Application of Asphaltene Deposition Tool (ADEPT) Simulator to Field Cases

Yi Chen, Anju Kurup, Walter Chapman

Houston, April 29 2013

Department of Chemical & Biomolecular Engineering, Rice University

Outline

•Introduction

1. Asphaltene deposition issue2. The ADEPT simulator and application procedure

•Field case studies

•Summary

Asphaltene issue in flow assurance

Flow Assurance Prediction – Operator’s Savings:• Intervention cost to remove solids: ~

300K/well-dry tree, $3,500K / well – wet tree.

• Loosing the well: ~ $50,000K to replace the well with a side track.

• Losses due to downtime: ~ $ 700K /day (for prod. of 7,000bbls/day)

Deposition mechanismad

vecti

on

diffusion

CDaCDarZ

C

Z

C

Pe

Cd

2agp2

21

Precipitation &

Re-dissolution kinetics:

Dimensionless parameters:

Initial & boundary condition:

Kurup, A.S. et al., Energy & Fuels. 2011, 25, 4506–4516 5

z

dd

z

pp

z

agag

z

zeqeq

ff

V

LkDa

V

LkDa

V

LkDa

D

LVPe

L

vt

L

zZ

C

CC

C

CC

C

CC

,,,

,,,0

'

0

'

0

'

0,0,0 )()0,(),0(

LzZZ Z

CCC

pff

eqfpdissdiss

eqfeqfpp

rz

CC

CwhenCCDakr

CwhenCCCDar

,

,

Mathematical model

Thermodynamic module

Depositionmodule

Composition, Liquid density,Bubble point,

GOR, AOP, SARA Asphaltene instability,

Ceq

Depositionprofile,

Thickness,Pressure drop

Kinetic parameters

Operational conditions

Ceq

P-T profile in wellbore/pipeline

6AOP--- Asphaltene onset pressureCeq --- Asphaltene equilibrium concentration

ADEPT simulator structure

Appropriate Parameters

① Characterization / Recombination

②Tuning parameters to match Pb, liquid density, AOP

③Phase behavior prediction

④ Ceq calculation with P-T profile input

MW & mass percentages of all (Pseudo-) components

Asphaltene instability

Asphaltene equilibrium concentration, Ceq

Fluid composition, GOR, SARA

Deposition module

7

Thermodynamic modeling

The kinetic constant of deposition in capillary-scale

⑤ determine kp & kag using reaction model

⑥fitting kd(cap) to reproduce capillary deposition flux

⑦scaling up of kd(cap) to k*d

The kinetic constants of precipitation and aggregation

The kinetic constant of deposition in field-scale

Asphaltene deposition flux, thickness, pressure drop

The asphaltene precipitated amountsThermodynamic module

8

⑧input Ceq , kp , kag , k*d , operational conditions

Deposition modeling

field case 1

9

10

Wellbore pressure loss is approximately 10 psi per day in the first several weeks after wellbore wash;

GOR decreases 60 ScF / STB over 4 months;

GOR increases with gas injection;

GOR sensitivity analysis is needed.

Deepwater Gulf of Mexico wellbore

90 140 190 240 2900

1000

2000

3000

4000

5000

6000

7000

8000

9000onset P @GOR=669

bubble P @GOR=669

lower onset P @GOR=669

P-T trace

onset P- exp. @GOR=669

bubble P-exp. @GOR=669

T / F

P /

Psi

11

Phase behavior prediction(wellbore)

PC-SAFT EoS (VLXE / Multiflash / PVTsim)

90 140 190 240 2900

1000

2000

3000

4000

5000

6000

7000

8000

9000onset P @GOR=1000

onset P @GOR=669

onset P @GOR=549

bubble P @GOR=1000

bubble P @GOR=669

bubble P @GOR=549

lower onset P @GOR=1000

lower onset P @GOR=669

lower onset P @GOR=549

P-T trace

onset P- exp. @GOR=669

bubble P-exp. @GOR=669

T / F

P /

Psi

12

Phase behavior prediction(wellbore)

GOR

GOR

Extract kp & kag

eqfpf

2pag

S

2pageqfp

p

CCkdt

dC

Ckdt

dC

CkCCkdt

dC

Aging Time

(hour)Precipitate amount (g)

