MSc Thesis. Jonathan Roche - Investigate the rate of phase re-segregation in a shut-in multiphase well for a range of starting water cuts using transient well modelling. Software; OLGA-ROCX.

SCHOOL OF ENGINEEERING
MSc Oil and Gas Engineering
Investigate the rate of phase re-segregation
in a shut-in multiphase well for a range of
starting water-cuts using transient well
modelling.
Jonathan Roche (1215737)
September, 2014

Investigate the rate of phase re-segregation in a
shut-in multiphase well for a range of starting
water-cuts using transient well modelling.
JONATHAN ROCHE
(1215737)
September 2014
This report is submitted in partial fulfilment of the requirements for
the Degree of Master of Science in Oil and Gas Engineering at
Robert Gordon University, Aberdeen.

Declaration
This thesis is submitted to The Robert Gordon University in accordance
with the requirements of the degree of Master of Science in Oil and Gas
Engineering, in the School of Engineering. I confirm that the material
presented in this report is my own work. Where this is not the case, the
source of material has been acknowledged.
Student Name Jonathan Roche
Signed ................................................
Date 17 September 2014

Abstract
When a multiphase production well is shut-in at surface, the effects of
gravity and density difference cause phase re-segregation.
A dynamic wellbore simulator was used to investigate the rate of phase
re-segregation in a shut-in multiphase well for a range of starting water-
cuts. Output plots showed that, as water-cut at time of shut-in increases,
the time taken for phase re-segregation increases.
Simulation results confirmed empirical observations that in 90% water-
cut wells, the phases redistribute completely in less than a week. That is,
the tubing string fills with 100% oil/gas with all water having gravitated
out of the well, being replaced by reservoir oil/gas.
Sensitivity analysis of fluid properties and well data showed good
agreement with established theories and phenomena. Results show that
oil density, which is related to gas-oil ratio and bubble point, affects the
rate of phase re-segregation.
The rate of phase re-segregation is of particular interest when
considering intermittent production. Also termed skimming; this
production method utilises the phase re-segregation phenomenon to
produce dry oil intermittently from high water-cut wells.
To simulate well skimming, a wellbore model was coupled to a near-
wellbore reservoir model. Model parameters were varied to optimise skim
frequency and skim time to maximise recovery of dry oil.
Also investigated, was phase re-segregation occurring in the reservoir
during a prolonged shut-in. Onset of phase re-segregation was apparent
during a shut-in period of 20 days.

i
Acknowledgments
I would like to extend my thanks to both Alastair Baillie, for his guidance
and supervision throughout this project, and my industry mentor, Tony
Peters (Fairfield Energy, UK) for his support and the opportunity to work
on this study.
Thanks also go to Gareth Herron (Xodus Group) and Luke Boongird
(Chevron, UK) for their time and advice.

ii
Table of Contents
Acknowledgments....................................................................... i
Table of Contents ....................................................................... ii
List of Figures ............................................................................ v
List of Tables............................................................................. ix
Nomenclature ........................................................................... xi
Abbreviations...........................................................................xiii
Conversion Factors...................................................................xiv
Chapter One
INTRODUCTION
1.1. Overview........................................................................ 1
1.2. Rationale........................................................................ 2
1.3. Aims/Objectives .............................................................. 2
1.4. Methodology ................................................................... 3
1.5. Limitations and Constraints ............................................... 3
Chapter Two
LITERATURE REVIEW
2.1. Wellbore Storage Effects................................................... 4
2.2. Well Testing.................................................................... 6
2.2.1. Pressure Build-up Test ................................................ 6
2.2.2. Pressure Transient Analysis.......................................... 6
2.3. Estimating Bottom-hole Pressure........................................ 8
2.3.1. Reservoir Pressure from Shut-in THP ............................. 9
2.4. Skimming/Intermittent Production.................................... 11
2.4.1. Case Study: Fairfield Energy, Dunlin Field (North Sea) ... 12
2.5. Phase Re-segregation in the Reservoir .............................. 16
2.6. OLGA........................................................................... 17
2.6.1. OLGA Overview........................................................ 17
2.6.2. Black oil Correlation.................................................. 18
2.6.3. OLGA-ROCX ............................................................ 19

