection
period. Obviously, as the injected CO2 volume increases, more local
capillary traps become filled. The injected CO2 mass does not affect the
extent of LCT; the bright yellow pixels common in the four cases have
the same spatial distribution. This again indicates that local capillary
traps are intrinsic to capillary entry pressure fields.
Similar to the behavior (refer to Fig. 6) observed at different
buoyancy numbers, Fig. 8 shows that CO2 occupies all the local capillary traps within the region swept by CO2. Thus, the essential question
during injection is what fraction of the reservoir volume get invaded by
the injected CO2. The gravity driven fluid movement after injection
ends enables CO2 to fill local traps in the swept region to a large (∼0.8)
saturation.
3.2. Reservoir static properties
3.1.3. Effect of well types on LCT
A vertical injector is used in the above analysis. In this section, a
point injector is placed at the middle bottom of the domain, to mimic a
vertical slice of horizontal injection. Fig. 9a and b show CO2 saturation
in the isotropic (kv/kh = 1) field at the end of injection for a small, and a
3.2.1. Effect of anisotropy on LCT
As stated earlier, injection of large quantities of CO2 eliminates
transition zones in an isotropic formation, even when perforations are
140
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 8. CO2 saturation fields at the end of post-injection. Different PV of CO2 were injected under a fixed injection rate (Ngr = 0.02). (For interpretation of the
references to colour in the text, the reader is referred to the web version of this article.)
This CO2 becomes the source CO2 zone for the post-injection buoyant
flow, during which, transition zones and gas caps are generated. The
right column of Fig. 10 shows CO2 saturation at the end of post-injection, which confirms the formation of transition zones.
In the right column (at the end of post-injection) of Fig. 10, structures and distributions of LCT (bright yellow pixels) are similar in the
flooded areas common for four anisotropies. However, CO2 saturations
are a little different. The first three fields have a higher CO2 saturation
in local capillary traps than the highest anisotropic field does. This is
because the first three have relatively large mass of CO2 left in the
storage domain: as calculated for the left column of Fig. 10, the mass of
CO2 staying in the storage domain were 106, 110, 97, and 69 tonnes,
only in the bottom quarter of the domain. On the other hand, such
transition zones are an important feature of CO2 migration from an
initial emplacement of CO2 at the bottom of a storage domain
(Saadatpoor, 2012). Therefore, it is important to determine if transition
zones arise during long-term injection under other conditions. The
condition most likely to lead to this situation is permeability anisotropy
as shown in the effect of well types on LCT.
Here, kv/kh is set to be 0.1, 0.01, and 0.001 by decreasing vertical
permeability. Fig. 10 shows the CO2 saturation fields at the end of injection. As kv/kh decreases (anisotropy increases), CO2 tends to flow
along the bottom of the domain. When kv/kh decreases to be 0.001, the
injected CO2 is mainly restricted at the bottom at the end of injection.
Fig. 9. CO2 saturation fields created through a
point injector in the middle bottom of the domain. The upper row is CO2 saturation fields at
the end of injection for the isotropic permeability field using two different injection rates
(refer to Table 3). The middle row is CO2 saturation fields at the end of injection for the
very anisotropic permeability field using the
same injection rates as the upper row. The
lower row is CO2 saturation fields at the end of
post-injection following CO2 distribution
shown in the middle row. Anisotropy is increased by decreasing vertical permeability.
Recall both injection rate and vertical permeability are considered in the definition of Ngr.
141
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 10. CO2 saturation fields at the end of injection (left column) and at the end of post-injection (right column). (For interpretation of the references to colour in the
text, the reader is referred to the web version of this article.)
the inclined formation. This suggests, if small injection rates have to be
employed (because of, e.g., small formation fracture pressure), it would
be better to choose a horizontal saline aquifer to enhance LCT.
respectively.
In the transition zones (refer to the right column of Fig. 10), CO2
migrates along some of the flow paths to reach the top seal but leaves a
large gas saturation in the flow path. Large CO2 saturations accumulate
below the top seal but not uniformly. Notably, for the most anisotropic
field, almost half of the upper portion of the domain is uninvaded by
CO2. Obviously, the local capillary traps in the portion are not filled.
