gasem-co2-presentation (cbm)

8/7/2019 Gasem-CO2-presentation (CBM)

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March 6, 2002 1

Oklahoma State University

School of Chemical Engineering

Modeling of Gas Adsorptionon Coalbeds

K. A. M. GasemZ. Pan

J. E. FitzgeraldM. Sudibandriyo

R. L. Robinson, Jr.


Sponsored by theU.S. Department of Energy


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RATIONALE

Modeling of the adsorption behavior of coalbed gases(methane, CO 2, nitrogen) is essential in CBMproduction and in CO 2 sequestration.

Further, knowledge of the competitive adsorption ofCBM gases is required to elucidate mechanisms forenhanced recovery of CBM and CO 2 sequestrationprocesses.

Reliable adsorption predictions cannot be generatedusing simple, empirical models. Accurate modelsrequire sound theory, judicious approximations, andaccurate experimental information.


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Cleat system wherefree gas resides

Micropores where

Adsorbed gas resides

Zoom-in viewof model micropore

Coalbed Adsorption Phenomenon


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Desorption

Diffusion toCleats

Free Gas DiffusionThrough Cleats

Reduce cleat pressure by producing water

Methane desorbs from matrix to cleats Methane and water flow to well bore

To Well-Bore

CoalMatrix

Water

Methane

Primary Recovery


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0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0 500 1000 1500 2000

Pressure, psia

Adsorption, m

mol/g

Absolute Adsorption on Fruitland Coal at 115F

CO 2

Nitrogen

Methane


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CoalMatrix

To WellBore

MethaneDesorption

CO 2Adsorption

Diffusion

CO 2Injection

WaterMethane

CO 2

CO 2 displaces methane after injection No initial breakthrough of CO

2 Higher cleat pressure results in faster flow

CO 2 Enhanced Recovery


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Theory / Practice

Theory: Improve our understanding of high-pressureadsorption through rigorous methodologies.

Practice: Provide reliable equilibrium adsorptionmodels for optimum CBM production andCO 2 sequestration.

Strategy: Use rigorous methodologies to developreliable adsorption models for industrial

practice. Goal: Develop reliable coal-structure-based

generalized predictions using simple,accessible characterizations.


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Current Issues

Adsorption modeling Coal characterization

Coal structure-based model generalizations

Estimates for adsorbed-phase density

Effect of moisture on modeling adsorption capacity

Matrix swelling

Binary and ternary pvT data

Balancing computational efficiency and reliability


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Current Issues: Adsorbed-Phase Density

Why do we need adsorbed-phase density? Current estimation methods:

! Traditional

! Experimental approximation! Model-based:

2D equations of state, SLD theory, Ono Kondo theory

What is the impact?


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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

Local Density, g/cc

Molecular Interactions: Mean Field Approximation

Bulk Ga s

Adsorbate


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The excess adsorption is defined as follows

( )

( )bulkadsGibbs

VbulkadsGibbs

Vn

or

dVn

=

=

Excess and Absolute Adsorption

The absolute adsorption is defined as

ads

bulk

Gibbsadsadsabs

1

nVn

==


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Estimation of Phase Volume and Density

y = -0.360x + 0.365R2 = 0.994

0.00

0.05

0.10

0.15

0.20

0.250.30

0.35

0 0.2 0.4 0.6 0.8 1 1.2Density, g/cc

Adsorption, g CO2/g-carbon

Phase Density1.02 g/cc

0 400 800 1200 1600 2000

Pressure, psia9200

CO2 on activated carbon at 113 oF


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CO 2 and Ethane Adsorption on Activated Carbon (OSU)

0

2

4

6

8

10

0 2 4 6 8 10 12 14

Pressure (MPa)

Adsorption (mmol/g

Carbon Dioxide, Gibbs

Carbon Dioxide, AbsoluteEthane, Gibbs

Ethane, Absolute


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Impact of Adsorbed-Phase Density: CO 2 on Activated Carbon at 113 o F

0.0

2.0

4.0

6.0

8.0

10.0

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Pressure (psia)

Adsorption (mmol/g AC)

ZGR -- 0.98 g/ccOK -- 1.00 g/ccExperimental -- 1.02 g/ccOKv -- variableSLDv -- variableZGRv -- variable

Traditional -- 1.18 g/ccGibbs Adsorption


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Current Issues: Adsorption Modeling

We seek simple, reliable adsorption equilibriummodels that are suitable for generalized predictionsand reservoir simulations.

