Experimental and Numerical Assessment of Cold Restart Process of Heavy 7 WHOC12_277

8/10/2019 Experimental and Numerical Assessment of Cold Restart Process of Heavy 7 WHOC12_277

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WHOC12-277

Experimental and numerical assessment of cold restart process of

viscous oil pipeline

A. TWERDATNO; [email protected]

Z. YANGStatoil; [email protected]

E. NENNIETNO; [email protected]

H. VELTHUISTNO; [email protected]

This paper has been selected for presentation and/or publication in the proceedings for the 2012 World Heavy Oil Congress[WHOC12]. The authors of this material have been cleared by all interested companies/employers/clients to authorize dmg events(Canada) inc., the congress producer, to make this material available to the attendees of WHOC12 and other relevant industry

personnel.

AbstractOperating a flow line that transports so-called heavy

oil can be cumbersome, especially at low temperatures.

If a heavy oil flow has been stopped for awhile, the oil

inside the flow line will cool, which significantly

increases its viscosity. When re-starting the flow line,

the pressure gradient necessary to transport the cooled

oil has increased severely due to the increased

viscosity. Furthermore, it is expected that 3D

temperature effects play an important role in

determining the restart pressure gradient behaviour,

making it hard to accurately predict.

Statoil has performed detailed experiments of heavy oil

cool down and restart processes on their test rig inPorsgrunn. These experiments are simulated using two

tools 1) the multiphase software tool OLGA. 2) the

Computational Fluid Dynamics (CFD) code Fluent.

The goal of the research is to identify the performance

of each tool for the use in a cold start-up of offshore

heavy oil production pipeline.

Results demonstrate that both codes are very well

capable of predicting the cool down of the heavy oil.

The initial start-up pressure, which is fully temperature

and viscosity dependent, is also very well predicted.

The simulations also show that there is a large

dependency on temperature of the viscosity data.

Therefore, it is very important to have proper data

regarding the temperature dependency of the viscosity.

Start-up simulations are more challenging, due to the

non-uniform temperature (and viscosity) across the

pipe section. As a result, 1D codes such as OLGA fail

to accurately simulate the pressure gradient behaviour,

as demonstrated by comparisons with experiments,

limiting their range of applicability.

Such limitations should be known when performing

simulations to recommend operational procedures for

viscous oil transport in pipelines.

IntroductionAs the resources of easy oil are decreasing the oil and gas

industry is shifting its focus to the more difficult oils toproduce. Offshore heavy oil is one of the candidatestogether with tar sands and oil from the fields in the articregions. Heavy oil has received its name from the high

viscosity of the fluid, especially at low temperatures, whichmakes it difficult to transport.Due to the high viscosities, high pressure drops are expected,especially after a cool down of the pipeline. The design of the


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flow line, pumps and other equipment is complex with this

type of fluid. Currently OLGA3 is used as the industrialstandard for calculating these type of flows. OLGA uses one-

dimensional modeling concept for multi-phase flow.However, due to the strong- temperature dependence of theviscosity the 1-dimensional assumption of the flow profileinside the pipe line can be significantly violated. This paper

describes results of experiments and CFD modeling, incomparison with OLGA simulations to access the validity ofthis 1D assumption.The paper is set up as follows. First the experiments will be

detailed. Next, the OLGA simulations are discussedfollowed by the CFD simulations. Finally some discussion

and conclusions will be presented.

Experiments

Figure 1 Schematic set up of flow loop of Statoil.

Figure 1 shows the layout of the flow loop where theexperiments are performed. The pipe diameter was 2 andsurrounded by 80 mm of insulation. The flow loop is

especially designed to handle viscous oils, together withwater and or gas. In this paper only single fluid (oil)experiments are considered.At several locations, denoted by the red circles, the

temperature and pressure (drops) are measured.The shut-in of the flowline was achieved by quickly closingthe valves at both end of 2 inch flowline. At the same timethe by-passing line which links the both end of the test

flowline was open such that both feeding pumps for oil orwater can still be running. After the shut-in of the flowline,the fluid in the pipe was cooled via natural convection in air.The restart of the flowline was conducted by injecting oil or

water flow into the 2 inch pipeline after a period of naturalconvection cooling (no flow in the 2 inch pipeline) or withpre-defined temperature. During the period of shut-in in of 2-inchs test flowline, the flow simply by-passes the 2-inchs

flowline, and is routed the outlet of the test flowline. Theshut-in of the flowline is achieved by closing the valves atboth ends of 2-inchs flowline, and by opening the valve on

the line directly linking ESP and the first-stage separator.The restart process is just a reverse process of the shut-in.