3.2.3. Effect of auto-correlation length on LCT
Fig. 12 shows CO2 saturation at the end of injection and at the end
of post-injection in the 2D domain with a large horizontal auto-correlation length of 60.96 m. Recall, the base case uses a horizontal autocorrelation length of 1.52 m. The large horizontal auto-correlation
length enhances lateral migration of CO2, and gives rise to remarkable
distribution patterns of CO2.
For large injection rates, CO2 sweeps the whole domain and therefore, all the local capillary traps are filled. However, for small injection
rates, auto-correlated structures with relatively small capillary entry
pressure determine the CO2 preferential flow paths, so large horizontal
auto-correlation suppresses the upward migration of CO2. This is further reflected in Fig. 13 that shows CO2 saturation fields at the end of
leakage. For the small injection rate, all the injected CO2 stays inside
the storage formation, and no CO2 leaks out. However, for the large
injection rate, both capillary barriers and flow paths are flooded. This
causes some of CO2 to move toward the wellbore and subsequently
escape from the storage formation.
Through comparing Fig. 12 (λx = 60.96 m) to Fig. 6 (λx = 1.52 m),
a large horizontal auto-correlation length yields: (1) widely extended
LCT structures; (2) a large LCT mass fraction (it increased from 36% to
48 as λx increased from 1.52 to 60.96 m). Additionally, in the case of
leakage, a large horizontal auto-correlation yields less leakage of CO2
along the wellbore (Fig. 13 vs. Fig. 7). This is because large horizontally
auto-correlated flow paths cause CO2 to migrate laterally, rather than
upward.
3.2.2. Effect of formation dip angle on LCT
Fig. 11 shows CO2 saturation in formations with dip angles of 0°, 5°,
and 25°. For each dip angle, both the smallest and largest injection rates
(refer to Table 2) are employed. For the largest injection rate, the mass
of CO2 staying in the storage domain (the 399 × 100 ft portion) at the
end of post-injection for the three dip angles was 147.6, 147.73, and
148 tonnes, respectively. Whereas, for the smallest injection rate, the
mass of CO2 remaining in the storage formation at the end of postinjection was 57.6, 48.6, and 25.8 tonnes, respectively. Thus, formation
dip angle tends to have a greater impact on stored mass of CO2 inside a
fixed area under small injection rates (Ngr∼20).
In a moderate dip (5°) formation, the structures of LCT are similar to
those in the horizontal formation. However, when the formation becomes highly inclined (25°), LCT structures tend to be parallel to the
formation inclination. Notably, when the injection rate is smaller for
the highly-deviated formation, CO2 migration tends to be dominated by
several of the capillary channels. For this scenario, obviously, most of
the local capillary traps cannot be flooded. The laterally extensive local
capillary traps become convenient conduits for moving CO2 rapidly to
the right boundary (Fig. 11).
However, for the smallest injection rate (right column in Fig. 11);
LCT filling efficiency in the horizontal formation is better than that in
142
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 11. CO2 saturation fields at the end of
post-injection for the largest (left column) and
smallest injection rate (right column). Recall
the definition of Ngr includes the parameter of
formation dip angle, so Ngr changes slightly
with dip angles. The model vertical dimensions
are visually compressed due to the incorporation of dip angle. All the models have the size
of
121.92 m
(along
the
dip
direction) × 30.48 m (along the vertical direction).
ft = 4.07 × 10−3 MPa/m). Hence, this is helpful to examine the robustness of LCT under viscous flow.
Under viscous flow (Fig. 15b), the size of LCT (dispersed bright
yellow) and magnitude of associated LCT saturations become small, as
compared to the local capillary trapping under buoyant flow of leakage
(Fig. 15a). However, many small patches of local capillary trapping
remain in the former case even after 50 yrs of leakage.
Next, the mass of LCT in the storage domain is compared to residual
and dissolution trapping. Fig. 16 shows the variation of trapped CO2
mass fraction along time (injection, post-injection, and leakage) for
both closed and open aquifers. Many studies have examined the fraction
change of CO2 in forms of residual phase trapping, dissolution trapping,
and free states [e.g., Kumar et al. (2005), Doughty (2007), Taku Ide
et al. (2007)]. Their analyses are restricted to the injection and postinjection periods. Whereas, this work focuses on the post-injection and
leakage periods because LCT mainly takes the effect on the safe storage
of CO2 during these periods. During the post-injection period, LCT decreases while residual phase trapping increases: the former is converted
into the latter as water imbibes into the trail of CO2 plume. During
leakage, CO2 flows toward to the leak point and then escapes from the
formation in a short time period. After that, buoyant flow approaches to
a steady state, and the mass fraction of CO2 in different forms keeps
almost constant. LCT immobilizes more CO2 than dissolution trapping
in the closed aquifer, while for the open aquifer, LCT can play as significant role as residual phase trapping in storing CO2. It should be
noted that those mass fractions are measured in a small (1.52 m) horizontally auto-correlated domain. They would change with horizontal
auto-correlation length.
