Towards the modeling of natural gas systemsTowards the modeling of natural gas systems containing water and selected chemicals

June 15 2012June 15, 2012GERG academic network event 2012Eirini Karakatsani, post-docDepartment of Chemical and Biochemical Engineering

Contents0 Background of the project0. Background of the project

1. Target of the project

2. Existing model

3. Defining parameters for NG components

4. Results for multicomponent mixtures

5 Conclusions5. Conclusions

6. Future plans / work

0. Background of the project: a GERG project“Calculating Dew Points for Natural Gas containing Water and/or“Calculating Dew Points for Natural Gas containing Water and/or

“The European Gas Research Group, wasfounded in 1961 to strengthen the Gas Industry

Calculating Dew Points for Natural Gas containing Water and/or Calculating Dew Points for Natural Gas containing Water and/or selected Production Chemicals”: selected Production Chemicals”:

founded in 1961 to strengthen the Gas Industrywithin the European Community by promoting

effective, gas-related R&D. GERG priorities are technical informationexchange and collaborative R&D, with projects carried out byg j ydedicated, multi-disciplinary Project Teams, which can includeacademics, manufacturers and other non-member organisations”(www.gerg.eu).

Danish Gas Technology Centre

1/26

1. Targets of the project M i t t• Main target:To evaluate and compare the performance of CPACPA EoS vs.GERGGERG waterwater calculation method regarding the calculation ofGERGGERG--waterwater calculation method regarding the calculation ofDPs of NG systems containing H2O and traces of selectedproduction chemicals

In parallel: • To develop databases of reliable experimental data and then use

them to establish and suggest model parameters/modifications

• To perform different data analyses

• To provide a user friendly software for calculation of dew points• To provide a user-friendly software for calculation of dew points

2/26

1. Targets of the project: the main target

E l t d CPA GERG t• Evaluate and compare CPA vs GERG-water model•• CPACPA: a model with a wide range of applicability,

preliminarily tested for the targeted applications (G.Folas et al.,

FPE 252(2007) 162 174) vsFPE 252(2007), 162-174) vs.

•• GERGGERG--waterwater: an ISO-standard model with more limitedapplicability range** based on PR EoS (currently underapplicability range based on PR EoS (currently underexpansion), specifically designed to correlate H2O contentand DP in NG.

** 15ºC ≤ T ≤ 5ºC 5b ≤ P ≤ 100b15ºC ≤ T ≤ 5ºC 5b ≤ P ≤ 100b* * --15ºC ≤ T ≤ 5ºC, 5bar ≤ P ≤ 100bar, 15ºC ≤ T ≤ 5ºC, 5bar ≤ P ≤ 100bar, CHCH44 ≥ 40.0%, N≥ 40.0%, N22 ≤ 55.0%, CO≤ 55.0%, CO22 ≤ 30.0%, ≤ 30.0%, CC22HH66 ≤ 20.0%, C≤ 20.0%, C33HH88 ≤ 4.5%, ≤ 4.5%, ii--CC44HH1010 ≤1.5%, n≤1.5%, n--CC44HH1010 ≤ 1.5%,≤ 1.5%,ii CC44HH1010 1.5%, n1.5%, n CC44HH1010 1.5%, 1.5%, ii--CC55H1H122 ≤ 1.5%, neo≤ 1.5%, neo--CC55HH1122 ≤ 1.5%, ≤ 1.5%, nn--CC55H1H12 2 ≤ 1.5%, C6+ ≤ 1.5% ≤ 1.5%, C6+ ≤ 1.5%

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2 E i i d l d l f F S2.Existing model: separate models for F+S• Fluid phases: CPA

• Solid phases: CPA + vdW-P (Folas et al., FPE 252(2007),162):

• The fugacity of ice is calculated by correcting the saturation fugacity at g y y g g ythe same temperature by the Poynting factor.