Olga simulations

For the OLGA simulations version 6.1.0. is used. Thematerial properties are computed using PVTsim, with theexception of the viscosity which is recomputed using theexprimental data.

For material properties of the pipe line and insulation, typical

values are used. For the heat transfer to the surroundingstandard values in OLGA are used for air. The surrounding

air velocity is taken equal to 2 m/s. This results in a heattransfer coefficient to the surrounding of 10.33 W/(m2K).Mass flows were taken from the flow loop measurements.The insulation value of the pipes is not known a priori, but is

important to predict oil temperatures. The insulation valuewas estimated by matching simulation results withexperiments, for a typical situation. This is not arecommended practice for validating simulations with

measurements. It is recommended to determine the insulationvalue in an independent way.

Figure 2 Temperature profile of the cool down period.

Figure 3 Pressure drops over several sections of the flow

loop after restart calculated with OLGA compared with

the measurements.

Figure 2 shows the temperature behavior during cool down.As can be seen OLGA predicts it very well. The differences

in measured values can be explained by local insulationdifferences at the flow loop and the ondulation can be relatedto daily variations of the ambient temperature.Figure 3 and Figure 4, show the pressure drop and

temperatures respectively during restart. Both OLGA resultsand measured values are plotted. The initial pressure drop iswell predicted by OLGA. However prediction of the transientbehaviour is less good. Prediction of the hot fluid arrival time

by OLGA is significantly delayed compared to themeasurements. Unexpectedly the temperature evolution isquite well predicted.. The OLGA predicted temperaturescorrespond of course a uniform section-wise temperature.


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radial temperature conductivity. The pressure drop, shown in

Figure 10, is also less well predicted, with a pressure frontwhich is significantly delayed. However, the sharp pressure

gradient at the pressure front is much better resolved(circledin the figure).

Figure 7 Temperature profile at a measurement location

at several times computed with CFD.

Figure 8 Velocity profile at a measurement location at

several times computed with CFD.

Figure 9 Temperatures at several locations of the flow

loop after restart calculated with CFD, using the higher

value for ,,,, compared with the measurements.

Figure 10 Pressure drops over several sections of the flow

loop after restart calculated with CFD using the k-w

turbulence model compared with the measurements.

Figure 11 Temperatures at several locations of the flow

loop after restart calculated with CFD using the k-w

turbulence model compared with the measurements.

Comparison with OLGA

Now we will compare some CFD results with OLGAsimulations and the measurements. In Figure 12 the pressure

drop at one of the measurement locations is plotted. We seethat CFD gives an improvement to the OLGA results,however some differences with the measurements remain.For the temperature, which is plotted in Figure 13 we see that

OLGA predicts the increase in temperature too fast and CFDtooslow. As already mentioned after an increase of the heatconductivity, the simulated results match nicely.

Figure 12 Comparison of the simulations of OLGA, CFD

and experiments with respect to the pressure drop.


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Figure 13 Comparison of the simulations of OLGA, CFD

and experiments with respect to the temperature.

Discussion & Conclusion

The prediction of the pressure drop at restart and the period

after restart, boils down to the correct prediction of fluidtemperature in the flow loop in the various periods, given aknown initial condition and known boundary conditions.

In general OLGA is very well capable of predicting the cooldown behaviour of the heavy oil in the flow loop. For thetrends in temperature and pressure drop after startup weconclude that OLGA has some difficulties to predict thecorrect values. Quantifying OLGAs uncertainties cannot be

easily evaluated since this is dependent on the specificproperties of the oil and of the flowing conditions.

For the CFD results and looking at the experiments we see

that the initial and transient pressure drop is well predicted.The measured temperatures during startup were more

difficult. An increase of the heat conductivity () with a

factor of 10(!) gives the best of the data. Several additionalsimulations were performed to examine this. Interpreting

these we state that the reason(s) for increased (effective) heatconductivity could be:

Turbulence

Errors in heat conductivity taken from PVTsim

3D effects, such as bends or locally degradedinsulation

NOMENCLATURERe = Reynolds number

= heat conductivity

CFD = Computational Fluid Dynamics

REFERENCES

[1] Wesseling, P., (2000) Principles of Computational FluidDynamics, Springer-Verlag New York, Inc. Secaucus, NJ,USA

[2] Walters, K. W., Cokljat, D., (2008), "A Three-Equation

Eddy-Viscosity Model Reynolds-Averaged Navier-StokesSimulation of Transitional Flow", J. of Fluids Engineering

130-121401.

[3] OLGA, www.sptgroup.com/Products/olga/

[4] ANSYS Fluent, www.ansys.com

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Experimental and Numerical Assessment of Cold Restart Process of Heavy 7 WHOC12_277