Specifically, at the end of leakage, the LCT mass fraction was 0.37
for the open aquifer, and it was 0.15 in the closed aquifer. This indicates
that viscous force compromises LCT during leakage, and LCT is sensitive to aquifer pressure. This finding is consistent with laboratory
3.2.4. Effect of standard deviation of capillary entry pressure on LCT
The above analysis demonstrates the spatial heterogeneity or autocorrelated structures of capillary entry pressure determines LCT amount
and distribution. This part shows the effect of another indicator of
heterogeneity (i.e., standard deviation) on LCT. Fig. 14 shows CO2 saturation fields at the end of post-injection for capillary entry pressure
fields with different coefficient of variations (Cv). Cv is the ratio of the
standard deviation to the mean of capillary entry pressure. Larger Cv
gives rise to a denser distribution of LCT (the yellow and red pixels).
Quantification shows the LCT volume fraction increased from 22 to
28% as Cv increased from 0.66 to 1.14.
3.2.5. Effect of aquifer types on LCT
All the above studies are limited to the effect of buoyant force on
LCT robustness in an open system where aquifer pressure has almost no
change during the storage period; it increased by only 5 psi at the end of
post-injection. However, pressure build-up would be encountered in a
closed aquifer (Ehlig-Economides and Economides, 2010). Thus, during
leakage, viscous flow would be expected, which is driven by the relaxation of pressure build-up of a storage aquifer into the still hydrostatic pressure of an upper aquifer. The effect of viscous flow on LCT is
examined through modelling leakage from a closed aquifer. The domain
configuration is the same as before except that a small VOLMOD
(1.0E + 4) is employed to the right boundary cells. Meanwhile, the
injected CO2 mass is kept at 190 tonnes (1 P V). Thus, the finite size of
the domain is noticeable for the volume of CO2 injected, and consequently the fluid pressure in the domain will increase during injection.
At the moment of leakage or at the end of post-injection, the average
pressure build-up relative to the original reservoir pressure was about
2000 psi (13.79 MPa). This gives rise to a pressure gradient (from the
storage aquifer to the upper aquifer) around 10 psi/ft (0.23 MPa/m),
which is much larger than buoyancy pressure gradient (0.18 psi/
143
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 12. CO2 saturation fields at the end of injection (left column) and at the end of post-injection (right column).
in terms of underlying mechanisms: the former trapping is resulted
from the heterogeneity of capillary entry pressure at large or representative element volume scales, whereas, the latter is caused by
snap-off (Roof, 1970) at pore-scales.
experiments (Sun, 2014), in which locally trapped non-wetting phase
remain intact when system pressure is hydrostatic, but when forcing
imbibition occurs (driven by imposing a gradient in hydraulic potential
in aqueous phase in the domain), much of the locally trapped phase is
displaced.
3.3.3. Effect of capillary hysteresis on LCT
Fig. 19 shows CO2 saturation fields at the end of injection in the
very anisotropic domain for cases without and with capillary hysteresis,
respectively. In the compact displacement region, most of the CO2 inside local capillary traps have been displaced after considering capillary
hysteresis. However, the remaining CO2 saturation after capillary imbibition was still around 0.4–0.5 (see scattered green pixels in Fig. 19b).
Recall the residual gas saturation is 0.29, so the remaining CO2 saturation in LCT is still larger than residual gas saturation. The right
open boundary condition creates “a very large aquifer”. This supplies
enough water for the imbibition. Even after the complete imbibition,
CO2 inside local capillary traps cannot be entirely displaced to the residual level even after 50 yrs of buoyant flow. Moreover, in the transition zone, LCT keeps intact after considering capillary hysteresis. The
yellow pixels (Fig. 19b) with high CO2 saturation are LCT. They are not
compromised by capillary hysteresis, even if they are surrounded by
water with high saturation.