• The fugacity of water in the hypothetical empty hydrate phase is described assuming that the hypothetical empty hydrate phasedescribed assuming that the hypothetical empty hydrate phasebehaves as a solid phase. The following 2 simplifications are implied:

• the hydrate partial molar volume equals to the molar volume,

• the vapor pressure of the hypothetical empty hydrate structure is relativelysmall (of the order of 10-3 MPa) so that the fugacity coefficient of watervapour over the empty hydrate phase is set to unity.

expEH

w

P EHEH EH EH w

W w wP

Vf P dPRT

4/26

2 E i i d l h dW P d l2. Existing model: the vdW-P model• “CPA –CERE” (Folas et al., FPE 252(2007),162):

• The chemical potential of the hydrate phase is obtained from the vdW-P model:

ln 1H EHW W i miRT

where 1

mi mmi

C fC f

and is based on the following assumptions:

1. each hydrate cavity can only host one guest molecule (not true for

guests W W i mi

i m

1 ki kguests k

C f

N2), (J.Phys.Chem.B 2010, 114,9602-7)

2. the encaged molecules do not distort the cavity (not true for large guest molecules like CO2), (Chem.Eng.Sci. 49(8), 1994, 1161)g 2), ( g ( ), , )

3. the interactions between encaged molecules can be neglected (only averaged interactions between the guest molecules and the closest shell of H2O molecules are taken into account) (not true according toshell of H2O molecules are taken into account) (not true according to MC simulations results), (Annals of the New York Academy of Sciences, 715, 545, 1994) and

4 spherical symmetry is assumed (this treatment only works well for4. spherical symmetry is assumed (this treatment only works well for hydrates formed by monatomic gases, f.ex. Ar) (Geoch. et Cosmoch. Acta, 69 (18), 4411, 2005). 5/26

3. Parameters: Simplified Parish-Prausnitz approach3. Parameters: Simplified Parish Prausnitz approach

expmi mimi

A BCT T

2 parameters fitted to expt. data per guest moleculeand structure 2-8 parameters / guest molecule

(+) (-)The rate of hydrate dissociation is dependent not only on the overall

Empirical relationdependent not only on the overall occupancy, but also on the cage-specific occupancy it is important to consider the relative occupancies of

Initially suggested for the temperature range (260-300)KOptimal but not real potentialto consider the relative occupancies of

the small and large cages (Debenedetti, J.Phys.Chem.A 2011, 115, 6102)

Optimal but not real potentialparameters (?) RecentlyPapadimitriou et al. obtainedoptimum values by matching A andoptimum values by matching A and B to the cavity occupanciesresulting from GCMC simulations:

Effective approach in the sense of smoothing of the errors caused by the choice of a true function for intermolecular interaction, of rules for combination of potential parameters, etc.

1

i

i

C T PC T P

6/26

3 How to define PP parameters? (contradictions)3. How to define PP parameters? (contradictions)

Cavity occupancy of CH4 Proc ICGH 2011Proc. ICGH 2011, Papadimitriou et al.

•• LundgaardLundgaard andand MollerupMollerup ((19911991)): “by fitting to dissociation Ps along theHIV line, the Kihara parameters are obtained independent of the mutualsolubility of the gas and water. Further, the φs in that region are close to1 so that the Kihara parameters are rather insensitive to the choice ofEoS”

vs. •• BakkerBakker etet alal.. ((19961996)): “it is important to use as many independently

bt i d d t ibl b l ti b d i l t fobtained data as possible, because a solution based on a single set ofdata may differ considerably from other sets. Most studies have includedonly a small part of the available data”.7/26

3 How to define PP parameters? (approach used)3. How to define PP parameters? (approach used)•• UseUse ofof thethe mostmost recentrecent availableavailable exptexpt datadata ((bothboth HIVHIV andand HLV)HLV)

•• UseUse ofof onlyonly singlesingle hydratehydrate datadata wherewhere possiblepossibleUseUse ofof onlyonly singlesingle hydratehydrate datadata wherewhere possiblepossible

•• UseUse ofof thethe mostmost recentrecent CPACPA parametersparameters forfor NGNG componentscomponents

•• CheckingChecking thethe internalinternal consistencyconsistency ofof datadata beforebefore usingusing themthemgg yy gg

F.ex. for CH4 str.I parameters use of:Yasuda and Ohmura (2008) (244.2-274.7)KMakogon and Sloan (1996) (193-260)K 200

250

300Jager and SloanYasuda and OhmuraMakogon and SloanAndersonNixdorf and OellrichSl lMakogon and Sloan (1996) (193 260)K

Jager and Sloan (2001) (291.86-303.48)KAnderson (2004) (150-318)KNixdorf and Oerrlich (1997) (273.49-293.57)K 100

150

P(ba

r)

Sloan et al.

