OLGA2000_TransientSimulation

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Faculty of Engineering Science and Technology

Department of Petroleum Engineering and Applied Geophysics

Diploma Thesis

Field Data Analysis using the Multiphase

Simulation Tool OLGA2000

Karl Ludvig Heskestad

Stavanger/Trondheim, June 2005


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NTNUNorges teknisk-naturvitenskapelige universitet Fakultet for ingenirvitenskap og teknologi Faculty of Engineering and Technology

Studieprogram i Geofag og petroleumsteknologi

Study Programme in Earth Sciences and Petroleum Engineering

Institutt for petroleumsteknologi og anvendt geofysikk


HOVEDOPPGAVE/DIPLOMA THESIS

Kandidatens navn/ The candidates name: Karl Ludvig Heskestad

Oppgavens tittel, norsk/Title of Thesis, Norwegian: Felt Data Analyse ved bruk av FlerfaseSimuleringsverktyet OLGA2000

Oppgavens tittel, engelsk/Title of Thesis, English: Field Data Analysis using the MultiphaseSimulation Tool OLGA2000

Utfyllende tekst/Extended text:

1. Gather operational data for selected pipelines

2. Verify and update OLGA models with respect to pressure and temperature

3.Analyze and discuss results of comparison

Studieretning/Area of specialization: Petroleumsteknologi/ Petroleum technologyFagomrde/Combination of subjects: Petroleumsproduksjon / Petroleum productionTidsrom/Time interval: Januar Juni 2005 / January June 2005


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NTNUNorges teknisk-naturvitenskapelige universitet Fakultet for ingenirvitenskap og teknologi Faculty of Engineering and Technology

Studieprogram i Geofag og petroleumsteknologi

Study Programme in Earth Sciences and Petroleum Engineering

Institutt for petroleumsteknologi og anvendt geofysikk


Declaration

I, Karl Ludvig Heskestad, hereby declare that this Diploma thesis for the degree of

Master of Sciencein Petroleum Engineeringis completed in accordance with all the

rules and regulations of the Norwegian University of Science and Technology.

Karl Ludvig Heskestad, Trondheim 20th

of June 2005


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Field Data Analysis using the Multiphase Simulation Tool OLGA2000

Norwegian University of Science and Technologyiv

Abstract

This thesis presents a comprehensive analysis of field data using OLGA2000

(OLGA). The field data was gathered from two different fields in the North Sea that

produce gas and condensate. The objective with this study was to verify and evaluate

the obtained field data by basic calculations to make sure it was applicable for tuning

and further to test and tune the OLGA model with the field data. The multiphase

pipelines investigated stand out from each other by one being an insulated and buried

pipeline transporting gas and condensate from a subsea development to a platform,

and the other being an uninsulated pipeline transporting rich gas from platform to

shore. In the pipeline where the pressure drop is mainly determined by friction a close

match between OLGA and field data has been obtained by changing the roughness of

the pipeline wall. OLGA has shown its vulnerability in cases where the pressure loss

is dominated by gravity forces. The simulation tool has been partly successful when

simulating an unsteady state incident. As an overall conclusion from this work OLGA

appears as a convincing simulation tool. However, it stands out that the tool needs

significant improvement for calculations where the pressure drop is dominated by

gravity forces.


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Norwegian University of Science and Technologyv

Preface

This thesis has been carried out at the Department of Multiphase Systems and Flow

Assurance, Statoil Stavanger. Professor Jn Steinar Gudmundsson has been my

teaching supervisor. The thesis has been professionally demanding and the

connection with large and active surroundings has given me technical insight and a

few extra challenges. For this there are a few people I would like to thank.

First of all I want to thank professor Gudumundsson who by his teaching has

supplied me with the technical knowledge which has been the foundation when

executing this work. I also appreciate his effort in trying to teach me the ability to

write in a technical and professional manner.

I want to express my appreciation to the Department in Statoil. Anne Synnve

Hebnes the leader of the department (now in a leave of absence) has always been

cooperative and helpful both technical and practical. I would also like to thank the

discipline leader Torbjrg Klara Fossum, who by her expertise and well meaning

attitude has been invaluable.

In general I would like to thank NTNU and the Department of Petroleum Engineering

and Applied Geophysics for giving me an education within an area of expertise that is

both exiting and innovative.


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Norwegian University of Science and Technologyvi

Table of Contents

Abstract........................................................................................................................iv

Preface........................................................................................................................... v

Table of Contents.........................................................................................................vi

Table list......................................................................................................................vii

Figure list ....................................................................................................................viiNomenclature............................................................................................................... ix

1 Introduction........................................................................................................... 1

2 Literature Review.................................................................................................. 2

2.1 Experience from previous work.................................................................... 23 Multiphase simulation tool OLGA ....................................................................... 4

3.1 The two-fluid model ..................................................................................... 4

3.2 Flow regimes................................................................................................. 7

3.3 Applications .................................................................................................. 94 Field A ................................................................................................................ 10

4.1 General ........................................................................................................ 10

4.2 System overview......................................................................................... 114.3 Design Basis................................................................................................ 11

4.4 Field data analysis....................................................................................... 13

4.4.1 Steady state data.................................................................................. 134.4.2 Unsteady state data ............................................................................. 14

4.5 Simulations and results ............................................................................... 16

4.5.1 Steady state simulations...................................................................... 16

4.5.2 Unsteady state simulations.................................................................. 184.6 Discussion ................................................................................................... 19

4.7 Conclusion .................................................................................................. 225 Field B................................................................................................................. 23

5.1 General ........................................................................................................ 23

5.2 System overview......................................................................................... 235.3 Design Basis................................................................................................ 23

5.4 Field Data Analysis..................................................................................... 24

5.5 Simulations and Results.............................................................................. 25

5.6 Discussion ................................................................................................... 275.7 Conclusion .................................................................................................. 29

6 References........................................................................................................... 307 Tables.................................................................................................................. 32

8 Figures................................................................................................................. 38A. Calculations............................................................................................................I

a. Field B................................................................................................................ I


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Norwegian University of Science and Technologyvii

Table list

Table 1 Expected Production ...................................................................................... 32Table 2 Fluid composition 1 for Field A .................................................................... 32Table 3 Fluid composition 2 for Field A .................................................................... 33

Table 4 Detailed wall construction Field As pipeline ............................................... 33

Table 5 Material properties used in the OLGA simulations at Field A...................... 34

Table 6 Selected steady state data............................................................................... 34Table 7 Steady state data used in the extensive testing of the models........................ 34

Table 8 Evaluation of base case.................................................................................. 35Table 9 Gas production from Field B ......................................................................... 35

Table 10 Material properties used in the pipeline on Field B..................................... 36

Table 11 Gas composition for Field B,....................................................................... 36

Table 12 Results from the tuning based on OLGA simulations. ................................ 37

Figure listFigure 1 Schematic drawing of horizontal flow regimes............................................ 38

Figure 2 GUI OLGA .................................................................................................. 38

Figure 3 The phase Envelope for Field A................................................................... 39Figure 4 System Overview for Field A....................................................................... 40

Figure 5 Figure profile for one of the wells at Field A .............................................. 41

Figure 6 Overview for one of the wells at Field A. .................................................... 42

Figure 7 The pipeline profile for the pipe at Field A.................................................. 43

Figure 8 Field As buried pipeline .............................................................................. 43Figure 9 Hydrate equilibrium curve for Field A......................................................... 44

Figure 10 Production profile for Field A .................................................................... 45

Figure 11 Pressure losses on Field A.......................................................................... 46

Figure 12 Temperature drop on Field A ..................................................................... 47Figure 13 Calculated pressure drops........................................................................... 48

Figure 14 Calculated temperature function................................................................. 49

Figure 15 Shutdown sequence for Field A ................................................................. 50Figure 16 Injection of MEG at Field A....................................................................... 51

Figure 17 Hydrate area................................................................................................ 52

Figure 18 Topside temperature during restart............................................................. 53

Figure 19 Flow regimes during stable production at Field A ..................................... 54Figure 20 Pressure drop versus massflow 0.001 mm ................................................. 55