3.3. Rock/fluid interaction parameters
3.3.1. Effect of residual gas saturation on LCT
Recall the base case sets the residual gas saturation to be 0.29. Here,
the residual gas saturation is changed from 0 to 0.44. This range is
representative of sandstone/sand-packs (Iglauer et al., 2011). Fig. 17
shows the mass fraction of LCT, residual phase trapping, and dissolution
trapping at both the end of post-injection and the end of leakage. These
mass fractions change little during leakage, thus, curves almost overlap
at the two measured times. As residual gas saturation increases, the LCT
mass fraction decreases significantly, and meanwhile, dissolution
trapping decreases slightly. LCT and residual phase trapping compete
with each other.
3.3.2. Effect of relative permeability hysteresis on LCT
Fig. 18a shows CO2 saturation fields with relative permeability
hysteresis added (base case); the hysteresis is the reason for widespread
residual gas (cyan color) inside the domain. Without hysteresis, residual
phase trapping does not occur (Fig. 18b). However, LCT still occurs. In
addition, its structures and saturation are similar to the case with
hysteresis: the spatial distribution of high (∼0.8) CO2 saturation patches are similar in the two fields of Fig. 18. This means that the hysteresis in relative permeability has no effect on LCT. Additionally, this
observation indicates that LCT is different from residual phase trapping
4. Discussion
The spatial auto-correlated distribution of capillary entry pressure
determines the extent of LCT. Such trapping determines the final distribution of CO2 in a storage aquifer. Therefore, the amount of CO2 that
is trapped locally changes with the spatial heterogeneity of capillary
entry pressure. Specifically, the potential of LCT increases as a storage
144
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
analyses of spatial correlation effects on capillary trapping of CO2
(Trevisan et al., 2015). For the capillary pressure hysteresis, our simulation results show that capillary hysteresis compromises LCT in
compact displacement regions, rather than transition zones (Fig. 19).
This is because the storage domain is connected to a large aquifer
(recall the use of large volume modifier for the boundary cells in the
Approach Section). Aquifer water tends to move downward toward the
compact region and imbibes into LCT. Thus, CO2 in the LCT are displaced. This is different from Gershenzon et al. (2017b) which observed
that capillary pressure hysteresis shows a negligible effect. The reason
behind this difference might be boundary conditions and capillary
pressure magnitudes.
The simulation results in this work show that LCT amounts are increased when decreasing Ngr. The decrease of Ngr can be realized
through increasing injection rates (e.g., Fig. 6). This observed effect of
injection rate is consistent with Gershenzon et al. (2017b) that shows
increasing injection rates enhances the amount of capillary pinned CO2.
Specifically, this work shows that local capillary traps in near-well regions can be fully filled (CO2 invades all the traps and establishes a
large saturation) during injection in an isotropic domain when the
corresponding Ngr is less than 2. This region is named as a “compact
displacement region” in the above. Moreover, local capillary traps remain filled after post-injection buoyancy driven flow ends. The next
question would be how large this “compact region” can be in a typical
injection scenario in a 3D domain. Consider a vertical CO2 injector in an
open aquifer, the aquifer thickness is 390 ft (118.87 m), and the vertical
perforation interval is in the lower quarter part. CO2 is injected at the
surface rate of 5.0E + 7 Scf/d (16.39 m3/s). The average vertical permeability is 20 mD (1.94 × 10−14 m2). The properties of brine and CO2
are the same as described above. The calculated radius of the compact
region is around 60 ft. Therefore, such a “near-well region” is small for
typical injection rates.
For leakage modeling, a single leakage conduit along a wellbore is
used to model the most probable leakage scenario of CO2 (Tao, 2012).
Admittedly, LCT amount would be influenced by leakage settings, including the number of leakage points, leakage time, and the connection
between leakage points and local capillary traps. Thus, the mass fraction of LCT calculated above would be changed as well.
