adsorption models for coalbed methane production and co2 ... · adsorption models for coalbed...
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November 12, 2004 1
Oklahoma State University
School of Chemical Engineering
Adsorption Models for Coalbed Methane Production and CO2 Sequestration
K. A. M. GasemR. L. Robinson, Jr.
(Principal Investigators)
Z. Pan J. E. Fitzgerald
M. Sudibandryio
Oklahoma State University
Sponsored by theU.S. Department of Energy
November 12, 2004 2
Oklahoma State University
School of Chemical Engineering
Equilibrium Adsorption Modeling
§ We seek simple, reliable adsorption equilibrium models that are suitable for generalized predictions and reservoir simulations.
§ Such models should:
– Precisely represent pure and mixture isotherms
– Facilitate accurate a priori predictions based on gas properties and coal matrix characterization
Strategy: Use rigorous methodologies rooted in fundamentals to develop reliable methods of high industrial utility.
November 12, 2004 3
Oklahoma State University
School of Chemical Engineering
Excess Ads. = Vads (ρads- ρgas)
Pressure
Exc
ess
Ad
s.
§ At low pressures the isothermis nearly linear and ρads>>ρgas
Local Density Near Surface
Excess Adsorption: Near-Critical Behavior
November 12, 2004 4
Oklahoma State University
School of Chemical Engineering
Pressure
Exc
ess
Ads
.
§ At higher pressures the isotherm has some curvature
Local Density Near Surface
Excess Ads. = Vads (ρads- ρgas)
Excess Adsorption: Near-Critical Behavior
November 12, 2004 5
Oklahoma State University
School of Chemical Engineering
Pressure
Exc
ess
Ads
.
§ At higher pressures the isotherm has some curvature and an excess adsorption maximum is reached.
Local Density Near Surface
Excess Ads. = Vads (ρads- ρgas)
Excess Adsorption: Near-Critical Behavior
November 12, 2004 6
Oklahoma State University
School of Chemical Engineering
Pressure
Exc
ess
Ads
.
§ The isotherm shape will eventually change concavity.
Local Density Near Surface
Excess Ads. = Vads (ρads- ρgas)
Excess Adsorption: Near-Critical Behavior
November 12, 2004 7
Oklahoma State University
School of Chemical Engineering
Pressure
Exc
ess
Ads
.
§ The excess adsorption will pass through zero at sufficiently high pressures.
Local Density Near Surface
Excess Adsorption: Near-Critical Behavior
Excess Ads. = Vads (ρads- ρgas)Does this mean that coalbed reservoirs contain lessnatural gas at higher pressures?
November 12, 2004 8
Oklahoma State University
School of Chemical Engineering
Excess and Absolute Adsorptionand Gas Capacity
§ Even though the excess adsorption, nE passes through a maximum and eventually through zero,the absolute adsorption, nA increases with pressure.
Pressure
Ads
orpt
ion
Qua
ntity
§ The gas capacity, nGCdenotes how much gas (both adsorbed and unadsorbed) is in the volumetric container of arbitrary Vvoid.
nGC= nE+ ρgasρhelium1
φpack-1
nA= nE+ Vads ρgas
φpack =ρhelium
ρapparent=
Adsorbent volumeTotal volume
§ The excess adsorption is sometimes called the Gibbs excess adsorption because it assumes two distinct phases, the adsorbed phase, and the unadsorbed phase.
November 12, 2004 9
Oklahoma State University
School of Chemical Engineering
Comparison of Gibbs Excess, Absolute Adsorption and Gas-Capacity of Carbon Dioxide on Dry Activated
Carbon at 45°C
0
5
10
15
20
25
30
0 2 4 6 8 10 12 14
Pressure (MPa)
Adso
rptio
n o
r Am
ount
(mm
ol/g
)
Gibbs Excess, SLD ModelAbsolute AdsorptionGas-In-Place
0.529 g/cc Apparent Density
November 12, 2004 10
Oklahoma State University
School of Chemical Engineering
Experimental Facility
• Two experimental apparatuses are used in current studies.
• The mass balance approach is employed in both.
• Expected uncertainty in the measurements is estimated at:– 2% for the pure fluids – 6% for the mixtures
November 12, 2004 11
Oklahoma State University
School of Chemical Engineering
Vacuum Pump
Pressure Temp.
Heat Exchanger
Air Temperature BathRuska Pump
Vent
Water Heaterand Pump
Pressure
Equ
ilibr
ium
Cel
l
Mag
netic
Pum
p
Temp.