Figure 21 Pressure drop versus massflow 0.01 mm ................................................... 56Figure 22 Pressure drop as a function of time ............................................................ 57

Figure 23 Temperature drop versus massflow............................................................ 58

Figure 24 Deviation in the temperature drop.............................................................. 59

Figure 25 Restart Field A............................................................................................ 60Figure 26 Restart Field A after 21 hours .................................................................... 61

Figure 27 Restart Field A with modified wall model ................................................. 62

Figure 28 Restart Field A with modified soil properties ............................................ 63Figure 29 Restart Field A with modified soil properties 2 ......................................... 64


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Norwegian University of Science and Technologyviii

Figure 30 Restart Field A with modified soil properties 3 ......................................... 65

Figure 31 How to create the soil grid in OLGA 2000 ................................................ 66Figure 32 Restart Field A with the soil model............................................................ 67

Figure 33 Restart Field A with the soil model 2......................................................... 68

Figure 34 The liquid surge.......................................................................................... 69Figure 35 Restart Field A Comparison of the cases ................................................... 70

Figure 36 Restart Field A Comparison of the cases ................................................... 71

Figure 37 Phase envelope for the Gas on Field B....................................................... 72Figure 38 Field Bs pipeline profile............................................................................ 73

Figure 39 System overview for the pipeline on the platform,. ...................................73

Figure 40 Overall heat transfer coefficient for Field B............................................... 74Figure 41 Production profile for Field B .................................................................... 75

Figure 42 Total liquid and pressure drop.................................................................... 76

Figure 43 Flow regime and hold-up for Field Bs pipeline. ....................................... 77

Figure 44 Pressure and flow regime for Field B......................................................... 78


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Norwegian University of Science and Technologyix

Nomenclature

Latin letters

A areaCp specific heat capacity

d diameter

E internal energy per unit of mass

f friction factor

G mass sourceH enthalpy

h height

k surface roughness

L lengthNRe Reynolds number

p pressure

Re Reynolds numberS wetted perimeter

Sm3

Standard cubic meter

T temperatureU overall heat transfer coefficient

u velocity

V volume

v velocity

Greek letters

inclination from vertical

change

pb frictional pressure drop across the slug bubble

pS frictional pressure drop in the liquid slug

surface roughness

friction factor

densityg mass transfer rate between the phases

e entrainment rate

d deposition rate


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Norwegian University of Science and Technologyx

Subscripts and superscripts

ac acceleration

D droplets

g gasi interphase

L liquid

Lb slug bubbleLS liquid slug

w water

Abbreviations

DHP down hole pressure gaugeGUI graphical user interphase

GOR gas oil ratio

HET hydrate equilibrium curve

HPHT high pressure high temperature

LNG liquefied natural gasLPG liquefied petroleums gas

MEG methyl ethylene glycol

MSL mean sea levelNGL natural gas liquids

PVT pressure volume temperature

SCSSV surface controlled sub sea safety valve


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Norwegian University of Science and Technology1

1 Introduction

More and more fields are developed with subsea solutions and this often results in

multiphase transport in long pipelines. OLGA is widely used in the international oil

business as the premium multiphase simulation tool. Since the companies become more

dependent on tools such as OLGA, continuous testing and evaluation of these tools are

necessary. This thesis has evaluated field data from two different fields, both fields

produce gas and condensate.

Chapter 2 in the thesis is a brief literature review and a description of previous work that

is relevant for this thesis has been included.

In chapter 3 the theory behind OLGA is presented. All the basic equations are included

and the different flow regimes are discussed. Typical systems that OLGA is applicable on

are also mentioned.

The first field is presented in chapter 4. A general overview of the field appears. The

obtained data is presented and evaluated. Attempts to tune the model against the

mentioned data are performed. A shut-in/restart incident is also simulated. At the end of

the chapter there is an extensive discussion followed by the conclusion.

Chapter 5 is built up as the previous one with a general introduction of the field. The field

data obtained for this field is limited but the evaluation of it has been crucial for the

simulations and tuning performed later on. The chapter is brought to an close during the

discussion and finalized by the conclusion.

The following chapters show all the references, tables and figures which are referred to in

the text.


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2 Literature Review

In the 70s Oil and gas companies used to apply empirical correlated multiphase flow

simulation tools to design new pipelines. The empirical correlations were also used to

determine the future behaviour of existing pipelines with changing production rates. The

software performed well as long as the pipelines were designed for or operated in

conditions that the empirical correlations were derived from. Later more reliable

mechanistic flow simulators emerged: these were based on equations of mass momentum

or energy of oil and gas phases. They were used to simulate steady state flow for any

conditions. However this was not sufficient enough to design confidently new pipelines

or to anticipate unsteady behaviours of existing pipelines. The oil industrys solution to

this problem was the introduction of transient multiphase flow simulators. These

simulators can simulate unsteady flows of oil, gas and water. The next step is likely to be

a four phase simulator, where the fourth phase could be hydrates. Before the introduction

of such a simulator there is great demand for evaluating of already existing multiphase

flow simulation tools1. One of these tools is OLGA.

2.1 Experience from previous work

Irfansyah et al, at TOTAL E&P Indonesia proposed that OLGA predicted satisfactory

results on steady state simulations. During transient simulations the conclusions were that

OLGA could reproduce the variations of water flow rate at the pipeline outlet. The inlet

pressure was however not calculated with the same accuracy. The authors think that this

could be because the amount of gas trapped in the high points of the pipeline is not very

well determined. OLGA and TACITE, another multiphase simulation tool, were tested

towards field data obtained from a 41 kilometres long 12 inch Indonesian pipeline. The

field data includes steady state data from stable production and transient data from slug

catchers. The steady state data are quite interesting because it behaves like a typical gas

pipeline with superficial gas velocity at 5 m/s and superficial liquid velocity of 0.07 m/s.

From steady state simulations the deviation in OLGA from field data was 7.4 % and 15.7


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% for TACITE, with regards to the pressure drop. The pressure drop was however as low

as 4.2 bars. The transient data are taken from the pipeline when operating slug catchers1.

Eidsmoen and Roberts at Scandpower Petroleum Technology performed work on a 77

kilometres long 20 inch pipeline. With an inlet temperature of 50 C, slug catcher

pressure of 50 bars and production rates ranging from 1.4 to 8.5 MSm3/d. The authors

looked at several aspects connected to simulations using OLGA. They concluded that due

to very slow water build-up rates some gas condensate pipeline are rarely at steady state.

To achieve steady state in the simulations the OLGA models has to be run for a long

time. Through dynamic simulation examples it was shown that special attention has to bepaid to the boundary conditions when performing transient simulations. Simplifications

will usually result in discrepancies from what will be observed in reality2.


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the gas phase:

( ) ( )21 1

2

1cos

4 2 4

g g g g g g g g g g g

g ii g r r g g g a D

p

V v V AV v v vt z A z

S Sv v V g v F

A A

=

+ + +

Equation 3.4

for liquid droplets:

( ) ( )21

cos

D L D D D L D

DD L g a e i d D D

L D

pV v V AV v

t z A z

VV g v v v F

V V

= +

+ ++

Equation 3.5

Equation 3.4 and Equation 3.5 can be combined to cancel out the gas/droplet drag, FD:

( ) ( )

( )

( )

2 21 1

2 4

1cos

2 4

g g g D L D g D

g

g g g D L D g g g g

ii g r r g g D L

Dg a e i d D

D L

pV v V v V V

t z

SAV v AV v v v

A z A

Sv v V V g

A

Vv v v

V V

+ = +

+

+ +

+ + +

Equation 3.6

for the liquid at the wall:

( ) ( )

( )

21

1 1cos

2 4 2 4

sin

L L L L L L L

iLL L L L i g r r L L

L Lg a e i d d L L g

L D

pV v V AV v

t z A z

SSv v v v V g

A A

V Vv v v V d g

V V z

=

+ +

+

+

Equation 3.7

From Equation 3.4 through Equation 3.7, p is the pressure, is the pipe inclination fromthe vertical, the Sfis the wetted perimeters of the given phase f. The internal source Gf is

assumed to enter a 90 angle to the pipe wall thus carrying no net momentum. When >

0 the evaporation from the liquid film gives va = vL, and evaporation from the liquid

droplets gives va = vD. For < 0 the condensation gives va = vg. The conservation

equations can be applied to all possible flow regimes. The following slip equation defines

the relative velocity, vr:


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( )g D L r v R v v= + Equation 3.8

The RD is a distribution slip ratio caused by an uneven distribution of phases and

velocities across the pipe cross section. A similar definition for the droplet velocity is

defined by v0D, which is the fall velocity of the droplets.