This work employs a simple way to estimate LCT. The cells in simulation models with CO2 saturation larger than residual phase saturation are considered as LCT. This approach to quantifying LCT is not
accurate as some CO2 classified as LCT are structurally trapped in the
locations just below the seal. However, the overestimation of LCT is
relatively small in the cases examined. In the modeling efforts, long
(100 yrs) buoyant flow simulations are run in order to i) enable CO2 to
have enough time to charge local capillary traps; and ii) force the
structurally-trapped CO2 to move laterally into the right boundary cells
as much as possible. This minimizes the effect of structural trapping on
LCT. For example, through comparing the left uppermost field of Fig. 6
to the upper field of Fig. 7, it can be seen that structural trapping influences only a very small portion of the storage domain (i.e., the uppermost several layers). Alternatively, the bounds of LCT amounts
Fig. 13. CO2 saturation fields after 50 yrs of leakage following the right column
of Fig. 12. Two extreme buoyancy numbers (0.02 and 20) are shown in the
figure.
reservoir becomes heterogeneous (e.g., long horizontal auto-correlation
length and large standard deviation of permeability; refer to Figs. 6, 12,
and 14). The observation of the effect of standard deviation on LCT is
consistent with other studies (Gershenzon et al., 2015, 2017a,b), in
which, the influence of small-scale fluvial architecture on capillary
pinning (it is essentially local capillary trapping) was systematically
investigated. They showed that the amount of capillary pinning changes
with (1) the volume portion of fine grains to coarse grains changes the
amount of capillary pinning; (2) the permeability and capillary pressure
contrast between rock types. The observation of the effect of autocorrelation length on LCT was also supported by the experimental
Fig. 14. CO2 saturation fields at the end of post-injection for the capillary entry pressure fields with two coefficients of variation (Cv). (For interpretation of the
references to colour in the text, the reader is referred to the web version of this article.)
145
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 15. CO2 saturation fields after 50 yrs of leakage modeling in an open aquifer (a) and in a closed aquifer (b). (For interpretation of the references to colour in the
text, the reader is referred to the web version of this article.)
Fig. 17. Variation of CO2 mass fraction in different forms with residual gas
saturation.
of LCT. This kind of system is mimicked by choosing a very large volume multiplier on the right boundary grid blocks and injecting the
proper amount of CO2.
LCT could be as significant as residual gas trapping in immobilizing
CO2 in the intermediate period of leakage from the open aquifer. This
significance is enhanced as aquifer heterogeneity become horizontally
correlated in space. Thus, LCT would greatly enhance CO2 sequestration
safety and refine risk assessment framework.
For the static reservoir parameters, the heterogeneity of permeability/capillary entry pressure fields essentially determines the LCT
amount and structure. The injection parameters (i.e., injection rate and
injected volume) influence only the filling efficiency of local capillary
traps. This suggests that LCT can be maximized through manipulating
injection strategies. The rock/fluid interaction parameters (e.g., hysteresis in relative permeability and capillary pressure curves) affect CO2
saturation in LCT, but not the spatial configurations of LCT.
Overall, through compositional simulation, this work demonstrates
that LCT is one of the most important trapping mechanisms during
geological carbon sequestration in saline aquifers. Therefore, in the
future CO2 sequestration projects, LCT should be considered during the
design and optimization of trapping processes.
Fig. 16. Variation of CO2 mass fraction stored by LCT, residual gas, and dissolution along with time. (a) is for a closed aquifer, (b) is for an open aquifer.
could be estimated through analyzing the constitutive capillary pressure curves (Gershenzon et al., 2017b) or invoking reduced-physics
modeling methods (Ren et al., 2018).
5. Summary and conclusions
This work employs a commercial reservoir simulator CMG-GEM to
study the influential parameters of local capillary trapping (LCT). These
parameters are categorized into three groups: reservoir static parameters, injection parameters, and rock/fluid interaction parameters.
CO2 injection into heterogeneous 2D domains is simulated with two
main objectives: i) to examine whether flow rates (measured by gravity
number) alter the extent of LCT; and ii) to determine whether an open
system, generally encountered in sedimentary basins, alters the extent
Acknowledgements
The author would like to thank the sponsors of the Geological CO2
Storage Industrial Affiliates Project at The University of Texas at Austin.
This work was supported by the Office of Fossil Energy, National
146
International Journal of Greenhouse Gas Control 78 (2018) 135–147
B. Ren
Fig. 18. CO2 saturation fields at the end of the post-injection.
Fig. 19. Effect of capillary hysteresis on LCT. (For interpretation of the references to colour in the text, the reader is referred to the web version of this article.)
Energy Technology Laboratory of the United States Department of
Energy under DOE Award Number DE-FE0004956. The author is
grateful to Ian J. Duncan for his help in condensing the manuscript. The
author is also thankful to the reviewers Naum Gershenzon and Luca
Trevisan for their comments.