Vent
Air Temperature Bath
Motor
SamplingValve
Gas ChromotagraphHe CH4 CO2 N2 C2 He
Experimental DesignThe experimental method employs a mass balance principle, based on careful volumetric measurements.
November 12, 2004 12
Oklahoma State University
School of Chemical Engineering
§ Volumetric measurements§ Moisture content § PVT density predictions § Adsorbed phase density estimates
Factors Affecting Equilibrium CBM Adsorption Measurements
November 12, 2004 13
Oklahoma State University
School of Chemical Engineering
CO2 and Ethane Adsorption on Activated Carbon (OSU)
0
2
4
6
8
10
0 2 4 6 8 10 12 14
Pressure (MPa)
Adso
rptio
n (m
mol/g
)
Carbon Dioxide, Gibbs
Carbon Dioxide, Absolute
Ethane, Gibbs
Ethane, Absolute
November 12, 2004 14
Oklahoma State University
School of Chemical Engineering
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
0 500 1000 1500 2000
Pressure, psia
Ads
orpt
ion,
mm
ol/g
Absolute Adsorption on Fruitland Coal at 115°F
CO2
Nitrogen
Methane
November 12, 2004 15
Oklahoma State University
School of Chemical Engineering
Mixture Adsorption on Illinois-6 Coal at 115°F
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 200 400 600 800 1000 1200 1400 1600 1800
Pressure (psia)
Abs
olut
e A
dsor
ptio
n (m
mol
/g c
oal) Pure CO2
Mixture Total
Pure CH4
CO2 in Mixture
CH4 in Mixture
LRC
Mixture is 60/40 CH4/CO2
November 12, 2004 16
Oklahoma State University
School of Chemical Engineering
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0.0 0.1 0.2 0.3 0.4 0.5
Normalized Slit Width
Loca
l Den
sity
, g/c
cStrategy: Use rigorous methodologies rooted in fundamentals to develop reliable models…
Bulk Gas
Adsorbate
Mean Field Approximation
November 12, 2004 17
Oklahoma State University
School of Chemical Engineering
Molecular Interactions
Gas Molecule
z L - z
Coal Surface
( ) ( ) ( )zLzz 2fs1fsfs −µ+µ=µ
ff
fs1 fs2
ρwall = 1 / b
Local Density
Area / 2
November 12, 2004 18
Oklahoma State University
School of Chemical Engineering
Modeling Approach
§ Articulate the physics of the adsorption phenomenon.
§ Rely on VLE and PVT data to provide required model inputs for fluid-fluid (εff , σff ) interactions.
§ Generate fluid-solid (εfs, σfs ) interactions applicable to all models; e.g.,
– εfs is estimated from theory or regressed– L is obtained from matrix pore distribution or regressed– A is regressed or obtained from accessible characterization
§ For matrix characterization, seek the ability to utilize limited adsorption data involving only one fluid.
November 12, 2004 19
Oklahoma State University
School of Chemical Engineering
Selected Theories for Modeling High-Pressure Adsorption
§ Simplified Local Density Model(Rangarajan et al., 1995; Fitzgerald et al., 2003)
§ Ono-Kondo Lattice Model(Aranovich et al., 1996; Sudibandriyo, 2003)
§ Two-Dimensional Equation of State Model(DeGance, 1992; Zhou et al., 1994; Pan et al, 2003)
November 12, 2004 20
Oklahoma State University
School of Chemical Engineering
SLD-EOS AdsorptionModeling: An Example
November 12, 2004 21
Oklahoma State University
School of Chemical Engineering
The SLD model:
§ Provides a consistent theory which accounts for adsorbate-adsorbate (fluid-fluid) and adsorbate-adsorbent (fluid-solid) molecular interactions
§ Delineates the adsorbent structural properties based on assumed physical geometries of the adsorbent
§ Predicts the adsorbed-phase density, which facilitates prediction of absolute gas adsorption
Why the SLD Model?