0D g Dv v v= Equation 3.9

OLGA reformulates the problem before discretisizing the differential equations to obtain

a pressure equation. The conservation of mass equations (Equation 3.1-Equation 3.3) may

be expanded with regards to pressure, temperature and composition. This assumes that

the densities are given as:

, , )f Sp T R = ( Equation 3.10

Rs is the gas mass fraction. After inserting the conservation of mass equations and

applying Equation 3.11:

1g L DV V V+ + = Equation 3.11

Then a single equation for the pressure and phase fluxes appears:

( ) ( )

( )

,,

1

1 1

1 1 1

1 1 1

SS

g g g L

g L T RT R

g g g L L L

g L

D L D

g

L g L

g L D

g L L

V V p

p p t

AV v AV v

A z A z

AV v

A z

G G G

+ =

+

+ + +

Equation 3.12


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The energy conservation of the mixture is expressed by Equation 3.13:

2 2

2 2

2 2

1 1[

2 2

1 1] [

2 2

1 1]

2 2

g g g L L L

D D D g g g g

L L L L D D D D

S

m E v gh m E v ght

m E v gh m v H v ghz

m v H v gh m v H v gh

H U

+ + + + +

+ + + = + +

+ + + + + +

+ +

Equation 3.13

Where mf is a product of Vff, E is the internal energy per unit mass, the elevation is

given with h, HSis the enthalpy from the mass sources and U is the heat transfer from the

pipe walls3.

OLGA can simulate pipelines with any kind of wall constructions with several different

layers, heat capacities and conductivities which may change along its profile. The

program computes the heat transfer coefficient from the flowing fluid to the internal pipe

wall; the outside heat transfer coefficient is user specified. Special phenomena are

included, for instance the Joule-Thompson effect, given that the PVT package that

generates the fluid properties is capable of describing such phenomena

3

.

All fluid properties used in OLGA are calculated and given as tables in pressure and

temperature. The actual values at a given point in time and space are found by

interpolating in these tables. The tables are generated before OLGA is run. It is assumed

that the total mixture composition is constant in time along the pipeline, while the gas and

liquid compositions change with pressure and temperature as a result of interphasial mass

transfer. The reality is that the difference between oil and gas may change the total

composition of the mixture3.

3.2 Flow regimes

In OLGA the friction factor and wetted perimeters depend on the flow regime. There are

two basic flow regimes in this flow simulator. Distributed that contains bubble and slug

flow and separated, which contains stratified and annular mist flow. Due to the fact that


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OLGA is a unified model, separate user specified correlations are not needed. Thus a

dynamic flow regime prediction is required, yielding the correct flow regime as a

function of average flow parameters3.

Separated flow is characterized by the two phases moving separately4, Figure 1. The

phase distributions across the respective phase areas are assumed constant. The

distributions slip ratio, RD then becomes 1.0. The wetted perimeters of the liquid film

define the transition between stratified and annular flow. When this perimeter becomes

equal to the film inner circumference this results in annular flow. Stratified flow may be

either wavy or smooth and an expression for the wave height, hw, is as follows:

( )

( )( )

2

2

1{

2 2( ) sin

4}

2( ) sin sin

g g L

w

L g

g g L

L g L g

v vh

g

v v

g g

=

+

Equation 3.14

The applied friction factors for gas and liquid are those of either turbulent or laminar

flow. In practice the largest one is chosen. The friction coefficient, t, for turbulent flow

is given by:

4 6

3

Re

2 10 100.0055 1t

hd N

= + +

Equation 3.15

For laminar flow the friction coefficient, l, is expressed as:

Re

64l

N = Equation 3.16

Where is the absolute pipe roughness and dh is the hydraulic diameter. In annular

vertical flow the interfacial friction factor, i,is given by Wallis equation:

( )0.02 1 75 1i gV = + Equation 3.17

For inclined annular mist flow Equation 3.18 is applied (where the K is an empirically

determined constant):

( )0.02 1i LKV = + Equation 3.18


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In stratified smooth flow, Figure 1, the standard friction factors with zero pipe roughness

is applied. The interphasial friction factor for wavy flow is determined from Equation

3.18 and Equation 3.19:

wi

hi

hd

= Equation 3.19

In distributed flow the total pressure drop is given by:

( )1

S b ac

zp p p

p L

= + +

Equation 3.20

is the frictional pressure drop in the liquid slug and pbdenotes the frictional pressure

drop across the slug bubble. pac is the pressure drop required to accelerate the liquidunder the slug bubble with velocity vLbup to the liquid velocity in the slug, vLS. L is the

total length of the slug and bubble. For slug flow the wall friction terms will be more

complicated since the liquid friction depend on vg and the gas friction on the vl, see

Malnes5for full description

3.

3.3 Applications

An example of the graphical user interface (GUI) in OLGA is shown in Figure 2. Typical

systems that OLGA may be applied to are6:

Oil and natural gas flowlines or transportation lines

Wet gas or condensate pipelines

Well stream from a reservoir

LNG/ LPG/ NGL pipelines

Dense phase pipelines

Network of merging and diverging pipelines Artificial lift and other mass source injections

Pipelines with process equipment

Single phase gas or liquid

Small diameter pipelines with various fluids

Laboratory experiments

Topside process systems


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4 Field A

In this section Field A will be generally described, field data will be analyzed and

evaluated. The OLGA model will be tested and an effort to improve it will also be

initiated.

4.1 General

Field A is a saturated gas field located in the North Sea. Condensate forms at pressure

reduction meaning during production. The field started production in the 3

rd

quarter of2004 and is expected to recover 13 billions Sm

3 of gas and 32 millions barrels of

condensate7.

Formation X is the main reservoir which contains gas and minor amounts of proven oil.

The total depth of the reservoir varies from 3400 to 3700 meters below mean sea level

(MSL). The thickness of Formation X varies between a maximum of about 70 meters to a

minimum of 40 meters. The sand quality is quite good and has a porosity of

approximately 18% and a permeability of 400 to 500 milliDarcy (mD). The initial

reservoir pressure is 445 bars at 3640 meters, and the reservoir temperature is 120

degrees Celsius (C). The dew point is at 420 bars and the gas condensate ratio (GCR) is

1984 Sm3/Sm

3. Typical pressures at wellhead upstream choke are 270-290 bars, Figure 3

shows the phase envelope for the gas and typical inlet/outlet pressures and temperatures

are plotted8.

The field will be producing at max capacity the first two years, until it start decreasing.

Table 1 gives the: production profile, reservoir, wellhead, arrival and required pressures

and water production for Field A. Wellhead and arrival temperatures are also included.

The water production is given as a range between a minimum and a maximum value9.


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4.2 System overview

The field is a subsea development with a tie-back to a gas-process platform7, Figure 4

gives an overview.

The subsea development consists of four wells (where the production tubing has an inner

diameter of 151 millimetres8) tied together to a template. In Figure 5 the profile of one of

the wells is shown. Each well has a downhole pressure gauge (DHPG), a surface

controlled subsea safety valve (SCSSV), pressure and temperature measurement up- and

downstream the wellhead and up- and downstream the production choke. A wet gas

meter is placed downstream the wellhead but upstream the production choke see Figure

6. The four wells merge into a subsea template which is located 111 meters below MSL9.

An 18 kilometres long pipeline, Figure 7 shows its profile, connects the template to the

process platform. The production is brought to the platform by a 12 riser. On the

platform there is pressure and temperature measurements up- and down stream the

productions choke. As shown in Figure 4, a wet gas meter is placed upstream the

production choke

9

. The wet gas meters subsea shows ~5% difference from the topsidemeter, the topside meter is considered more accurate than those located subsea

10.