Adisasmito,Franck&Sloan(1991) (273.4-286.4)KInstead of:

Roberts et al.(1940)Deaton and Frost (1946) (both C1 H2O and C1 C2 H2O data used)

0

50

140 160 180 200 220 240 260 280 300 320T(K)Deaton and Frost (1946) (both C1-H2O and C1-C2-H2O data used)

Marshall et al. (1964)Kobayashi and Katz (1949)McLeod and Campbell (1961) (both C1-H2O and C1-C2-H2O data used)

T(K)

p ( ) ( )Holder and Grigoriou (1980) (inconsistent C1-C2-H2O data)

8/26

3 Results: new PP parameters (I)3. Results: new PP parameters (I)Small cavity Large cavity Mean

errorin Tin T (%)

Comp. Str. Amix103(K/bar) Bmi (K) Amix103(K/bar) Bmi (K)CH4 I 9 99997 1969 77 316 434 2048 66 0 069CH4 I 9.99997 1969.77 316.434 2048.66 0.069C2H6* I 0 0 57.0184 3040.91 0.042

II 0 0 9.54095 4000 0.086CO2** I 0.108734 3400 43.1146 2804.85 0.33

II 0.1 3119.67 63.11 3500 0.55

* Udachin et al. found in 2002 that the small cage is weakly occupied (~5%), notseen in previous NMR work (neglected)

**Big discussions about which cavities are occupied and about how and ifsolubility should be taken into account According to Seitz et al (1987) Sloan etsolubility should be taken into account. According to Seitz et al. (1987), Sloan etal. (1992), Bakker et al.(1996) and Sung et al. (2000) CO2 can only enter thelarge cavities of structure I. According to Caroll and Mather and Bakker, theactivity coefficient can be put equal to 1, but not according to Sandler and Klauday p q , g(CO2>C1>N2>C2>C3>C4 solubility of pure gas in water, Tang et al.J.Chem.Eng.Data 2011, 56, 1025).

9/26

3 Results: new PP parameters for C3H8 (II)3. Results: new PP parameters for C3H8 (II)Large cavity Average error in

T (%)Amix103(K/bar) Bmi (K)

MC approach for H2O 79.6303 3912.8 9.48Twu expression for H2O 79.8177 3942.2 8.87pMC approach for C3 99.9992 3794.48 0.29

• Nasrifar and Bolland concluded that the Twu expression for alpha function isrecommendable and orks ell for the prediction of Ps of p re compo nds atrecommendable and works well for the prediction of Ps of pure compounds atlow Ts (”Predicting Natural Gas Dew Points from 15 EoS”, Energy & Fuels,2005, 19, 561).

• On the other hand, Neau et al. Conclude that ”our study of the strengths and, y gweaknesses of the Soave, Twu and Boston-Mathias alpha function using theRedlich-Kwong EoS gave evidence that, for current industrial applications,there are no theoretical objective reasons to reject the Soave function, aswell as for the modeling of Ps or for the prediction of derived thermodynamicswell as for the modeling of Ps or for the prediction of derived thermodynamicsproperties” (”The Soave, Twu and Boston-Mathias alpha functions in cubicEoS. Part I. Theoretical analysis of their variations according to temperature”,FPE 228-229, 2005,213)., , )

10/26

3. Testing the new parameters (I)1

IHV / LHV equilibrium conditions in C2-H2O

Yasuda and Ohmura expt. data

g p ( )25 N2-CH4 (strI)

MPa

dataCPA old parameters

CPA new parameters

15

20

(MP

a)

P / M

5

10

Pre

ssur

e

expt. Data, OellrichCPA,old parameters

0,1240 250 260 270 280

T / K

0278 280 282 284 286 288 290 292 294

Temperature (K)

new parameters CH4

10

a)

CO2-H2O1,3

1,4

1,5

Pa) CH4-H2O

p ( )

1

ress

ure

( MPa

expt. data, Yasuda-Ohmura 1

1,1

1,2P

ress

ure

(M

expt.data,Yasuda&OhmuraCPA ld CH4 t

0,1240 250 260 270 280

Pr

Temperature (K)

CPA,CO2 strI,2parameters

0,8

0,9

240 245 250 255 260Temperature (K)