November 12, 2004 22
Oklahoma State University
School of Chemical Engineering
The Simplified Local Density (SLD) Model
z L-z -
AdsorbentSurface
Adsorbed Phase
Bulk Phase[ ]bayPTf i
bulki ,,,,ˆ r
[ ]bzazxzPTf iads
i ),(),(),(,,ˆ rρ
[ ]zfsiΨ
( )( )
( ) ( )0
ˆ)(),(ˆ
ln =−Ψ+Ψ
+
kT
zLz
yf
zzxf fsi
fsi
bulki
adsi
r
r ρEquilibrium Relationship:
November 12, 2004 23
Oklahoma State University
School of Chemical Engineering
Fluid- Fluid Interactions within Slit
Fluid-Fluid Interactions
The fugacity near the surface is a function of position:
( )( )
−+
++
−
−
+
−−
−
−
=
∑∑
∑
21)(1
21)(1ln
)(
)()(2)(2
22
)(
)(ln1
)(
)(2
)(
)(ˆln
bz
bz
za
zazx
b
bbzx
RTb
za
RT
Pb
RTz
P
RTz
P
b
bbzx
Pzx
zf
jijj
jijj
jijj
i
adsi
ρ
ρ
ρρ
Bulk- Phase Interactions[ ][ ]bbRT
Ta
bRT
P
ρρ
ρ
ρρ )21(1)21(1
)(
1
1
++−+−
−=PR-EOS:
November 12, 2004 24
Oklahoma State University
School of Chemical Engineering
Fluid-Solid Interactions
ρwall = 1 / b
σff / 20.142 nmσ
ss = 0.335 nm
Slit Length L
Local Density
Area / 2
z
Depiction of a SlitWe use Lee’s partiallyintegrated (10-4) potentialmodel todescribe thefluid-solid interactions.
( ) ( ) ( )( )
( )( )[ ]
∑
σ−+′
σ−
′
σσεπρ=Ψ
=
4
1 4
4
10
102
12
1
54)(
iss
ifsifs
ifsifsatomsfs
iizz
z
November 12, 2004 25
Oklahoma State University
School of Chemical Engineering
Extending SLD to Mixtures
§ We set Cij and Dij to zero for all component interactions in the gas phase
§ We regress Cij (Dij=0) in the adsorbed phase
∑∑=i j
ijji axxa ∑∑=i j
ijji bxxb
( ) 2/)C1(aaa ijjiij −+= ( ) 2/)D1(bbb ijjiij ++=
November 12, 2004 26
Oklahoma State University
School of Chemical Engineering
Database Used§ We have assembled the OSU Adsorption Database
which contains pure, binary, and ternary mixture adsorption measurements conducted at Oklahoma State University on eight different matrices.
§ Included in the database are details regarding:- Adsorbates, adsorbent, temperature, pressure,
composition, and moisture content
- Gibbs and absolute adsorption in both SI and English engineering units
- The expected experimental uncertainty for each adsorption measurement
November 12, 2004 27
Oklahoma State University
School of Chemical Engineering
OSU Adsorption Database
0.7 – 13.7328.2CH4, CO2, N2, C2H6Dry Illinois #6, Beulah Zap, Wyodak, Upper Freeport, Pocahontas
Coal
77-81
0.7 – 13.7319.3CH4, CO2, N2Wet LB Fruitland Coal74-76
0.7 – 12.4328.2CH4, CO2, N2 MixturesWet Tiffany Coal70-73
0.7 – 13.7328.2CH4, CO2, N2Wet Tiffany Coal67-69
0.7 – 12.4319.3CH4, CO2, N2 MixturesWet Illinois #6 Coal64-66
0.7 – 12.4319.3CH4, CO2, N2Wet Illinois #6 Coal61-63
0.7 – 12.4319.3CH4, CO2, N2 MixturesWet Fruitland Coal58-60
0.7 – 12.4319.3CH4, CO2, N2Wet Fruitland Coal55-57
0.7 – 12.4318.2CH4, CO2, N2 MixturesDry AC – F 40051-54
0.7 – 13.7318.2CH4, CO2, N2, C2H6Dry AC – F 40047-50
Pressure Range (MPa)
Temp (K)
AdsorbateAdsorbentSys. No.
November 12, 2004 28
Oklahoma State University
School of Chemical Engineering
Literature Database
0.44 – 9.19178 - 298N2AC, Coconut shell 20
0.05 – 0.8 294 - 351CH4, CO2AC, Norit RB118-19
0.02 – 20.2303 - 318CO2AC, Calgon F-40017
0.09 – 9.40233 - 333CH4AC, Coconut shell 16
0.008 – 6.0 298CH4, CO2, N2AC, Norit R1 Extra 13-15
0.05 – 3.35278 - 328CO2AC, F30/470 12
0.11 – 6.69296 - 480CH4, CO2AC, PCB-Calgon Corp. 10-11
0.003 – 3.84213 - 301CH4, C2H4, C2H6, CO2AC, BPL 6-9
0.0 – 13.5283 - 333CH4, C3H8Charcoal4-5
0.026 – 1.50311 - 422N2, CH4, C2H6AC, Columbia Grade L 1-3
Pressure Range (MPa)
Temp (K)
AdsorbateAdsorbentSys. No.