Wet gas meters are delivered by Roxar. They measure two flows; hydrocarbon and water.

The split between condensate and gas are calculated from PVT properties10

.

The pipeline is buried, covered by sand on top and placed approximately 0.5 meters

below the sea bed, see Figure 8. There is also a service umbilical going from the template

to a production platform, located close to the process platform9.

4.3 Design Basis

The simulation tool used in this study is OLGA 2000 v4.13 (OLGA). Further PVTSim

v11/14 (PVTSim) has been used to generate fluid properties tables which are input to the

OLGA simulations.


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The ambient temperature changes from month to month in the North Sea. The warmest

months are from November to January, and correct temperatures have been applied in the

simulations13.

4.4 Field data analysis

The data obtained for use on Field A have been closely evaluated. The data has been

gathered from January to March this year, and includes steady and unsteady state data.

4.4.1 Steady state data

A production profile from 15th

to 31stof January is shown in Figure 10. In the figure the

steady state data that have been used are highlighted in yellow. The data that was selected

as possible data for testing of the model are given in Table 6. The data are also shown

graphically in Figure 11 and Figure 12, which shows the pressure loss versus mass flow

and the temperature drop versus massflow respectively.

To evaluate the pressure loss during stable production, simplified hand calculations wereperformed. The pressure drop in the pipeline is mostly frictional and the Darcy-Weisbach

equation has been applied:

2

2f

f Lp u

d

=

Equation 4.1

Where pfdenotes the frictional pressure drop, f (-) is the friction factor, L (m) the length

of the pipeline, d (m) is the diameter of the pipe, is the density of the fluid and finally u

is the velocity of the fluid. The friction factor has been calculated using Haalands

equation:

21.11

1

6.90.6log

Re 3.75

n nf

k

d

= +

Equation 4.2


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Where Re (-) denotes the Reynolds number, k is the surface roughness of the pipe wall

and n is constant that either has the value 1 for oil/liquid or 3 for gas. Since the flow in

the pipeline is dominated by gas the calculations have been done with an average in

vapour density and viscosity. The fluid properties have been calculated with PVTSim. In

Figure 13 the results from the calculations are plotted versus massflow and compared

with the field data. The calculated pressure drops comes close to field data, but have a

different slope. The deviation in pressure drop from field measurements compared to

calculated pressure drop increase as the production rate is reduced. This can be explained

by the simplifications in fluid properties which is less valid as more liquid will drop out

at low production rates.

In Figure 12 at least one data point from the field data deviates and stands out from what

is expected, marked in the graph. This gives reason to evaluate the measured

temperatures using the following equation:

( )2 1 exps sp

dULT T T T

C m

= +

Equation 4.3

Where Ts(C) is the surrounding temperature, T1(C) is the inlet temperature, T2(C) is

the outlet temperature, U (W/(m2C)) is the overall heat transfer coefficient, m (kg/s) is

the massflow and Cp (J/(molC)) is the specific heat capacity of the fluid. Solving this

equation with regards to the temperatures gives Figure 14. The slope of the graph is equal

to1/mwhen assuming that the other variables are constant. In Figure 14 the same data

point as in Figure 12 has been marked. This point stands out in both graphs and appears

to be a measurement error thus being removed from the data set. The new data which will

be used to evaluate the multiphase flow program is given in Table 7.

4.4.2 Unsteady state data

The 10th

of March this year Field A had a shutdown, Figure 15 shows the shutdown

sequence. Prior to the shut-in, injection of MEG into the wellstream was started.

However, the circumstances concerning the shutdown did not allow for full inhibition of

the pipeline. Only a small part of the pipeline was inhibited when the production was


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fully stopped, Figure 16 shows the MEG content in the water phase along the pipeline

profile according to estimations using OLGA. The field was shutdown for 65 hours thus

staying in the hydrate region for a long time. According to OLGA simulations, parts of

the pipeline will enter the hydrate region after 21 hours, Figure 17. If the hydrate control

procedures were to be followed in this shut-in case, the pipeline should have been

depressurized. However, the risk for hydrate plugging was considered very low for the

pipeline. This risk assessment was based on factors like gas oil ratio (GOR), water

production, pipeline topography and pipeline diameter, all indicating low probability for

hydrate plugging. Further, it was decided to quickly pressurize the pipeline during restart,

so that the compression heat developed during the pressurization would melt possiblehydrate seeds. This quick pressurization of the pipeline during restart will even more

reduce the risk for hydrate plugging. The pressurization was carried out by keeping the

topside choke closed and quickly opening the well chokes.

The data obtained for this incident are somewhat questionable, especially the massflow

metering. It states that there is a ~2 % opening on the choke when other measurements

make it clear that it the choke is fully closed. The data set that comes from the

temperature measurement topside is regarded as accurate and has been used extensively

in the simulations14

. Figure 18 shows the field data from the restart, the graph shows

topside temperature versus time. In the graph it is evident that after approximately 78

hours (4700 minutes) there is an increase in the temperature. The temperature increase

can be explained by warm liquid arriving at the platform, due to the fact that liquid cools

down slower than gas. During the shutdown a relatively large liquid accumulation can be

expected at the beginning of the pipeline (wellhead), see pipeline profile Figure 7. The

temperature increase at time 78 hours can be explained by this liquid surge arriving at the

platform. If there is a liquid plug arriving at the platform at that time the velocity of the

plug should be approximately 1.5 m/s (based on simple calculations, distance = velocity

time). Calculations performed by OLGA shows that the liquid velocity at the platform at

78 hours is 1.7 m/s, which is quite close. This indicates that there might be a liquid surge

moving through the system.


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4.5 Simulations and results

OLGA has been applied to see if the simulation tool can achieve a closer match to field

data than calculations performed in 4.4. The OLGA model has also been tuned against

steady state field data and the tuned model has been applied to simulate the unsteady state

incident.

4.5.1 Steady state simulations

Table 7 shows the data used for the tuning for the model. The production rates are

ranging from 94 kg/s to 135 kg/s.

The model was first tested with respect to the pressure drop in the pipeline. In order to

eliminate the uncertainties connected to the pressure drop in the subsea choke and the

topside chokei, the pressure drop in between the chokes was used for testing. The

pressure drop ranges from 15 to 22 bars for the selected production rates. The base case

model (described in 4.3) gives 7 15 % deviation in the pressure drop, see Table 8.

In order to improve the model, the pipelines geometry was first investigated to verify

that the deviation in pressure drop was not caused by any simplifications of the pipeline.

The pipeline geometry was in accordance with as laid data15

. The pipeline topography

is quite flat and gas dominates the flow in the pipeline, therefore the pressure drop is

mostly frictional. According to simulations the flow in the pipe is stratified, see Figure

19, and from Equation 3.15 we see that the friction coefficient is dependent on the

roughness. Thus the roughness of the pipeline wall is a key parameter when tuning the

model.

A parameter study in OLGA was carried out to determine the value of the roughness

which gave best match to field data. At the highest rates (135 kg/s) a roughness as low as

0.001 millimetres was required to match the model against field data, Figure 20. This low

roughness did not match the operating data for rates in the range 105 115 kg/s (which

iThe CV curves for the chokes were not available, i.e. data for pressure drop as a function of opening of the

choke were not available.


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are the normal production range for the pipeline). A roughness of 0.01 millimetres gave

good match with field data for the production rates between 105 and 115 kg/s see Figure

21 and Figure 22.

In OLGA a command called Steady State pre-processor exists. This is an option that is

mainly intended as a generator of initial values for dynamical simulations6. This option

has been tested to see if it can be used instead of running the model until it reaches steady

state. This option calculates the pressure drop quite good when the production rates are

low, but the error increases as the production rate increase, reference Figure 20 and

Figure 21.