0.166667 0.01320.333333 0.0165

0.5 0.01692 0.01674 0.0172

7.5 0.018712 0.018224 0.02

kp / s-1 2.5×10-2

kag / s-1 1.7×10-3

Batch experimental results from NMT

0 5 10 15 20 25 300.2

0.4

0.6

0.8

measured

Predicted

Time, hr

pre

cip

ita

ted

ag

gre

ga

tes

co

nc

en

tra-

tio

n, d

ime

ns

ion

les

s

14Wang, J. X., et al., Dispersion Sci. Technol. 2004, 25, 287–298.

Capillary deposition test

kd(cap) = 2.11×10-3 s-1

Fitting kd (cap) to make the peak of deposition flux curve predicted match the experimental observation.

15

Fitting kd(cap)

0.00 40.00 80.00 120.000.00

40.00

80.00

120.00

160.00

tubing lenth / inch

depo

sition

flux

, g/

m2/

day

Simulation with fitted kd (cap)

Expt

Scale up kd(cap) to k*d

kd (cap) k*d(mom) = 4.31×10-6 s-1

6

1

)(2

KTD

k

D

m

capd

m

ScFkk capdd )(*

1

2

RScF

8/77.62 etmom RD

Kurup, A.S. et al., Energy & Fuels. 2012, 26 (9), pp 5702–5710

17

Deposition flux prediction (wellbore)

0 10,000 20,000-1.0E-03

4.0E-03

Distance ( ft )

CF-C

EQ

(g/m

l)

0 10,000 20,0000.0E+00

4.0E-08

8.0E-08

1.2E-07

Depo

sition

flux

(g/

cm2/

s) I II III

Precipitated particles

Flow out

Aggregation

Deposition

Flow in

CF-CEQ = 0

Re-dissolution starts

0 10,000 20,0000.00

0.04

0.08

0.12

GOR=1000 GOR=669 GOR=549

Distance / ft

Dep

osit

thic

knes

s /

inc

h

18

14 days

Deposit thickness prediction (wellbore)

19

GORSCF/STB

Frictional pressure drop Psi /day

549 9.45669 10.10

1000 10.89≈ 10 Psi / day (Based on 14 days)

25.0

2

Re

316.0

2

f

gg

v

D

LfPfriction

Frictional pressure drop (wellbore)

field case 2

20

21

• Asphaltene problem is reported.

• The total pressure drop in the first 28 days is about 648 psi.

• The asphaltene deposition situation must be estimated.

Pipeline Gulf of Mexico

Pressure 5,284 psi

Temperature 177 ⁰F

Flow rate 13482 bbl/day

Diameter 5.137 inch4.881 inch

length 52389 ft

Field information (pipeline)

22

Phase behavior prediction (pipeline)

Kinetic parameters

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30

Aging Time, hr

Pre

cipi

tate

d am

ount

/ as

pha

l. M

ass

in 1

ml m

ixtu

re

Predicted-Set1 Measured-Set1 Predicted-Set2 Measured-Set2

Simulation with fitted kd (cap)

Expt

kp / s-1 1.32×10-3

kag / s-1 7.29×10-5

kd(cap) = 1.43×10-3 s-1

k*d(mom) 3.25×10-6 s-1

k*d(lar) 1.73×10-6 s-1

k*d(mt) 4.50×10-7 s-1

24

0 10000 20000 30000 40000 50000

-0.1

-2.77555756156289E-17

0.1

0.2

0.3

Kd-Mom

Kd-Lam

Kd-MT

Distance (ft)

Dep

osit

thic

knes

s (in

)

Boundary layer Frictional ∆P(Psi)

Momentum 700

Laminar 605

Mass transfer 519

Field data= 648 Psi (28days)

Simulation results

25

1. ADEPT simulator can successfully predict the asphaltene deposition in wellbore/pipeline.

2. Onset pressure and bubble pressure increases significantly with GOR increases, but the effects on lower onset pressure can be neglected;

3. Deposit location changes with GOR.

Summary

26

• Jeff Creek• Jianxin Wang• Andrew Yen • Sai Panuganti • Jill Buckley • Vargas Francisco

Acknowledgments