CPA, old CH4 parametersCPA, new CH4 parameters

11/26

3. Testing the new parameters (II)g p ( )• From single gas systems to multicomp mixts:

• Big challenge: mixed hydrates

2,5

3

3,5

Pa)

sIsII

2,5

3

3,5

Pa)

sII

t

1,5

2

2,5

Pres

sure

(MP

1,5

2

2,5

Pres

sure

(MP new parameters,

sI

0,5

1

0 0,2 0,4 0,6 0,8 10,5

1

0 0,2 0,4 0,6 0,8 1l f ti f thmole fraction of methane mole fraction of methane

E.Sato et al., Jpn. J. Appl. Phys., 46(9A), (2007), 5944

T = 274.15K, xCH4 = 0.72-0.994 (S.Subramanian et al. Ch E S i 55(2000) 1981)Chem.Eng.Sci.55(2000), 1981)

12/26

3. Testing the new parameters: with chemicals3. Testing the new parameters: with chemicals • Inhibiting effect of TEG on CH4 + C2H6 hydrate

formation conditions

4

4,5

5

2 5

3

3,5

e (M

Pa)

1,5

2

2,5

Pre

ssur

e

20.2% TEG, Wu and Englezos, 2006

40% TEG Wu and Englezos 2006

0

0,5

140% TEG, Wu and Englezos, 2006

CPA, str I

CPA, str II

Wu and Englezos: “A noteworthy property of the CH4+C2H6 system is that although CH4and C H are known to form str I hydrate the binary gas mixture MAY form structure II

266 268 270 272 274 276 278 280 282 284Temperature (K)

13/26

and C2H6 are known to form str I hydrate, the binary gas mixture MAY form structure IIhydrate at certain compositions and temperatures (J.Chem.Eng.Data 2006, 51, 1811)”.

3. Testing the new parameters: the effect of kij3. Testing the new parameters: the effect of kij• Inhibiting effect of TEG on CH4 + C2H6 hydrate

formation conditions

4

4,5

5

2 5

3

3,5

e (M

Pa)

1,5

2

2,5

Pre

ssur

e

20.2% TEG, Wu and Englezos, 2006

40% TEG Wu and Englezos 2006

0

0,5

140% TEG, Wu and Englezos, 2006

CPA, str I

CPA, str II

Wu and Englezos: “A noteworthy property of the CH4+C2H6 system is that although CH4and C H are known to form str I hydrate the binary gas mixture MAY form structure II

266 268 270 272 274 276 278 280 282 284Temperature (K)

14/26

and C2H6 are known to form str I hydrate, the binary gas mixture MAY form structure IIhydrate at certain compositions and temperatures (J.Chem.Eng.Data 2006, 51, 1811)”.

4 Multicomponent Mixtures of Tohidi et al

C1 90 85 C4 0 11200

4. Multicomponent Mixtures of Tohidi et al. J.Chem.Eng.Data 2011, 56, 2932.

C1 90.85 nC4 0.11C2 6.13 CO2 0.03C3 1.1 N2 1.65140

160

180

pm)

CPA + Kihara potential

GERG-water

expt data, 3.45MPa (Tohidi et al 2011)

iC4 0.13

80

100

120

er c

onte

nt (p

p 2011)expt. data, 6.89MPa

expt. data, 10.34MPa

expt data 13 79MPa80

20

40

60wat

e expt data, 13.79MPa

60

70

pm)

expt data, 13.79MPa

0235 240 245 250 255 260 265 270 275

Temperature (K)

30

40

50

er c

onte

nt (p

10

20wat

1715/26

0235 240 245 250 255 260 265 270 275

Temperature (K)

4. Multicomponent Mixtures of Oellrich and Klaus GERG Technical Monograph TM 14

Component NG1Helium 0,015

200

NG1 water content

t d t O ll i h t l 100bHelium 0,015HydrogenOxygen

140

160

180

)

expt data, Oellrich et al, 100bar

SRK

PR

Nitrogen 0,84CO2 0,109methane 98,197

100

120

cont

ent (

ppm

VPT

sCPA

ethane 0,564propane 0,1892 th l 0 029

40

60

80

wat

er c GERG-water

2-methylpropane 0,029n-butane 0,038

2,2-0

20

255 257 259 261 263 265 267 269 271 273 275 277 279 281 283 285( )

HYDRAflash software used

dimethylpropane 0,0012-methylbutane 0,007n-pentane 0,006

Temperature (K)

AAD (%)