When Field As OLGA model had been tuned against pressure drop, the temperature

drop prediction was also investigated (for same field data as above). The temperature

drop in the pipeline is in the range 15 22 C. The pipelines base case model was

constructed with a 0.5 meter concentric sand layer as part of the wall, 0.5 meters being

the actual burial depth. This sand layer is a simplification for the soil around the pipe.

This way of constructing a wall will be referred to as the wall model. However this

base case model gave a deviation, from the field data, up to 13 %. When applying the

sand layers in the pipe wall, the sand layer should be doubled of what the buried depth,

chapter 2.3.66. The model was therefore modified by increasing the sand layer to 1 meter

thickness. Figure 23 and Figure 24 shows that the modification of the sand layer gives

good agreement of temperature drop when comparing the simulations with the field data.

The deviation in temperature drop is maximum 8.6 %. Based on this, a sand layer

thickness of 1 m is used as a starting point for the tuning carried out in next section

(section 4.5.2). In accordance with the theorem in the OLGA user manual the specific

heat capacity for the sand was reduced from 1100 to 955 J/(kgK) .The Cpdoes not have

any affect on steady state simulations. Because the heat transfer at steady state depends

on the outer soil layer radius, but for transient simulations it will affect the result.


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4.5.2 Unsteady state simulations

The previously mentioned shutdown and the following restart (described in 4.4.2) have

been simulated using the OLGA model.

The simulations carried out by OLGA are in accordance with the course of events during

the fields shut-in and restart (described in 4.4.2). The focus when comparing the OLGA

simulations with the field data has been to evaluate the temperature development in the

pipeline. Both the temperature cooling of the fluid in the buried pipeline during shut-in

and the temperature increase due to pressurization of the pipeline during restart is

discussed. Also the possible liquid surge discussed in section 4.4.2 has been paid specialattention.

First approach when simulating the fields shut-in and restart was to use the steady state

tuned OLGA model (i.e. a roughness of 0.01 mm and a sand layer thickness equal to 1 m,

see section 4.5.1). Figure 25 shows the fluid temperature topside during the restart from

the OLGA simulations and from the field data. The figure shows that OLGA predicts too

low temperature topside during the restart.

It should be noted that when simulating the restart of the pipeline after 21 hours shut-in

instead of 65 hours (using the same OLGA model as above), the OLGA prediction of

topside temperature gives good match to the field data, see Figure 26. A quite similar

result was obtained when the steady state tuned model was run with 2 meters of sand

around the pipe, Figure 27. This model is of course unrealistic and not applicable because

it will make the model mismatch in steady state.However this gave reason to investigate

how much the properties of the sand influenced the steady state tuned model. In one case

the Cp was changed to 1800 J/(kgK), Figure 28. The density was changed to 2300 kg/m3

in another, Figure 29. And in one case the changes were combined, Figure 30.

The approach to model the buried pipeline by assuming a concentrically sand layer equal

to 1 m is a simplified method which gives good agreement with field data for steady state

production (reference section 4.5.1). However, a more precise way to model the buried


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concentric sand layer as part of the wall. Applying the theorem in the OLGA users

manual gave the model a better match when considering stable production. However

when simulating the dynamic shut-in/restart of the field it mismatched considerably.

Investigating Figure 32 shows that the previously mentioned increase in temperature (at

time 78 hours, see section 4.4.2, Figure 18) does not appear in the OLGA simulations.

Reason for this could be that OLGA does not predict the liquid plug very well, indicating

that no liquid surge moves through the system. However when plotting the gas and liquid

massflow versus time, see Figure 34, the liquid plug appears at approximately 4700

minutes. This is also almost at the same time as the discussed increase in temperatureappears. A possible explanation could be that OLGA over predicts the pressurization and

heats up the gas too quick. Hence the gas reaching the liquid temperature faster in the

simulations than what is the reality.

The case with the short shut-in indicated that the cooling time of the pipeline is

significantly longer than what is expected from the first approach model. This gave

reason to investigate the affect the properties of the sand had on the model. Simulations

showed that increasing the Cphad more effect than increasing the density. Use of the soil

model is the closest match to unsteady state field data reached in this study, Figure 35. It

has also been verified that the soil model which produce the best match field data

regarding the shut-in/restart, also gives good agreement with the steady state field data in

section 4.5.1 (see Figure 23 and Figure 24). Even if the soil model is the closest match to

this dynamic restart it does not match in a satisfactory way. The Cpof the sand, in the soil

model, was increased and gave a better result. However part of the temperature

development does not follow the field data, Figure 36.

It is difficult to know for sure if the mismatch between OLGA predictions and field data

is mainly explained by deviation in cooling time during shut-in or by deviation in heat

development during compression restart, or by a combination of these.


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4.7 Conclusion

Several conclusions can be drawn from the work that has been conducted on this field.

The reduction of the pipe wall roughness to 0.01 millimeters was very successful and

gave the model a good match when considering the pressure drop in the pipeline.

The wall model with one meter of sand around the pipeline complied with the

temperature drop from stable production and gave satisfactory results. When looking at

the shut-in/restart incident the more complicated soil model gave a better result. Howeverdue to the relatively large deviations it can not be concluded that this model is correct.

Nor can it be defined as completely wrong. It has been show that the effect is minimal

when changing the density of the soil. However the effect of changing the Cp has a larger

impact.

Whether the mismatch in OLGA is caused mainly by deviation in the cooling time,

during shut-in or by deviation in the heat developed during pressurization restart has not

been determined in this study. To conclude in either way more field data is needed.


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5 Field B

In this section Field B will be generally described, field data will be analyzed and

evaluated. The OLGA model will be tested and an effort to improve it will also be

initiated.

5.1 General

Field B is located in the North Sea and contains hydrocarbons characterised as gas

condensate. The production started in September 2004. The Reservoir is located 4000meters below MSL. This field is defined as a high pressure high temperature (HPHT)

field. Initial reservoir pressure is 780 bars and the initial temperature is 150 C. The field

is expected to recover approximately 55 billions Sm3of gas and 190 million barrels of

condensate. It is planned that the production will reach plateau rate in year 2006 and that

it will produce until 202419

, Table 9 shows the production for each year. Figure 3722

shows the phase envelope for the gas, different curves for condensate content in the gas

have been plotted.

5.2 System overview

The field has been built with a fully integrated steel platform. From the platform to land

there are two pipelines, each ending up at different processing plants. The first pipeline

transports light oil and the other one transports rich gas. The rich gas pipeline, Figure 38,

is 146.5 kilometres long and is the pipeline that has been investigated in this study. The

rich gas comes from a separator on the platform and moves down the riser and further

through in the pipeline on its way to the process plant, Figure 39.

5.3 Design Basis

The simulation tool used in this study is OLGA 2000 v4.13. Further PVTSim v11/14 has

been used to generate fluid properties tables which are input to the OLGA simulations.


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The gas comes directly from a separator and the fluid composition is represented in Table

1119, 22.The flowline has an inner diameter of 710 millimetres, while the riser has an inner

diameter of 650 millimetres. The riser is coated with an epoxy layer of 0.005 metres.

However the pipeline is uncoated and as a base case a roughness of 0.03 millimetres is

used in the simulations20

.

The selected material for the pipeline is carbon steel. The pipeline has no insulation exept

from a 0.006 metres thin layer of Asphalt enamel and 0.05 metres of concrete layer. The

pipe is not buried and combined with the selected materials12

this give the pipeline a

overall heat transfer coefficient of 32 W/(m2-C), Figure 40. This is implemented in the

OLGA model and the material properties are shown in Table 11.

The hydrate control for the pipeline is based on continuous injection of MEG. At a

production of 20.7 MSm3/d the injection is supposed to be 12.7 m

3/d in a 90 / 10 MEG /

Water ratio. The relationship between injection and production is linear. At 13.5 MSm3/d

(circa 135 kg/s) the production rate that has been simulated, the injection rate is 8.3

m3/d22.

The ambient temperature changes from month to month in the North Sea. The warmest

months are from October to January, and correct temperatures have been applied in the

simulations13

.

