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Hadi Zainee (Petronas), Abdullah Alkindi (Petroleum Development Oman) &

Ann Muggeridge (Imperial)

16th European IOR Symposium, 11th-14th April 2011

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Outline

What is VAPEX?

Prediction of oil drainage rate

Method

Experimentally validated numerical model

Results

Conclusions

Acknowledgements

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What is VAPEX?

Vapour Extraction Improve heavy oil recovery by injecting vaporised solvent

Horizontal injector and producer

Analogue of SAGD

Oil viscosity reduced by diffusion driven mixing between oil and solvent

More energy efficient than SAGD

Better in thin reservoirs or those underlain by an aquifer

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Prediction of Oil Drainage Rate

Butler & Mokrys (1989), analytical expression for oil rate:

But actual qo >> Butler & Mokrys qo Experimental results including Dunn et al., 1989; Lim et al., 1996; Das and Butler, 1998; Boustani and Maini,

2001; Oduntan et al., 2001; Karmaker and Maini, 2003; Yazdani and Maini, 2005; Kapadia et al., 2006

Explanations include

Increased rate of mixing due to Convective dispersion

Capillary films

Counter-current flow

Higher effective drainage height

sooNSghkq 2

max

min

lnd

)1(c

cs

s

s c

Dc

N

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Prediction of Oil Drainage Rate

Alkindi (2009)

1. performed VAPEX experiments using analoguefluids

Glass bead pack representing 2D section of a reservoir

Producer at bottom & Injector mid-height Could be rotated to give lower aspect ratio

Ethanol (solvent) and glycerol (oil)

All input data measured experimentally includinglongitudinal and transverse convective dispersion

2. Performed numerical simulations (STARS) usingexperimental data as input

To predict experimental behaviour

Injection I

Production

30 cm

15 cm

Injection II

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Prediction of Oil Drainage Rate

Alkindi (2009), results confirmed underprediction of oil rate by Butler &Mokyrs model

Using convective dispersion improves prediction, but still too low

Numerical simulation predicted experimental results

need improved analytic model

Modelheight

cm

Injection ratecm3/hr

Measured oildrainage rate

cm3/hr

Butler and Mokrys drainage rate

Molecular diffusioncm3/hr

Longitudinal dispersioncm3/hr

300.6 0.48

0.320.41

1.2 0.75 0.47

15 0.6 0.41 0.23 0.28

Simulationcm3/hr

0.46

0.75

0.38

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This work

Propose an improved analytic model to predict oildrainage rate

Validate the predictions of oil rate as a function of

Density difference ()

Viscosity ratio (M)

Permeability (k)

Reservoir thickness (h)

Reservoir aspect ratio (h/L)

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Modified Butler-Mokrys model

Original model (Butler & Mokrys, 1989)

=(1-cs)(0-s)

density difference between solvent anddraining solvent-oil mixture

Modified model

=(0-s)

density difference between solvent andundiluted oil

Ns larger,

qo largerWhy?

Butler and Mokrys model assumes VE

Drainage driven by spread of solvent chamber,segregated flow cf. Dietz (1953)

soo NSghkq 2

max

min

lnd)1(

c

c

ss

s cDc

N

max

min

lnd1

c

c

ss cDN

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Methodology

Numerical simulation using experimentally validated model of Alkindi (2009)

Analogue fluid properties (ethanol=solvent, glycerol=oil)

Grid size 60 1 150

Model dimensions (x,y,z) 30 0.5 15 cm

Porosity 0.4

Permeability 43.3 D

Reference pressure 101 kPa

Reference temperature 20C

Longitudinal dispersion coefficient 8.9 10-10

m2/s

Ethanol density (kg/m3) 790

Ethanol viscosity (mPa s) 1.2

Glycerol density (kg/m3) 1261

Glycerol viscosity (mPa s) 1390

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Methodology

Use numerical model validated by comparison between experimental andsimulation results (Alkindi, 2009)

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1 1.2

PVI

Rate,

cm

3/hr

Ex p. 1.2 ml /hr (Mode l he ight 30 cm) Sim. 1.2 ml /hr (Mode l he ight 30 cm)

Ex p. 0.6 ml /hr (Mode l he ight 30 cm) Sim. 0.6 ml /hr (Mode l he ight 30 cm)

Ex p. 0.6 ml /hr (Mode l he ight 15 cm) Sim. 0.6 ml /hr (Mode l he ight 15 cm)

0.01 0.60 1.0 PVI

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Good agreement between modified analytic model and simulation

Original Butler & Mokrys model underpredicts rate

Oil drainage rate increases with solvent oil density difference

Convective dispersion is not important at high density differences

Consistent with experimental results of Alkindi et al. (2011)

0

0.005

0.01

0.015

0.02

0.025

0 0.2 0.4 0.6 0.8 1 1.2

OilRa

te(cm3/min)

PVI

= 118 kg/m3

= 235 kg/m3

= 470 kg/m3

= 940 kg/m3

= 1400 kg/m3

= 2350 kg/m3

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 10 20 30 40 50 60 70 80

OilR

ate,cm3/min

, kg/m3

Simulation Results

_so and Longitudinal Dispersion

_so and Molecular Diffusion

_sm and Longitudinal Dispersion

_sm and Molecular Diffusion

soo NSghkq 2

max

min

max

min

max

min

lnd1

lnd1

lnd)1(

c

c

sLs

c

c

ss

c

c

ss

s cKNcDNcDc

N

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Results:Viscosity ratio and permeability

Good agreement between modified analytic model and simulation

Original Butler & Mokrys model underpredicts rate

Oil drainage rate

Increases with square root of permeability

Decreases as viscosity ratio (M) increases Analytic model breaks down for M

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Results:Aspect ratio and thickness

No dependency of oil drainage rate on aspect ratio for h/L < 1

Consistent with Butler & Mokrys model

Butler & Mokrys breaks down for h/L > 1

Flow no longer gravity dominated

Oil drainage rate dependency on thickness

Best matched with an exponent of 0.28

Butler & Mokrys and modification both predict an exponent of 0.5

soo NSghkq 2

max

min

max

min

max

min

lnd1

lnd1

lnd)1(

c

c

sLs

c

c

ss

c

c

ss

s cKNcDNcDc

N

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Conclusions

Presented an improved analytic model for predicting oil drainage rateduring VAPEX

Modification of the Butler & Mokrys (1989) model

Use density difference between pure oil and solvent

Investigated the analytic model predictions using numerical simulation

Numerical model originally validated by comparison with experiments ofAlkindi (2009)

The modified Butler & Mokrys model predicts simulation results for

Viscous oils, M> 1000

Thin reservoirs, h/L < 1

Convective dispersion is not important in VAPEX at high density differences

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Discussions and Recommendations

All simulations performed using FCM liquids on the laboratory scale

Numerical model assumptions consistent with Butler & Mokrys derivation

Further work is needed to investigate more realistic conditions

Field length scales

Sub-miscible fluids

A vapourised solvent

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Acknowledgements

We thank

Petronas for funding Hadis MSc studies

PDO for funding Abdullahs PhD studies

CMG for the use of the STARS reservoir simulator