CPA VPT PR SRK GERG‐water

16/26

p ,C6+ 0,007 3,1 3,1 5,1 4,0 6,6

4 Glycol Parameters and water glycol BIPs4. Glycol Parameters and water-glycol BIPsFluid Ass.scheme a0 (L2bar/mol) b (L/mol) c1 ε (bar L/mol) β

MEG 4C 10 8190 0 0514 0 6744 197 52 0 0141MEG 4C 10.8190 0.0514 0.6744 197.52 0.0141

DEG 4C 26,4080 0,0921 0,7991 196,84 0,0064

TEG 4C 39 1260 0 1321 1 1692 143 37 0 0188TEG 4C 39.1260 0.1321 1.1692 143.37 0.0188

System Combining BIP Type of data used during

Derawi et al, Ind. Eng. Chem. Res. 2003, 42, 1470.System Combining

rulesBIP Type of data used during

regression

MEG-H2O Elliott -0.115 VLE

MEG-H2O* CR-1 5.6295*104 T-0.2313 VLE & SLE

DEG-H2O CR-1 -0.115 VLE

TEG-H2O CR-1 -0.211 VLE

Derawi et al, Ind. Eng. Chem. Res. 2003, 42, 1470.*H hi hi t l FPE 2009 276 24

17/26

*Haghighi et al, FPE 2009, 276, 24.

4 Multicomponent mixtures with MEG (T-dependent vs4. Multicomponent mixtures with MEG (T-dependent vs. T-constant BIP)

300320340

C1-C2-C3-iC4-nC4-iC5-nC5-C6-C7-N2-CO2 (88.21-5.78-1.78-0.19-0.3-0.06-0.07-0.06-0.01-1.4-2.15)

10% MEG, Haghighi et al. 200930% MEG Haghighi et al

250C1-C2-C3-nC4-nC5-N2 (84.13-4.67-2.34-0.93-0.93-7)

220240260280300 30% MEG, Haghighi et al.

2009CPA, k(H2O-MEG) fixed

CPA, k(H2O-MEG) = f(T)

200

r)

120140160180200

Pres

sure

(bar

)

100

150

Pres

sure

(bar

406080

100120P

50

020

275 277,5 280 282,5 285 287,5 290 292,5 295T emperature (K)

0240 250 260 270 280

Temperature (K)

18/26

50% wt MEG, Chapoy & Tohidi,201270% wt MEG, Chapoy & Tohidi 2012CPA-T-dependent BIP(H2O-MEG)

4 Multicomponent mixtures with MEG (T-dependent vs

380400

C1-C2-C3-iC4-nC4-iC5-nC5-N2-CO2 (88.3-5.4-1.5-0.2-0.3-0.1-0.09-2.39-1.72)

4. Multicomponent mixtures with MEG (T-dependent vs. T-constant BIP)*

260280300320340360380

50% MEG, Haghighi et al. 2009

CPA, k(MEG-H2O) fixed

CPA k(MEG-H2O) = f(T)

140160180200220240260

P / b

arCPA, k(MEG-H2O) = f(T)

20406080

100120140

020

255 257,5 260 262,5 265 267,5 270 272,5 275 277,5 280T / K

•• 2626 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith alcoholsalcoholspp

•• 2828 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith glycolsglycols

•• 44 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith glycerolglycerol

19/26

•• 1717 literatureliterature referencesreferences ofof waterwater contentcontent experimentalexperimental datadata

•• 6464 literatureliterature referencesreferences ofof experimentalexperimental datadata withoutwithout chemicalschemicals

4. *But also for binary mixtures… 1000 1000

pm)

Water-methane (3.44MPa)

pm)

Water-methane (6.89MPa)

100

ter c

onte

nt(p

Chapoy et al. 2010100

ter c

onte

nt(p

Expt. Data (Chapoy et al, 2010)CPA

wa

CPA (kij=f(T))

GERG-water

wa (kij=0.0098)

GERG-water

10250 255 260 265 270 275 280 285 290

Temperature(K)

10250 255 260 265 270 275 280 285 290

Temperature(K)

%AAD of water content (both VLE and HVE data)%AAD of water content (both VLE and HVE data)Pressure(MPa) CPA (kij≠f(T)) CPA (kij=f(T)) GERG-water

3.44 6.2 5.5 8.8

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6.89 3.4 3.8 10.6

4. Multicomponent mixtures with MEG4. Multicomponent mixtures with MEG

320340

C1-C2-C3-iC4-nC4-iC5-nC5-C6-C7-N2-CO2 (88.21-5.78-1.78-0.19-0.3-0.06-0.07-0.06-0.01-1.4-2.15)