5.4 Field Data Analysis

The field data obtained for this field is limited. This is due to new operating procedures

that commenced in February 2005.

A production profile from 15th

to the 26th

of February this year is show in Figure 4121

. As

shown in the figure the production rates are quite stable and remain fairly constant at

approximately 135 kg/s. The temperature drops to ambient temperature quite fast due to

the fact that the pipeline is neither buried nor considerably insulated. The temperature is


35/89



measured at the inlet of the pipeline and at the outlet (process plant). The inlet

temperature is 32 C and at ambient temperature at the outlet (around 4-7 C at this time

period).

The pressure drop for this period is quite low for such a long pipeline, circa 14 bars. To

evaluate the pressure drop the problem has been approached in the same manner as

described in section 4.4.1. The fluid properties have been calculated in PVTSim. The

pressure drop was calculated using the same equations as mentioned earlier (Equation 4.1

and Equation 4.2). As previously an average of the fluid properties were used. The fluid

properties do not change too much over the pipeline. This due to the low pressure dropand that the temperature falls quickly and stays in the area of the ambient temperature.

Calculation was first done by treating the fluid as one phase gas, hence n equal to 3, gas

viscosity and density was applied in Equation 4.1 and Equation 4.2. The other variables

are defined in 5.2 and 5.3. This gave a pressure drop of 10 bars, which is almost a 30 %

miscalculation compared to field measurements. To compare, the pressure drop was also

calculated using the liquid properties from PVTSim. This gave as expected a too high

pressure drop, 17 bars. This can indicate that there is a change in the flow regime

somewhere in the pipeline, and this will affect the pressure drop calculations. It was thus

aimed to use OLGA to investigate the flow regime in the pipeline and to investigate if

OLGA would give a closer approach to the pressure drop calculations.

5.5 Simulations and Results

OLGA has, as in section 4.5, been applied to see if the simulation tool can achieve a

closer match to field data than the calculations performed in 5.4. Attempts to tune the

model against field data have also been investigated.

The model was tested with respect to the pressure drop in the pipeline. In order to

eliminate the uncertainties connected to the pressure drop in the choke located on the


36/89



platform before the riser and the onshore chokeii, the pressure drop in between the chokes

was used for testing. The model has only been tested for massflow equal to 135 kg/s

which mentioned earlier gives approximately 14 bars pressure drop (according to field

data). The base case model described in section 5.3 gives a pressure drop of 20 bars

which is further away than the simplified calculations described above.

In order to improve the model, the pipelines geometry was investigated to verify that the

deviation in pressure drop was not caused by any simplifications in the geometry. The

profile used in the OLGA model is quite detailed, shown in Figure 38 (the green line).

From this it is possible to conclude that it can not explain the large deviation22

. Accordingto Frode Nygrd, who has worked with the model in Statoil, tuning of the roughness has

no considerable effect thus this has not been performed.

The discussed deviation can be related to the liquid transport in the pipeline. In order to

verify that this could be the case, a parameter study was performed in OLGA where the

base case model was used and the mass flow was changed from 80-280 kg/s. Plotted in

Figure 42 is the pressure drop and the liquid accumulation in pipeline depending on the

mass flow. The production rate for the field data is also indicated in the figure. Based on

this plot it was decided to tune the friction factor between the phases, the OLGA keyword

is called LAM_LGI. LAM_LGI is a coefficient that will be multiplied to the gas-liquid

interfacial friction factor calculated by OLGA. The standard value is 1.0 for this

coefficient6. Several simulations were run with different values for the interfacial friction

factor, ranging from 0.01 2.1, the results are shown in Table 12. The tuning did not

reach the desired results. A case was run where OLGA used a fluid properties file where

the gas density was reduced with 5 %, the results from this simulation are also shown in

Table 12.

iiThe CV curves for the chokes were not available, i.e. data for pressure drop as a function of opening of

the choke were not available.


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(in particular the liquid hold-up) so changing this value should be used with great care. If

the case is a straight horizontal pipe with stratified flow of gas and liquid increasing the

tuning factor (LAM_LGI > 1.0) would increase the drag of the gas on the liquid and

therefore reduce the liquid hold-up. The opposite will happen if the factor is reduced

(LAM_LGI < 1.0) for this particular case. OLGA is based on mechanistic principles and

backed up by experimentation. Thus the friction factors implemented are controlled by

physical laws and by changing these OLGA deviates from the physical principles it is

built on23

. Table 12 shows that tuning of LAM_LGI gave no clear indication of whether

the tuning factor should be reduced (1) in order to get at better match

with field data pressure drop. The Table show that the best match to field data is obtainedwhen the LAM_LGI is reduced to 0.5 and increased to 1.1, thus the liquid hold-up is

reduced in the first case and increased in the last case. Both cases gave a deviation in

pressure drop equal to 22%.

Too see if any miscalculation of gas density (calculated by PVTSim) would affect the

results, a simulation was carried out where the gas density was reduced by 5%. This did

not have any considerable effect on the pressure drop.

The field data obtained for this field does not allow for extensive testing due to the fact

that data for only one mass flow was available. It should be noted that the experience

from these simulations appends to the already existing experiences with poor OLGA

predictions for gravity dominated flow. It stands out that the tool needs significant

improvement for calculations where the pressure drop is dominated by gravity forces.


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5.7 Conclusion

Field data for Field Bs pipeline has been evaluated with respect to the drop in pressure

and an effort has been made to match the OLGA model with the field data without

satisfactory success.

Simple hand calculations were performed which were partly successful. From flow

regime charts, provided by OLGA, two flow regimes were distinguished. Calculating the

pressure drop for each one, an almost perfect result was reached.

The base case model miscalculated the pressure drop by almost 43%. Attempts to

improve the model by tuning on the interfacial friction factor should be carried out

showing great care. Tuning on this factor will contradict physical principles. The best

match to field data is obtained when the tuning factor is reduced to 0.5 and increased to

1.1, thus the liquid hold-up in the pipeline is reduced in the first case and increased in the

last case. Both cases gave a deviation in pressure drop equal to 22%.

The field data obtained for this field does not allow for extensive testing due to the fact

that data for only one mass flow was available. It should be noted that the experience

from these simulations appends to the already existing experiences with poor OLGA

predictions for gravity dominated flow. It stands out that the tool needs significant

improvement for calculations where the pressure drop is dominated by gravity forces.


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6 References

1T.M. Irfansyah, K.M. Bansal, G. Gunarwan, D. Lopez, TOTAL E&P Indonesia.

Simulation of multiphase flows in Indonesian Pipelines: Comparison of TACITE and OLGA results 2005

2Hvard Eidsmoen and Ian Roberts, Scandpower Petroleum Techonology

Issues relating to proper modelling of the profile of long gas condensate pipelines, 2005

3K.H. Bendiksen et al., Institute for Energy Technology

The Dynamic Two-Fluid Model OLGA: Theory and Application, SPE 19451, 1991

4Mark Reed et al., SINTEFTechnical Documentation for the Pipeline Oil Spill Volume Computer Model, 2003

5Dag Malnes, Institue for Energy TechnologySlug Flow in Vertical, Horizontal and Inclined Pipes, 1983

6Scandpower Petroleum Technology

OLGA 2000 Users manual version 4.13, 2003

7Statoil internal web pageshttp://intranet.statoil.no/inf/svg00976.nsf/unid/4125680700363BD3C1256F2B00497C38

8Stig Ludvig Selberg, Ingrid Hnsi, Statoil ASAField A PETEK design Basis Document no: 2708-2001, 2003

9Jan Hundseid, Sverre Espedal, Statoil ASA

Field A Flow assurance, design and operating philosophy Document no: 01S96*11914, 2002

10Bodil F. Strmme, Statoil ASAPrivate communication, June 2005

11Statoil registration tool, Prosty v6.5

Prosty Field A, January May, 2005

12Adrian Bejan, Duke University

Heat Transfer (Appendix B), 1993

13Met Offices webpages, United Kingdom

http://www.met-office.gov.uk/research/ncof/shelf/browser.html

14Knut Lunde, Statoil ASA

Private communication, January May 2005

15Gisle Haaland, Statoil ASA

Private communication, February 2005

16Kenneth Bruer, The Institution Polytech, 2005

Introduction to the use of the Soil/Grid function in OLGA, presentation at Statoil Forus, 2005.