November 12, 2004 29
Oklahoma State University
School of Chemical Engineering
Literature Database – 2
0.03 – 6.00 298CH4, CO2, N2 mixturesAC, Norit R1 Extra 43-46
0.12 – 2.97301CH4,C2H4,C2H6mixtures
AC, BPL39-42
0.14 – 15.02298CH4, C2H6Zeolite, 13 X 37-38
0.056 – 1.15283 - 303CH4, C2H4, C2H6Zeolite, G5 34-36
2x10-5 – 0.21283 - 368CO2, H2S, C3H8H-Modernite 31-33
0.03 – 17.61298 - 348CH4, CO2, N2, C2H6Zeolite, Linde 5A 27-30
0.35 – 8.23298 - 348N2Zeolite, Linde 13 X 26
0.03 – 14.56 298N2, CO2AC, Norit R1 24-25
0.05 – 9.5303 - 383N2, CH4, C3H8AC, F30/470 21-23
Pressure Range (MPa)
Temp (K)
AdsorbateAdsorbentSys. No.
CBM Adsorbates: CH4, CO2, N2, C2H4, C2H6, C3H8, H2S
November 12, 2004 30
Oklahoma State University
School of Chemical Engineering
Why Activated Carbon?
§ Modeling of adsorption behavior on coals is complicated by: - The difficulty in characterizing the coal matrix
adequately
- Assessing the effect of water on the adsorption behavior
§ Dry activated carbon provides a simpler reference matrix for modeling adsorption.
§ Desired models for adsorption on wet coals should apply readily for adsorption on dry activated carbon.
November 12, 2004 31
Oklahoma State University
School of Chemical Engineering
We have developed:
§ State-of-the-art SLD, OK and 2-D EOS models and mixing rules to represent CBM adsorption equilibrium of pure fluids and mixtures within their experimental uncertainties.
§ Generalized and matrix-calibrated models to provide accurate predictions within one to three times the experimental uncertainties.
§ Improved computational capabilities, including robust algorithms for solving adsorption equilibrium for a variety of models.
Model Development
November 12, 2004 32
Oklahoma State University
School of Chemical Engineering
§ Despite their different theoretical bases, in general, 2-D EOS, SLD, and OK models give comparable results in their correlative and predictive abilities based on the gas properties and the accessible characterization of the adsorbent.
§ Specifically the models:
1. Correlate pure component adsorption within the experimental uncertainties (4% AAD).
2. Predict all pure component adsorption within 10% AAD.
Model Development - 2
November 12, 2004 33
Oklahoma State University
School of Chemical Engineering
4. Correlate the total and individual component adsorption in the binary systems within the expected experimental uncertainties.
5. Predict total adsorption for the binary and ternary systems studied within the expected experimental uncertainties.
6. Predict the individual component adsorption in the binaryand ternary systems within twice the expected experimental uncertainties.
7. Matrix-calibrated models provide reasonable predictions for high-pressure adsorption, typically within twice the expected experimental uncertainties
Model Development - 3
November 12, 2004 34
Oklahoma State University
School of Chemical Engineering
Sample Results
November 12, 2004 35
Oklahoma State University
School of Chemical Engineering
SLD-PR Model Representation of Methane Adsorption on Various Wet Coals
0.0
0.2
0.4
0.6
0.8
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0Pressure (MPa)
Gib
bs
Ad
sorp
tio
n (
mm
ol/g
) .