10% MEG, Haghighi et al. 250C1-C2-C3-nC4-nC5-N2 (84.13-4.67-2.34-0.93-0.93-7)

240260280300320 2009

30% MEG, Haghighi et al. 2009CPA, k(H2O-MEG) fixed

CPA, k(H2O-MEG) = f(T)

200

140160180200220

ssur

e(b

ar)

100

150

ress

ure

(bar

)

6080

100120140

Pres

50

P0

2040

275 277,5 280 282,5 285 287,5 290 292,5 295T emperature (K)

0240 250 260 270 280

Temperature (K)

50% wt MEG, Chapoy & Tohidi,201270% wt MEG, Chapoy & Tohidi 2012CPA-T-dependent BIP(H2O-MEG)

21/26

4. Multicomponent mixtures with MEG4. Multicomponent mixtures with MEG

380400

C1-C2-C3-iC4-nC4-iC5-nC5-N2-CO2 (88.3-5.4-1.5-0.2-0.3-0.1-0.09-2.39-1.72)

260280300320340360380

50% MEG, Haghighi et al. 2009CPA, k(MEG-H2O) fixed

140160180200220240260

P / b

ar

20406080

100120140

020

255 257,5 260 262,5 265 267,5 270 272,5 275 277,5 280T / K

•• 2626 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith alcoholsalcoholspp

•• 2828 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith glycolsglycols

•• 44 literatureliterature referencesreferences ofof experimentalexperimental datadata withwith glycerolglycerol

22/26

•• 1717 literatureliterature referencesreferences ofof waterwater contentcontent experimentalexperimental datadata

•• 6464 literatureliterature referencesreferences ofof experimentalexperimental datadata withoutwithout chemicalschemicals

5. Conclusions5. Conclusions• New PP parameters for C1, C2, C3 and CO2 have been

derived.• The new parameters have been tested under many

different conditions (low temperatures, hydrate structure transitions, HVE, HLE,…), and their performance was found comparable or in some cases, better than the one of older parametersolder parameters.

• HLE and structure transitions predictions were found to be the most difficult modeling challengesthe most difficult modeling challenges.

• The water content in several binary and multicomponentmixtures of NG components has been calculated with tu es o G co po e ts as bee ca cu ated tGERG-water and predictive CPA EoS. CPA seems to perform better than GERG-water method even when used in a purely predictive way.

23/26

5 Conclusions5. Conclusions• The new PP parameters for C1 and C2 perform better

compared to the older ones when predicting hydratecompared to the older ones when predicting hydrateformation in the presence of glycols (MEG, DEG, TEG).

• Inconsistent experimental data have been found in someInconsistent experimental data have been found in somecases (C1-H2O-TEG, C3-H2O-MEG and C3-H2O-DEG).

• Interestingly enough, the use of a T-dependent BIP for theg y g , psystem H2O-glycol does not always seem to providebetter results.

24/26

6 Future plans / work6. Future plans / work• Binary interaction parameters will be incorporated in the CPA model

( d l l i ill b d)(and calculations will be repeated).

• CPA will be combined with Kihara potential (and calculations will be repeated)repeated).

• Consistency tests of experimental data are under way (in collaboration with PhD student Ali Eslamimanesh).

• Concerning the solid model, the following improving attempts will be made:

• Multiple occupancy (derivation of new N2 parameters),

• Spherical symmetry (especially relevant for CO2)

• Other potentials (Paricaud, Anderson et al.) may be tested.

25/26

6 Future plans: participation to events6. Future plans: participation to events• 3rd International Gas Processing Symposium (Doha,

Qatar, 5-7 March 2012)

• 17th CHIGP meeting (15 May 2012)g ( y )

• CERE discussion meeting 2012 (13-14 June 2012)

• 4th GERG academic network event (Brussels 15• 4th GERG academic network event (Brussels, 15 June 2012)

• PVT and flow assurance modeling using MULTIFLASH:• PVT and flow assurance modeling using MULTIFLASH: a 2-day training course by INFOCHEM (18-19 June

2012)2012)

• 2012 AIChE Annual Meeting (28 October – 2 November 2012)2012)

26/26

Thank you!Thank you!

Center for Energy Resources Engineering – CERECenter for Energy Resources Engineering CERE