17Yves Charon and Claude Mabile, Institut Franais du Ptrole (IFP)Ways to Fight Internal Pressure Losses in Gas Lines, Paris 2005


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18Torbjrg Klara Fossum, Statoil ASA

Private Communication, January May 2005.

19R.M. Monsen, E.S. Pedersen, K.A. Brresen, L.S. Lien, Statoil ASAField B Annual Reservoir Development Plan, 2004

20N.N, Statoil ASAField B Rich gas transfer to Process Plant System Design report Doc. no.: D-194-SA-P192-F-RD-002

21Ola J. Rinde, Gassco

Private Communication, March 2005

22Frode Nygrd, Statoil ASA

Private Communication, March April 2005

23Gael Chupin, Scandpower Petroleum Technology

Private Communication, April 2005


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7 Tables

Table 1 Expected Production9

Year Gas Rate Water Rate Reservoir Wellhead Arrival Required Wellhead Arrival

Pressure Pressure Pressure Pressure Temp Temp

[MSm3/d] [Sm3/d] [bar] [bar] [bar] [bar] [C] [C]

2004 11 100-200 430 290 254 60 98 85

2005 11 100-200 330 180 134 60 90 72

2006 8,5 100-200 245 112 53 60 86 60

2007 6,79 300-500 200 96 57 60 81 56

2008 5,42 300-500 170 83 55 53 80 53

2009 5 300-500 145 75 46 48 77 49

2010 4 300-500 130 65 43 43 75 45

2011 3,2 300-500 110 60 45 38 73 41

2012 2,7 300-500 100 55 43 35 71 38

2013 2,2 300-500 90 50 40 35 70 33

2014 1,7 300-500 85 47 40 35 68 27

The table shows how gas and water rates, reservoir, wellhead, arrival and required pressures, wellhead and

arrival temperatures change with time.

Table 2 Fluid composition 1 for Field A9

Component Mol % Mol wt Liquid Density g/cm Critical T C Critical P bars

N2 0,29 28,01 -146,95 33,94CO2 8,45 44,01 31,05 73,76

C1 77,58 16,04 -82,55 46,00

C2 6,74 30,07 32,25 48,84

C3 2,71 44,10 96,65 42,46

iC4 0,39 58,12 134,95 36,48

nC4 0,69 58,12 152,05 38,00

iC5 0,21 72,15 187,25 33,84

nC5 0,24 72,15 196,45 33,74

C6 0,28 86,18 0,66 234,25 29,69

C7 0,46 86,60 0,76 251,19 39,00

C8 0,52 101,40 0,78 278,28 33,49

C9 0,32 115,00 0,80 300,38 29,78

C10 0,23 134,00 0,81 328,68 25,67

C11 0,18 147,00 0,82 345,68 23,84

C12-C13 0,26 167,22 0,83 369,96 21,68

C14-C16 0,22 203,63 0,85 408,72 19,10

C17-C20 0,14 253,00 0,87 453,89 17,12

C21-C26 0,07 316,26 0,90 503,75 15,81

C27-C34 0,02 407,34 0,92 566,22 14,85

C35-C45 0,00 527,39 0,95 638,28 14,32

C46-C61 0,00 689,29 0,98 724,53 14,12


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Table 3 Fluid composition 2 for Field A9

Component Mol % Mol wt Liquid Density g/cm Critical T C Critical P bars

N2 0,44 28,01 -146,95 33,94

CO2 5,08 44,01 31,05 73,76

C1 77,45 16,04 -82,55 46,00

C2 7,67 30,07 32,25 48,84

C3 3,60 44,10 96,65 42,46

iC4 0,51 58,12 134,95 36,48

nC4 0,95 58,12 152,05 38,00

iC5 0,31 72,15 187,25 33,84

nC5 0,34 72,15 196,45 33,74

C6 0,39 86,18 0,66 234,25 29,69

C7 0,62 89,07 0,76 255,28 37,56C8 0,70 101,48 0,78 278,14 33,55

C9 0,42 114,37 0,80 299,55 30,52

C10 0,26 134,00 0,81 326,82 25,94

C11-C12 0,39 153,35 0,82 351,56 23,11

C13 0,15 175,00 0,83 376,24 20,84

C14 0,12 190,00 0,84 392,33 19,64

C15-C16 0,19 213,25 0,84 415,96 18,20

C17-C18 0,13 243,35 0,85 444,17 16,87

C19-C21 0,12 274,61 0,86 471,94 15,94

C22-C25 0,09 321,68 0,87 510,72 14,95

C26-C71 0,08 427,77 0,89 596,55 13,75

Table 4 Detailed wall construction Field As pipeline9

Spool Main Pipe Spool_Zone2 WholeRiser Topside Pipe

Measured Length [m] 80 17167 590 138 304

Wall Template Spool Wall Pipe sone1 wall Riser Spool wall Riser Jtube wall Topside pipe wall

Material in wall [mm]

13 Chrome 19,0 16,8 19 35,3 19

FBE 0,3 0,3 0,3 0,3 0,3

PP-adh 0,3 0,3 0,3 0,3 0

PP-Solid 6,4 6,4 6,4 9,4 0

PP-Foam 54 30 54 0 0

PP-Solid Outer 4 4 4 0 0

Water Solid 0 0 0 72,1 0

Sand 0 500 0 0 0

Wall thickness [mm] 84,0 557,8 84,0 117,4 19,3


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Table 5 Material properties used in the OLGA simulations at Field A12

Material properties 13% Chrome FBE PP-adh PP-Solid PP-Foam PP-Solid Outer Water Solid Sand

Type Solid Solid Solid Solid Solid Solid Solid Solid

Capacity [J/(kg*K)] 450 1500 2461 2366 2262 1911 4200 1100

Conductivity [W/(m*k)] 18,1 0,3 0,22 0,22 0,167 0,22 0,58 2,1

Density [kg/m3] 7835 1300 900 900 720 900 1000 2000

Table 6 Selected steady state data11

Date pressure subsea temperature topside pressure topside subsea temp massflow

bars Celsius bars Celsius kg/s

15/1/2005 260.30 73.5 238.94 95.36 109.19

17/1/2005 259.00 78.3 234.55 96.52 117.9617/1/2005 259.40 75.7 231.30 92.10 133.85

18/1/2005 260.00 77.4 231.25 93.33 134.26

18/1/2005 261.30 78.0 233.97 93.53 130.96

19/1/2005 260.00 78.0 230.76 94.30 135.72

19/1/2005 247.50 77.2 221.07 95.79 125.87

19/1/2005 244.90 76.5 221.05 95.37 115.27

20/1/2005 237.50 74.1 220.02 93.31 93.77

21/1/2005 255.50 76.5 234.11 95.86 109.41

23/1/2005 255.00 76.1 233.51 95.82 109.35

25/1/2005 254.20 77.3 232.85 95.83 109.01

27/1/2005 251.20 76.3 230.28 95.67 107.5729/1/2005 251.80 77.1 230.04 95.81 109.17

30/1/2005 251.70 77.7 229.70 95.79 108.40

Table 7 Steady state data used in the extensive testing of the models11

Date pressure subsea temperature topside pressure topside subsea temp massflow

bars Celsius bars Celsius kg/s

17/1/2005 259.00 78.3 234.55 96.52 117.96

17/1/2005 259.40 75.7 231.30 92.10 133.85

18/1/2005 260.00 77.4 231.25 93.33 134.26

18/1/2005 261.30 78.0 233.97 93.53 130.96

19/1/2005 260.00 78.0 230.76 94.30 135.72

19/1/2005 247.50 77.2 221.07 95.79 125.87

19/1/2005 244.90 76.5 221.05 95.37 115.27

20/1/2005 237.50 74.1 220.02 93.31 93.77

21/1/2005 255.50 76.5 234.11 95.86 109.41

23/1/2005 255.00 76.1 233.51 95.82 109.35

25/1/2005 254.20 77.3 232.85 95.83 109.01

27/1/2005 251.20 76.3 230.28 95.67 107.57

29/1/2005 251.80 77.1 230.04 95.81 109.17

30/1/2005 251.70 77.7 229.70 95.79 108.40


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Table 8 Evaluation of base case

