Some oil pump station design layouts may contain multiple dead-legs. During the transportation of heavy crude through the pump station, these dead-legs will be filled with this crude. When a light crude batch is introduced next into the pipeline, following the heavy crude ahead, two phenomena will occur. First, contamination between batches at the interface of the two crudes will occur due to axial turbulent diffusion along the length of the pipeline itself. Second, as the light crude flows through the pump station and passes by each dead-leg containing still heavy crude from the preceding batch, the heavy crude trapped in these dead-legs will start to drain out into the passing light crude in the main run. This causes further contamination and spreading of the mixing zone between the two batches. These two different sources of contamination are addressed in this paper with the objective of accurately quantifying the extent of the contamination, with particular emphasis on the second phenomenon which could cause appreciable contamination particularly for large size and number of these dead-legs. A computational fluid dynamics (CFD) model has been developed to quantify the drainage rate of the contaminating crude into the main stream and its impact on widening the mixed zone (contamination spread) between the two batches. Two drainage mechanisms of the heavy crude in the dead-legs into the main stream of the light crude have been identified and quantified. The initial phase is a gravity-current-induced outflow of the initially stagnant fluid in the dead-leg, followed by a subsequent draining mechanism primarily induced by turbulent mixing and diffusion at the mouth of the dead-leg penetrating slightly into the dead-leg. It was found that the second mechanism takes a much longer time to drain the first, and that the break point in time where drainage switches from a predominantly gravity current to a turbulent diffusion appears to be at a specific time normalized with respect to the length of the dead-leg and the gravity current speed. The results show a consistent trend with actual interface contamination data obtained from the Keystone 2982 km pipeline from Hardisty (Canada) to the Patoka Terminal (U.S.A.).

References

References
1.
Austin
,
J. E.
, and
Palfrey
,
J. R.
,
1964
, “
Mixing of Miscible But Dissimilar Liquids in Serial Flow in a Pipeline
,”
Proc. Inst. Mech. Eng.
,
178
(
1
), pp.
377
389
.
2.
Levenspiel
,
O.
,
1958
, “
Longitudinal Mixing of Fluids Flowing in Circular Pipes
,”
Ind. Chem. Eng.
,
50
(
3
), pp.
343
346
.
3.
Songsheng
,
D.
, and
Jianing
,
P.
,
1998
, “
Application of Convection-Diffusion Equation to the Analyses of Contamination Between Batches in Multi-Product Pipeline Transport
,”
Appl. Math. Mech.
,
19
(
8
), pp.
757
764
.
4.
Aunicky
,
Z.
,
1970
, “
The Longitudinal Mixing of Liquids Flowing Successively Pipelines
,”
Can. J. Chem. Eng.
,
48
(
1
), pp.
12
16
.
5.
Krantz
,
W. B.
, and
Wasan
,
D. T.
,
1974
, “
Axial Dispersion in the Turbulent Flow of Power-Law Fluids in Straight Tubes
,”
Ind. Eng. Chem. Fundam.
,
13
(
1
), pp.
56
61
.
6.
Botros
,
K. K.
,
1984
, “
Estimating Contamination Between Batches in Product Lines
,”
Oil Gas J.
,
82
(7), pp.
112
114
.
7.
Deng
,
S.
, and
Pu
,
J.
,
1997
, “
The Comparison Between 1-d Model and Two-Dimensional Model of the Multi-Product Pipeline
,”
Oil Gas Storage Transp.
,
16
(
1
), pp.
16
18
.
8.
Dai
,
F.
, and
Hu
,
X.
,
2009
, “
The Contamination Calculation Formula for the Southwest Multi-Product Pipeline
,”
Oil Gas Storage Transp.
,
28
(
2
), pp.
40
42
.
9.
Chen
,
Q.
,
1999
, “
Calculations on the Mixing Volume of Products Pipeline With Variable Diameter Pipes
,”
Oil Gas Storage Transp.
,
18
(
1
), pp.
7
8
.
10.
Freitas Rachid
,
F. B.
,
Araújo
,
J. H. C.
, and
Baptista
,
R. M.
,
2002
, “
Mixing Volumes in Serial Transport in Pipelines
,”
ASME J. Fluids Eng.
,
124
(
2
), pp.
528
534
.
11.
Neutrium,
2016
, “Calculating Interface Volumes for Multi-Product Pipelines,” Native Dynamics, epub, accessed Mar. 31,
2016
, https://neutrium.net/fluid_flow/calculating-interface-volumes-for-multi-product-pipelines/
12.
Sherwood
,
T. K.
,
Pigford
,
R. L.
, and
Wilke
,
C. R.
,
1975
,
Mass Transfer
,
McGraw-Hill
,
New York
, Chap. 4.
13.
Taylor
,
G. I.
,
1953
, “
Dispersion of Soluble Matter in Solvent Flowing Slowly Through a Tube
,”
Proc. R. Soc. London, Ser. A,
219
(
1137
), pp.
186
203
.
14.
Taylor
,
G. I.
,
1954
, “
The Dispersion of Matter in Turbulent Flow Through a Pipe
,”
Proc. R. Soc. London
, Ser. A,
223
(
1155
), pp.
446
468
.
15.
Colebrook
,
C. F.
, and
White
,
C. M.
,
1937
, “
Experiments With Fluid Friction in Roughened Pipes
,”
Proc. R. Soc. London, Ser. A
,
161
(
906
), pp.
367
378
.
16.
Tichacek
,
L. J.
,
Barkelew
,
C. H.
, and
Baron
,
T.
,
1957
, “
Axial Mixing in Pipes
,”
AIChE J.
,
3
(
4
), pp.
439
442
.
17.
2015
, “
ANSYS Fluent Theory Guide
,”
Release 16.1
, ANSYS Inc., Canonsburg, PA.
18.
Menter
,
F.
, and
Egorov
,
Y.
,
2010
, “
The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 1: Theory and Model Description
,”
J. Flow Turbul. Combust.
,
85
(
1
), pp.
113
138
.
19.
Wilcox
,
D. C.
,
2006
,
Turbulence Modeling for CFD
,
3rd ed.
, DCW Industries,
Sherman Oaks, CA
.
20.
Patankar
,
S. V.
,
1980
,
Numerical Heat Transfer and Fluid Flow
,
Taylor & Francis
,
Abingdon, UK
.
21.
Fox
,
R. W.
, and
McDonald
,
A. T.
,
1992
,
Introduction to Fluid Dynamics
,
4th ed.
,
Wiley
,
Hoboken, NJ
.
22.
Shin
,
J. O.
,
Balziel
,
S. B.
, and
Linden
,
P. F.
,
2004
, “
Gravity Currents Produced by Lock Exchange
,”
J. Fluid Mech.
,
521
, pp.
1
34
.
23.
Simpson
,
J. E.
,
1997
,
Gravity Currents in the Environment and the Laboratory
,
2nd ed.
,
Cambridge University Press
,
Cambridge, UK
.
24.
Konecnik
,
C.
,
2012
, “
Keystone Pipeline—Optimizing Delivered Quality
,” Crude Oil Quality Association (COQA) Meeting, Kananaskis, AB, Canada, June 19–20, accessed Mar. 31, 2016, http://www.coqa-inc.org/docs/default-source/meeting-presentations/20120619-20_Konecnik_Pipeline_Quality.pdf
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