Fruitland #2 at 319 KIllinois #6 at 319 KTiffany at 328 KLower Basin Fruitland at 319 K
November 12, 2004 36
Oklahoma State University
School of Chemical Engineering
SLD Component Nitrogen Adsorption inMethane/Nitrogen Mixtures on Dry AC
0
1
2
3
4
0 500 1000 1500 2000Pressure (psia)
Nitr
og
en E
xces
s A
dso
rptio
n (m
mo
l/g)
Methane/Nitrogen 80/20Methane/Nitrogen 60/40Methane/Nitrogen 40/60Methane/Nitrogen 20/80Pure NitrogenRepresentationPredictions
November 12, 2004 37
Oklahoma State University
School of Chemical Engineering
Summary of Pure-Gas Adsorption Using 2-D Peng-Robinson (PR) EOS
Regressing A and εfs for each system
Generalized predictions
0.60.0504.7432Coals
--0.6178.61922Activated Carbons
--0.1992.41922Activated Carbons
Regressing σm,0, δ and εfs for each system
0.60.0674.9432Coals
--0.1081.4 1922Activated Carbons
Regressing a, b, and k for each isotherm
WAAERMSE%AADNPTSAdsorbents
November 12, 2004 38
Oklahoma State University
School of Chemical Engineering
Deviation Plot of the Two-ParameterOK Model Results
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
40.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0
Pressure, MPa
% D
evia
tio
n
Overall AAD = 3.6 %
November 12, 2004 39
Oklahoma State University
School of Chemical Engineering
0.0
2.0
4.0
6.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0
Pressure, MPa
Gib
bs
Ad
sorp
tio
n, m
mo
l/g A
C
303 K323 K343 K362 K 383 K Two-Parameter OK ModelGeneralized OK Model
OK Model Predictions of Methane Adsorptions onDry Activated Carbon at Various Temperatures
November 12, 2004 40
Oklahoma State University
School of Chemical Engineering
CH4 Absolute Adsorption for CH4 / CO2 onWet Fruitland Coal
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Pressure (psia)
CH
4 A
bsol
ute
Ads
orpt
ion
(mm
ol/g
)
Pure CH4
80% CH4
60% CH4
40% CH4
20% CH4
Wong-Sandler - Case 2
One-fluid - Case 1
November 12, 2004 41
Oklahoma State University
School of Chemical Engineering
0.0
0.1
0.2
0.3
0.4
0.5
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0
Pressure (MPa)
Gib
bs A
dsor
ptio
n (m
mol
/g)
Pure CH4Total CH4 in Mixture
Pure N2N2 in MixtureTwo-BIP OK ModelOK Predictions
Gibbs Adsorption of a 50/50 Mole % CH4 / N2 Feed Mixture on Wet Tiffany Coal at 327.6 K
November 12, 2004 42
Oklahoma State University
School of Chemical Engineering
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0
Pressure (MPa)
Gib
bs A
dsor
ptio
n (m
mol
/g)
TotalCO2CH4N2OK from PureOK form Pure & Binary
Total and Individual Gibbs Adsorption of a 10/40/50 Mole % CH4 / N2/CO2 Feed Mixture on Wet Tiffany Coal at 327.6 K
November 12, 2004 43
Oklahoma State University
School of Chemical Engineering
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0
Pressure, MPa
Gib
bs
Ad
sorp
tio
n, m
mo
l/g A
C
CO2CH4N2C2H6OK ModelOK Predictions
Matrix-Calibrated OK Model Predictions of Pure-Gas Adsorption on Dry Activated Carbon at 318.2 K
November 12, 2004 44
Oklahoma State University
School of Chemical Engineering
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0
Pressure (MPa)
Gib
bs
Ad
sorp
tio
n (
mm
ol/g
Co
al)
WyodakBeulah ZapIllinois-6PocahontasUpper FreeportTwo-Parameter OK ModelOK Predictions
Matrix-Calibrated OK Model Predictions of CO2 Adsorptions on Dry Coals at 328.2 K
November 12, 2004 45
Oklahoma State University
School of Chemical Engineering
Pressure (MPa)
0
5
10
15
20
25
0.0 2.0 4.0 6.0 8.0 10.0
CH
4A
bso
lute
Ad
sorp
tio
n (
mm
ol/g
)
Surface area and fluid-solid Interactionregressed based on 12 Data points 233 K
293 K
273 K
253 K
313 K
333 K
Matrix-Calibrated 2-D PR EOS Model Predictions of Methane Absolute Adsorption on Dry Activated Carbon
November 12, 2004 46
Oklahoma State University
School of Chemical Engineering
Closure§ The SLD-EOS, OK, and 2D EOS, frameworks are
effective for modeling high-pressure mixture adsorption.
§ The use of matrix-calibrated models will minimize the experimental effort required to obtain accurate adsorption predictions for a specific CBM site.
§ A potential exists for developing a priori predictive models using fully-generalized parameters determined by accessible adsorbate and adsorbent characterizations.
November 12, 2004 47
Oklahoma State University
School of Chemical Engineering
However! To fully exploit the potential of the models in CBM recovery and CO2 sequestration processes, we need to:
§ Develop a more rigorous approach to account for the effect of water on CBM adsorption systems.
§ Develop an accurate equation of state, which exhibits accurate hard-sphere limiting behavior, to improve modeling of high-pressure gas adsorption.
§ Systematically-selected measurements should be conducted to expand our database on mixtures adsorption and delineate the effects of moisture content and competitive adsorption.