iii
Chapter Three
OLGA MODEL
3.1. OLGA Well Data: Base Case............................................. 22
Chapter Four
RESULTS/DISCUSSION
4.1. Base Case .................................................................... 27
4.2. Sensitivities .................................................................. 30
4.2.1. Water-cut 60 – 90% ................................................. 30
4.2.2. Water-cut 90 – 98% ................................................. 31
4.2.3. Gas-Oil Ratio (GOR).................................................. 33
4.2.4. Oil Density .............................................................. 35
4.2.5. Tubing Size ............................................................. 38
4.2.6. Deviated Well .......................................................... 38
4.3. OLGA-ROCX.................................................................. 39
4.3.1. Skimming ............................................................... 40
4.3.2. Re-segregation in the Reservoir.................................. 44
4.4. Evaluation of software .................................................... 47
Chapter Five
CONCLUSIONS AND RECOMMENDATIONS
5.1. Conclusions .................................................................. 48
5.2. Recommendations ......................................................... 50
REFERENCES ............................................................................ 51
BIBLIOGRAPHY ........................................................................ 56
APPENDICES ............................................................................ 58
Appendix A............................................................................... 59
Stokes Law .............................................................................. 59
Appendix B............................................................................... 59
OLGA-ROCX Coupling................................................................ 60
Appendix C............................................................................... 61

iv
OLGA Well Base Case: Input Data ............................................. 61
Appendix D .............................................................................. 67
Tubing Size .............................................................................. 67
Appendix E............................................................................... 69
Deviated Well........................................................................... 69
Appendix F............................................................................... 73
OLGA-ROCX Well Data .............................................................. 73
Appendix G .............................................................................. 75
ROCX Input File........................................................................ 75

v
List of Figures
Figure 1. 1: Wellbore Fluid Distribution............................................ 5
Figure 2. 1: Wellbore storage on log-log pressure derivative plot ......... 7
Figure 2. 2: Reservoir Pressure - From Shut-in THP Data.................. 10
Figure 2. 3: Pressure Traverse. P7 & W4, P6 & W1 are Producer (P) and
Injector (W) wells, Psat = Saturation Pressure at Reservoir Temperature
................................................................................................ 11
Figure 2. 4: Production from ‘skim wells’ in the Dunlin Field, showing the
variation in skim frequency and skim volume for each well................. 13
Figure 2. 5: Skim volume compared to shut-in THP (bars: skim volume,
scatter plot: THP)........................................................................ 14
Figure 2. 6: Well DA-30: Tubing Head Pressure v Time .................... 15
Figure 2. 7: Well DA-36: Tubing Head Pressure v Time .................... 15
Figure 3. 1: OLGA Well Model: Base Case ...................................... 23
Figure 4. 1: Volume of each fluid in tubing changing during shut-in
period ....................................................................................... 28
Figure 4. 2: Base Case: Plot of THP v Shut-in Time also showing the
volume fraction of each phase (gas, oil, water) in the tubing during shut-
in period.................................................................................... 29
Figure 4. 3: Pressure response during shut-in at 3000ft TVD............. 29

vi
Figure 4. 4: Plot of THP v Shut-in Time also showing when the tubing
has become 100% oil/gas............................................................. 31
Figure 4. 5: WC 94%: Plot of THP v Shut-in Time also showing the
in period.................................................................................... 32
in period.................................................................................... 32
Figure 4. 7: OWC for different WC % at time of shut-in.................... 33
Figure 4. 8: The effect of changing GOR on Re-segregation Time....... 34
Figure 4. 9: Plot of THP v Shut-in Time for GOR 100 – 500 scf/STB.... 34
Figure 4. 10: Plot of THP v Shut-in Time for Oil SG 0.75 – 0.95......... 36
period ....................................................................................... 36
period ....................................................................................... 37
Figure 4. 13: OWC for different WC % at time of shut-in.................. 38
Figure 4. 14: Fluid distribution for different well deviations ............... 39
Figure 4. 15: Well Model OLGA-ROCX ........................................... 40
Figure 4. 16: Well Skimming: Plot of THP v Shut-in Time also showing
the volume fraction of each phase (gas, oil, water) in the tubing during
shut-in period............................................................................. 42
Figure 4. 17: Volumetric Flow Rates during well skimming................ 42
Figure 4. 18: Volumetric Flow Rate, 70 - 80 hours .......................... 43
Figure 4. 19: If the valve is opened for longer (5 hours), high WC is
reinstated .................................................................................. 43