Such models should be capable of! Precisely representing pure and mixture isotherms

! Facilitating a priori predictions


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Equilibrium Modeling: Three Methods

1. Enhanced forms of the Langmuir isotherms-- provide simple data correlation

2. Two-dimensional equations of state (2-D EOS)

(a) Cubic EOS (b) Segment-Segment EOS

-- facilitate generalized simulations

3. Simplified-Local-Density (SLD) models

-- account for surface structure and near-critical behavior


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The Langmuir & Loading Ratio Correlation (LRC)

P = pressure yi = gas phase mole fraction of component i

i = LRC exponent for component i i = amount adsorbed of component i Li, B i = Langmuir/LRC model coefficients

( )( )

+=

jii

ii

i

ii

i

PyB1PyB

L


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LRC Current Capability

The loading-ratio correlations:

Represent absolute pure-component and mixed-gastotal adsorption precisely

Yield reasonable predictions for these systems Represent individual-component adsorption in

mixtures less precisely, especially the less-

adsorbed ones Require adsorbed-phase density estimates


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LRC Representations: Illinois-6 Coal

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)

Absolute Adsorption (mmol/g coal) Pure CO2

Mixture TotalPure CH4

CO2 in Mixture

CH4 in Mixture

LRC

Mixture is 60/40 CH4/CO2


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2-D Equations of State (OSU, 1992)

[ ]A U W RT m

+

+ + =2 21

1( )

( )

=ji

x xi j ij =ji

x xi j ij

ij i j= +( ) / 2 ij i j=

EOS m U WVDW 1 0 0SRK 1 1 0PR 1 2 -1Eyring 1/2 0 0ZGR 1/3 0 0


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2D EOS Current Capability

2-D EOS models:

Describe CBM pure-component and mixed-gas totaladsorption data with sufficient precision

Yield reasonable predictions for these systems Represent individual-component adsorption less

precisely, especially the less-adsorbed ones

Employ inadequate repulsive terms Do not account for variations in coal structure


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2D EOS Representations: Illinois-6 Coal

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)

Absolute Adsorption (mmol/g coal)

Pure CO2Mixture TotalPure CH4CO2 in MixtureCH4 in MixtureZGR

Mixture is 60/40 CH4/CO2


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The EOS-SLD Adsorption Model

The fluid-solid interaction potential equals the sum of thepotentials between the gas molecule and the two sides of the slit.

Gas Molecule

z L - z

Coal Surface

( ) ( ) ( )zLzz 2fs1fsfs +=


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EOS-SLD Current Capability

The EOS-SLD models:

Account for variations in coal structure

Provide a viable framework for generalized predictions

Have produced promising preliminary results formixture adsorption modeling

Employ inadequate repulsive terms


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CO 2 Adsorption Using Modified SLD-PR

0

1

2

3

4

5

6

7

8

0 2 4 6 8 10 12 14

Pressure (MPa)

Gibbs Excess

(mmol/g)

Experimental Data OSU

Original SLD

Modified SLD


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Sample Pure-Gas Adsorption Model Results

%AAD

Nitrogen Methane CO 2 Ethane

Dry Activated Carbon

LRC 0.3 0.6 6.1 5.8

ZGR 0.4 0.7 5.2 5.6ZGR Gibbs 0.4 0.5 1.3 3.3Original SLD 0.5 0.8 14.9 29.7Modified SLD 0.4 0.6 2.2 6.1

Wet Fruitland Coal

LRC 1.1 0.7 3.3ZGR 1.9 0.7 3.1

Original SLD 1.5 0.6 3.9Modified SLD 1.1 0.6 3.6


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Conclusions 2-D EOS and the EOS-SLD models are better

equipped than Langmuir-type correlations for modelingCBM adsorption isotherms.

The EOS-SLD models appear both accurate and

amenable to structure-based generalization.

Improved mixing rules and additional mixture data arerequired to improve predictions for individual-

component adsorption. More efforts should be dedicated to structure-based

model generalizations.


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Modeling Work in Progress at OSU

Extend the EOS-SLD and Ono Kondo models tomixture predictions.

Implement other potential models for fluid-solid

Interactions. Incorporate other geometries within the EOS-SLD

framework.

Develop theoretically-based equations of state thatfeature more accurate fluid-fluid repulsive terms.

gasem-co2-presentation (cbm)

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