Date massflow [kg/s] dp field data [bars] dp base case [bars] dp deviation [%]

17. January 117,96 24,45 26,29 7,5 %

17. January 133,85 28,10 32,30 14,9 %

18. January 134,26 28,75 32,59 13,3 %

18. January 130,96 27,33 31,09 13,8 %

19. January 135,72 29,24 33,29 13,9 %

19. January 125,87 26,43 30,15 14,1 %

19. January 115,27 23,85 26,06 9,3 %

20. January 93,77 17,48 18,87 7,9 %

21. January 109,41 21,39 23,32 9,0 %

23. January 109,35 21,49 23,39 8,8 %

25. January 109,01 21,35 23,24 8,9 %27. January 107,57 20,92 22,87 9,3 %

29. January 109,17 21,76 23,40 7,5 %

Table 9 Gas production from Field B20

Gas

contract

year

Field B

[MSm3/d]

Gas

contract

year

Field B

[MSm3/d]

2004 13,9 2015 4,4

2005 20,7 2016 3,5

2006 20,7 2017 2,9

2007 20,7 2018 2,4

2008 20,7 2019 2,1

2009 20,3 2020 1,9

2010 16,8 2021 1,7

2011 12,7 2022 1,5

2012 9,5 2023 1,3

2013 7,2 2024 1,1

2014 5,4 2025 0


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Table 10 Material properties used in the pipeline on Field B22

Material properties Carbon steel Asphalt enamel Concrete

Type Solid Solid Solid

Capacity [J/(kg*K)] 500 1465 880

Conductivity [W/(m*k)] 43,25 0,95 2,20

Density [kg/m3] 7850 1300 2600

Table 11 Gas composition for Field B19, 22

Component Mol % Mol wt Liqu id Density g/cm Crit T C Crit P bara

H2O 0,08 18,02 1,00 374,15 220,89

N2 0,18 28,01 -146,95 33,94

CO2 3,69 44,01 31,05 73,76

C1 82,93 16,04 -82,55 46,00

C2 7,32 30,07 32,25 48,84

C3 3,21 44,10 96,65 42,46

iC4 0,46 58,12 134,95 36,48

nC4 0,94 58,12 152,05 38,00

iC5 0,26 72,15 187,25 33,84

nC5 0,27 72,15 196,45 33,74C6 0,23 86,18 0,66 234,25 29,69

C7 0,23 96,00 0,75

C8 0,15 107,00 0,77

C9 0,05 121,00 0,79

C10-C11 0,02 137,28 0,79

C12-C13 0,00 163,70 0,80

C14 0,00 183,70 0,82

C15-C16 0,00 202,30 0,83

C17-C18 0,00 234,30 0,83

C19-C22 0,00 278,40 0,85


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Table 12 Results from the tuning based on OLGA simulations.

Type of riser pressure plant pressure delta pressure deviation

tuning barg barg bara %0.01 Tuning 111,56 90,90 20,66 48 %

0.5 Tuning 107,94 90,90 17,04 22 %

1.1 Tuning 107,94 90,90 17,04 22 %

1.5 Tuning 109,13 90,90 18,23 30 %

1.9 Tuning 109,13 90,90 18,23 30 %

2.1 Tuning 112,58 90,90 21,68 55 %

No tuning (1.0) 110,95 90,90 20,05 43 %

No tuning w/reduced gasdensity 110,82 90,90 19,92 42 %


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8 Figures

Figure 1 Schematic drawing of horizontal flow regimes4

Image 1 shows Bubbly flow, Image 2 shows plug flow, Image 3 shows smooth stratified flow, Image 4

shows wavy flow, Image 5 show slug flow and Image 6 shows annular flow.

Figure 2 GUI OLGA6

This figure shows the graphical user interface in OLGA.

1 2 3

4 5 6


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Phase envelope Field A

0

50

100

150

200

250

300

350

400

450

0 50 100 150 200 250 300 350

pressure [bara]

tempera

ture

[C]

Typical inlet p & T

Typical outlet p & T

Figure 3 The phase Envelope for Field A8

This figure shows the phase envelope for Field A, which was created using PVTSim v14. In the phase

envelope typical pressure (p) and temperature (T) values are plotted.


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Figure 4 System Overview for Field A9.

PT denotes pressure- and TT denotes temperature measurements.


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Figure 5 Figure profile for one of the wells at Field A9

This figure shows the elevation versus horizontal length in meters for one of the wells at Field A.


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Figure 6 Overview for one of the wells at Field A9.

This figure shows an overview over the main valves and measurement tools placed in the well and at the

wellhead. PT and TT denote pressure- and temperature measurements respectively.


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Figure 7 The pipeline profile for the pipe at Field A9

This figure shows the elevation versus horizontal length in meters for the pipeline from Field A.

Figure 8 Field As buried pipeline9

The figure shows the pipe buried 0.5 meters beneath the sea bottom (in sand).

Sea bottom

0.5 meters

SAND/SOIL


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Hydrate curve - Year 2004-2006

0

50

100

150

200

250

300

350

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26

Temperature, C

Pressure,

bar

No MEG 10% MEG 20% MEG 30% MEG 40% MEG 50% MEG

Figure 9 Hydrate equilibrium curve for Field A

The graph shows the effect of MEG injection, calculated in PVTSim 119. The curves are plotted for

pressure (bars) versus temperature (C)


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Massf low in flow line

0

20

40

60

80

100

120

140

160

jan. 05 jan. 05 jan. 05 jan. 05 jan. 05 jan. 05 jan. 05 jan. 05 jan. 05 feb. 05 feb. 05

Date

Mas

sflow[

kg/s]

Figure 10 Production profile for Field A11

The figure shows the massflow [kg/s] versus time starting on the 15thof January.


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15

17

19

21

23

25

27

29

31

90 95 100 105 110 115 120 125 130 135 140

massflow kg/s

dp

bara

Figure 11 Pressure losses on Field A11

This figure shows the pressure loss for the field data plotted versus massflow, the line is generated by

excel.


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dT vs q

0

5

10

15

20

25

90 95 100 105 110 115 120 125 130 135 140

q [kg/s]

dT[C]

Figure 12 Temperature drop on Field A

11

In this figure the drop in temperature is illustrated as a function of massflow.


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0

5

10

15

20

25

30

35

40

45

50

60 70 80 90 100 110 120 130 140

massflow [kg/s]

pressureloss[bara]

field data

calc k=0.04 mm

calc k=0.03 mm

Figure 13 Calculated pressure drops

The graph shows the result from the simplified with respect to the pressure drop on Field A. The pressure

drop is plotted versus massflow.


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Shutdown

0

10

20

30

40

50

60

70

80

90

100

-5500 -5000 -4500 -4000 -3500 -3000 -2500 -2000 -1500 -1000 -500 0 500

minutes

mass

flow

kg

/s

0

10

20

30

40

50

60

70

cho

ke

%

total rate

choke

10th of 12th of March

Figure 15 Shutdown sequence for Field A11

The figure shows how total rate changes with the choke opening in % versus time. The time scale starts on

negative for simplicity reasons (easier to match with previous OLGA simulations)


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Figure 16 Injection of MEG at Field A

Shows the MEG injection along the pipelines profile at the moment the pipe is shutdown. The y-axis

denotes amount of MEG in the water phase. The graph is taken from OLGA simulations.


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Hydrate Area

0

50

100

150

200

250

0,000 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

C

bara

65 hrs Shutdown

HYDRATE

21 hrs Shutdown

pressure buildup

Figure 17 Hydrate area

Shows Field As pipeline profile as it enters the hydrate area for 21 and 65 hours shutdown and during the

pressure build-

Documents

OLGA2000_TransientSimulation