vii
Figure 4. 20: Day 1, Oil Saturation ~0.1 (90% WC) ........................ 46
Figure 4. 21: Day 20, Oil Saturation ~0.16 at the top of reservoir, near-
wellbore area. ............................................................................ 46
Figure C. 1: Casing Visualisation (depth in metres).......................... 61
Figure C. 2: Casing Specifications ................................................. 62
Figure C. 3: Tubing Visualisation (depth in metres) ......................... 63
Figure D. 1: Tubing ID 3”: Plot of THP v Shut-in Time also showing the
in period.................................................................................... 67
Figure D. 2: Tubing ID 4.02”: Plot of THP v Shut-in Time also showing
shut-in period............................................................................. 68
in period.................................................................................... 68
Figure E. 1: Deviated Well Survey ................................................ 70
Figure E. 2: Deviated Well WC 90%: Plot of THP v Shut-in Time also
showing the volume fraction of each phase (gas, oil, water) in the tubing
during shut-in period ................................................................... 71
during shut-in period ................................................................... 72

viii
Figure F. 1: Well Model OLGA-ROCX.............................................. 73
Figure G. 1: ROCX Grid............................................................... 75
Figure G. 2: ROCX Fluid Properties................................................ 75
Figure G. 3: ROCX Reservoir Properties ......................................... 76
Figure G. 4: ROCX Kr and Pc........................................................ 76
Figure G. 5: ROCX Initial Conditions.............................................. 77
Figure G. 6: ROCX Boundary Conditions (Well) ............................... 77
Figure G. 7: ROCX Boundary Conditions (Reservoir) ........................ 78
Figure G. 8: ROCX Simulation ...................................................... 78

ix
List of Tables
Table 2. 1: Approximate Fluid Density Gradients ............................... 9
Table 2. 2: Dunlin Field fluid density gradients.................................. 9
Table 2. 3: Voidage efficiency, skimming operation compared to
continuous production.................................................................. 12
Table 3. 1: OLGA Input Casing Data.............................................. 24
Table 3. 2: OLGA Input Tubing Data.............................................. 24
Table 3. 3: OLGA Input Reservoir Conditions .................................. 25
Table 3. 4: Fluid Properties Base Case ........................................... 25
Table 3. 5: Casing Initial Conditions .............................................. 26
Table 3. 6: Tubing Initial Conditions .............................................. 26
Table 4. 1: Simulation Results...................................................... 30
Table 4. 2: Water-cut 90 – 98% Simulation Results ......................... 31
Table 4. 3: Oil Properties and Simulation Results............................. 35
Table 4. 4: Reservoir properties ................................................... 41
Table 4. 5: Well boundary conditions............................................. 41
Table 4. 6: Reservoir boundary conditions...................................... 41
Table 4. 7: Reservoir properties ................................................... 44
Table 4. 8: Well boundary conditions............................................. 45
Table 4. 9: Reservoir boundary conditions...................................... 45
Table C. 1: OLGA Input Casing Data.............................................. 61

x
Table C. 2: OLGA Input Tubing Data.............................................. 63
Table C. 3: Ambient Temperature ................................................. 64
Table C. 4: Formation Heat Transfer Properties ............................... 64
Table C. 5: Fluid outside production tubing..................................... 64
Table C. 6: Each inflow has conditions set ...................................... 64
Table C. 7: Fluid Properties Base Case........................................... 65
Table C. 8: Production Top Boundary Conditions.............................. 65
Table C. 9: Casing Initial Conditions .............................................. 65
Table C. 10: Tubing Initial Conditions ............................................ 66
Table E. 1: Deviated Well Profile TVD 12000ft, MD 17598ft ............... 69
Table F. 1: OLGA-ROCX Casing Data ............................................. 74
Table F. 2: OLGA-ROCX Tubing Data ............................................. 74

xi
Nomenclature
K = Permeability
Kr = Relative Permeability
∆p = Pressure Difference
P = Pressure
Pb = Bubble Point Pressure
Pc = Capillary Pressure
PI = Productivity Index
PR = Reservoir Pressure
Pref = Reference Pressure
Psat = Saturation Pressure
Pwf = Bottom-hole Well Flowing Pressure
q = Production Rate
S = Saturation
scf = Standard Cubic Foot
SG = Specific Gravity
SGR = Residual Gas Saturation
SOR = Residual Oil Saturation
STB = Stock-tank Barrel
SWC = Connate Water Saturation
T = Temperature
TR = Reservoir Temperature
V = Volume