152–169.
Li, B., Benson, S.M., 2015. Influence of small-scale heterogeneity on upward CO2 plume
migration in storage aquifers. Adv. Water Resour. 83, 389–404.
Pentland, C.H., Itsekiri, E., Al-Mansoori, S.K., Iglauer, S., Bijeljic, B., Bluent, M.J., 2008.
Measurement of non-wetting phase trapping in sand packs. SPE Annual Technical
Conference and Exhibition. Society of Petroleum Engineers, Denver, Colorado, USA.
Pruess, K., Xu, T.F., Apps, J., Garcia, J., 2003. Numerical modeling of aquifer disposal of
CO2. SPE J. 8 (1), 49–60.
Ren, B., Bryant, S.L., Lake, L.W., 2018. Estimating local capillary trapping capacities
using a geologic criterion. Submitted to. Int. J. Greenh. Gas Control.
Roof, J.G., 1970. Snap-off of oil droplets in water-wet pores. SPE J. 10 (01), 85–90.
Saadatpoor, E., 2012. Local Capillary Trapping in Geological Carbon Storage. The
University of Texas at Austin.
Saadatpoor, E., Bryant, S.L., Sepehrnoori, K., 2010. New trapping mechanism in carbon
sequestration. Transp. Porous Media 82 (1), 3–17.
Shi, J.Q., Xue, Z.Q., Durucan, S., 2011. Supercritical CO2 core flooding and imbibition in
Tako sandstone - influence of sub-core scale heterogeneity. Int. J. Greenh. Gas
Control. 5 (1), 75–87.
Shook, M., Li, D., Lake, L.W., 1992. Scaling immiscible flow through permeable media by
inspectional analysis. In Situ 6 (4), 311–350.
Siddiqui, F.I., Lake, L.W., 1997. A comprehensive dynamic theory of hydrocarbon migration and trapping. SPE-38682 Presented at the Annual Technical Conference and
Exhibition.
Sun, Y., 2014. Investigation of Buoyant Plumes in a quasi-2D Domain: Characterizing the
Influence of Local Capillary Trapping and Heterogeneity on Sequestered CO2 - a
Bench Scale Experiment. The University of Texas at Austin.
Taku Ide, S., Jessen, K., Orr, F.M., 2007. Storage of CO2 in saline aquifers: effects of
gravity, viscous, and capillary forces on amount and timing of trapping. Int. J.
Greenh. Gas Control. 1 (4), 481–491.
Tao, Q., 2012. Modeling CO2 Leakage from Geological Storage Formation and Reducing
the Associated Risk. Ph.D. Dissertation. The University of Texas at Austin, Austin,
Texas.
Trevisan, L., Cihan, A., Fagerlund, F., Agartan, E., Mori, H., Birkholzer, J.T., Zhou, Q.,
Illangasekare, T.H., 2014. Investigation of mechanisms of supercritical CO2 trapping
in deep saline reservoirs using surrogate fluids at ambient laboratory conditions. Int.
J. Greenh. Gas Control. 29, 35–49.
Trevisan, L., Pini, R., Cihan, A., Birkholzer, J.T., Zhou, Q., Illangasekare, T.H., 2015.
Experimental analysis of spatial correlation effects on capillary trapping of supercritical CO2 at the intermediate laboratory scale in heterogeneous porous media.
Water Resour. Res. 51 (11), 8791–8805.
Trevisan, L., Krishnamurthy, P.G., Meckel, T.A., 2017a. Impact of 3D capillary heterogeneity and bedform architecture at the sub-meter scale on CO2 saturation for
buoyant flow in clastic aquifers. Int. J. Greenh. Gas Control. 56, 237–249.
Trevisan, L., Pini, R., Cihan, A., Birkholzer, J.T., Zhou, Q.L., Gonzalez-Nicolas, A.,
Illangasekare, T.H., 2017b. Imaging and quantification of spreading and trapping of
carbon dioxide in saline aquifers using meter‐scale laboratory experiments. Water
Resour. Res. 53 (1), 485–502.
Van Valkenburg, M.E., Annable, M.D., 2002. Mobilization and entry of DNAPL pools into
finer sand media by cosolvents: two-dimensional chamber studies. J. Contam. Hydrol.