xii
Subscripts and Superscripts
g = Gas
o = Oil
w = Water

xiii
Abbreviations
BBL = Barrel
FVF = Formation Volume Factor
GOR = Gas-Oil Ratio
ID = Inner Diameter
MD = Measured Depth
OWC = Oil-Water Contact
SPE = Society of Petroleum Engineers
THP = Tubing Head Pressure
TVD = True Vertical Depth
TVDSS = True Vertical Depth Subsea
WC = Water-cut
WI = Water Injection
WIF = Well Index Factor
WOR = Water-Oil Ratio

xiv
Conversion Factors
1 inch (“) = 0.0254 m
1 foot (ft) = 0.3048 m
1 cubic foot (scf) = 0.028317 m3
1 barrel = 0.158987 m3
1 pound (lb) = 453.592 g
1 bar = 105
Pa
1 psia = 6894.76 Pa
1 cP = 0.001 mPa.s
API Gravity =

1
Chapter One
INTRODUCTION
1.1. Overview
During production, pressure declines in the reservoir due to fluid
extraction. Pressure also drops in the wellbore as fluid moves from
bottom-hole to the wellhead. Typically, gas liberates from the liquid
phase if the pressure drops below the bubble point in the reservoir or
wellbore.
Water is often produced with hydrocarbons either from natural aquifer
encroachment or due to water injection. Due to increasing need for water
injection to maintain reservoir pressure, mature fields typically have high
water-cuts.
Operators are always seeking ways to improve production efficiency,
whilst minimising costs.
The efficiency of a mature field is often associated with its capacity to
process produced water. Initial topside design often doesn’t account for
increasing water rate. As the water-cut increases, the topside fluid
handling systems can become overloaded. Whether in separation,
transmission or disposal, a high water rate reduces oil processing
capacity and can threaten the economic viability of a field. (Arnold, 2004)
As the water-oil ratio (WOR) increases, eventually, the cost of handling
water approaches the value of the oil being produced. This is known as
the WOR “economic limit”. Once this limit is reached wells are routinely
shut-in and abandoned. (Bailey, 2000)
Intermittent production, also termed skimming, is one way to continue
production after the WOR economic limit has been reached. By
periodically shutting in the well, accounting for the phase re-segregation
phenomenon, water will gravitate out of the well, being replaced by
reservoir oil/gas.

2
The aim of well skimming is to produce the dry oil out the wellbore and
shut-in again before the reintroduction of high water-cut.
1.2. Rationale
Well skimming produces dry oil, which is the goal of all oil producers.
Knowing the rate of phase re-segregation and being able to predict when
the tubing is 100% oil/gas would enable the operator to optimise the
frequency of well skimming.
To approximate reservoir pressure from tubing head pressure (THP)
data, engineers routinely use water cut prior to shut-in and THP, which
has high error. Knowledge of the phase distribution in the wellbore
during a shut-in would mean an accurate fluid density gradient could be
determined and a better estimation of reservoir pressure.
Accurate information about the phase distribution in the wellbore would
also give engineers confidence during well intervention activities. Well
jewellery such as oil swellable packers need to be covered in the oil
phase to be set.
1.3. Aims/Objectives
The aim of this project is to run simulations using dynamic wellbore
software to estimate the time taken for phase re-segregation in a shut-in
multiphase well for a range of starting water cuts.
Sensitivity analysis will determine what parameters and conditions affect
the rate of phase re-segregation.
Additional objectives are to simulate well skimming and demonstrate
phase re-segregation occurring in the reservoir during a prolonged shut-
in.

3
1.4. Methodology
A literature review will be carried out into the phase re-segregation
phenomenon. Well skimming as a production method will be explored
and production data from the Dunlin Field’s skim wells will be analysed.
The solving mechanisms of the software and its current applications will
be reviewed.
A sample well model will be set up and simulations run. Sensitivities will
be investigated and results calibrated with data and empirical
observations.
The wellbore model will then be coupled to a near-wellbore reservoir
model in order to simulate well skimming and demonstrate phase re-
segregation occurring in the reservoir during a prolonged shut-in.
Finally, conclusions will be made and recommendations given for further
work.
1.5. Limitations and Constraints
i.) An integrated dynamic wellbore/reservoir model has not been
used to investigate the phase re-segregation phenomenon
before.
ii.) OLGA-ROCX is a recent software development and not yet
widely used in the industry.