59 (3–4), 211–230.
Wei, N., Gill, M., Crandall, D., Mcintyre, D., Wang, Y., Bruner, K., Li, X., Bromhal, G.,
2014. CO2 flooding properties of Liujiagou Sandstone: influence of sub-core scale
structure heterogeneity. Greenh. Gases Sci. Technol. 4 (3), 400–418.
References
Bachu, S., 2008. CO2 storage in geological media: role, means, status and barriers to
deployment. Prog. Energy Combust. Sci. 34 (2), 254–273.
Burton, M., Bryant, S.L., 2009. Eliminating buoyant migration of sequestered CO2 through
surface dissolution: implementation costs and technical challenges. SPE Reservoir
Eval. Eng. 12 (3), 399–407.
CMG-GEM, 2012. GEM Users’ Guide. Computer Modeling Group Ltd, Canada.
Doughty, C., 2007. Modeling geologic storage of carbon dioxide: comparison of nonhysteretic and hysteretic characteristic curves. Energy Convers. Manag. 48 (6),
1768–1781.
Ehlig-Economides, C., Economides, M.J., 2010. Sequestering carbon dioxide in a closed
underground volume. J. Petrol. Sci. Eng. 70 (1–2), 123–130.
Gershenzon, N.I., Ritzi, R.W., Dominic, D.F., Soltanian, M., Mehnert, E., Okwen, R.T.,
2015. Influence of small-scale fluvial architecture on CO2 trapping processes in deep
brine reservoirs. Water Resour. Res. 51, 8240–8256.
Gershenzon, N.I., Ritzi Jr., R.W., Dominic, D.F., Mehnert, E., Okwen, R.T., Patterson, C.,
2017a. CO2 trapping in reservoirs with fluvial architecture: sensitivity to heterogeneity in permeability and constitutive relationship parameters for different rock
types. J. Petrol. Sci. Eng. 155, 89–99.
Gershenzon, N.I., Ritzi Jr., R.W., Dominic, D.F., Mehnert, E., Okwen, R.T., 2017b.
Capillary trapping of CO2 in heterogeneous reservoirs during the injection period. Int.
J. Greenh. Gas Control 59, 13–23.
Gupta, A.K., 2011. Understanding the Plume Dynamics and Risk Associated with CO2
Injection in Deep Saline Aquifers. The University of Texas at Austin.
Holtz, M.H., 2002. Residual gas saturation to aquifer influx: a calculation method for 3-D
computer reservoir model construction. SPE Gas Technology Symposium.
Iglauer, S., Wülling, W., Pentland, C.H., Al-Mansoori, S.K., Blunt, M.J., 2011. Capillarytrapping capacity of sandstones and sandpacks. SPE J. 16 (4), 778–783.
Jennings, J.W., Ruppel, S.C., Ward, W.B., 2000. Geostatistical analysis of permeability
data and modeling of fluid-flow effects in carbonate outcrops. SPE Reservoir Eval.
Eng. 3 (4), 292–303.
Kong, X.G., Delshad, M., Wheeler, M.F., 2014. History matching heterogeneous coreflood
of CO2/brine by use of compositional reservoir simulator and geostatistical approach.
SPE J. 20 (2), 267–276.
Krause, M.H., Perrin, J.C., Benson, S.M., 2011. Modeling permeability distributions in a
sandstone core for history matching coreflood experiments. SPE J. 16 (4), 768–777.
Kumar, N., Bryant, S., 2008. Optimizing injection intervals in vertical and horizontal
wells for CO2 sequestration. SPE Annual Technical Conference and Exhibition.
Kumar, A., Noh, M.H., Ozah, R.C., Pope, G.A., Bryant, S.L., Sepehrnoori, K., Lake, L.W.,
2005. Reservoir simulation of CO2 storage in deep saline aquifers. SPE J. 10 (3),
336–348.
Lake, L.W., Johns, R., Rossen, B., Pope, G., 2014. Enhanced Oil Recovery, fourth edition.
Soceity of Petroleum Engineers, Richardson, TX.
Leverett, M.C., 1941. Capillary behavior in porous solids. AIME Petrol. Trans. 142,
147
Документ
Категория
Без категории
Просмотров
0
Размер файла
9 771 Кб
Теги
ijggc, 001, 2018
1/--страниц
Пожаловаться на содержимое документа