4
Chapter Two
LITERATURE REVIEW
2.1. Wellbore Storage Effects
When a producing well is shut-in at surface, flow into the wellbore at
sand-face continues for some time.
The duration of this “after flow” is primarily dependent on three factors;
the formation permeability, the wellbore volume and the compressibility
of the fluids (Redman, 2008). If the fluid is highly compressible and the
well flow rate is low, the influx period can be long. On the contrary, high
flow rate wells with little gas have negligible periods of after-flow.
(Speight, 2011)
In a multiphase well, the second wellbore storage phenomenon is phase
re-segregation. As reservoir influx ceases and the fluids in the wellbore
stall, the effects of gravity and density difference will allow phase
segregation. Depending on shut-in conditions and fluid properties, gas
will separate from liquid, forming a gas cap at the top of the tubing, and
oil will rise to the top of water due to buoyancy (Vai Yee, 2010). Stokes’
Law, defined in Appendix A, is valid for the buoyant rise velocity of oil
dispersed in water. The greater the difference in density between the oil
and water phases, the greater the vertical velocity. (Malhorta, 2009)
When a well with a high gas/oil ratio is shut in, anomalous pressure
build-up behaviour may occur due to phase segregation. If the wellbore
pressure builds up to a value greater than reservoir pressure, back flow
from the wellbore into producing zones can occur.
Figure 1.1 illustrates the fluid dynamics of a multiphase well before and
during a shut-in.

5
Figure 1. 1: Wellbore Fluid Distribution
(Adapted from: p295, Bellarby, 2009)

6
2.2. Well Testing
2.2.1. Pressure Build-up Test
A pressure transient test is a fluid-flow test conducted on wells to obtain
well completion and reservoir data. During the test, flow rate is changed
and the pressure response as a function of time is recorded.
A pressure build-up test is performed on a well which has been producing
at a constant rate and is then shut in. A pressure recorder is lowered into
the well to record the pressure in the wellbore for several hours.
Typically, soon after the well is shut-in, the fluids in the wellbore reach a
quiescent state and bottom-hole pressure rises smoothly. This allows
interpretable test results. Semi-log methods and type curve matching
can be used for analysis. (Halliburton, 2000)
2.2.2. Pressure Transient Analysis
During the period of wellbore storage, reservoir effects can be masked or
distorted. If the wellbore storage effects are not properly recognised,
they could be misinterpreted as reservoir characteristics, leading to
errors in the identification of the reservoir model and calculations of
parameters. Hence, the measured data must be critically evaluated
before the pressure transient analysis. (Qasem et al, 2001)
Wellbore storage effects last until pressure is equalized between the
wellbore and formation (Qasem et al, 2001). In most circumstances,
masking due to wellbore storage effects end after the early-time "hump"
on a pressure derivative plot (Fig 2.1).
Wellbore storage shows up as a unit slope at the start of the pressure
test. ∆p and its derivative ∆p’ are proportional to the elapsed time and
produce a 45o
straight line on the log-log plot. On the derivative plot, the
transition from wellbore storage effects to infinite acting radial flow gives

7
a “hump” that gradually disappears as reservoir trends become
recognisable. (Ahmed, 2011)
Figure 2. 1: Wellbore storage on log-log pressure derivative plot
(Redman, 2008)
Wellbore phase re-segregation can result in a more complex transient
trend. Phase segregation yields a net increase in the wellbore pressure
due to the relative incompressibility of the liquid and the inability of the
gas to expand in a closed system (Qasem et al, 2002). Bottom-hole
pressure may temporarily build up to a value greater than reservoir
pressure, resulting in an anomalous hump in the pressure response.
Stegemeier and Matthews (1958) attributed this behaviour to rising
bubbles of gas and the re-segregating of the phases in the wellbore.
Different models have been developed to distinguish phase redistribution
during well testing. Stegemeier and Matthews (1958) documented the
relation of phase re-segregation to the pressure build-up hump and its
size. The size of the hump was correlated with the volume of the gaseous
phase in the tubing. Olarewaju (1989) discusses the similarity between
pressure build-up behaviour in the transitional flow regime of dual

8
porosity systems and distortion due to phase segregation, demonstrating
how to differentiate between them.
Different methods have been used to analyse phase redistribution during
a build-up test. Fair (1981), Thompson et al. (1986) and Hageman et al.
(1993) proposed mathematical models for phase re-segregation. In their
models dimensionless pressure solutions were presented for type-curve
matching. Fair (1981) used a simple exponential function to describe the
pressure change resulting from the oil and gas segregation. Hageman et
al. (1993) modified Fair’s method by using an error function to represent
the pressure change when Fair’s model did not give a good fit of field
data influenced by wellbore phase redistribution. Several authors, such
as Winterfeld (1989), Hasan et al. (1994) and Xiao et al. (1995)
developed numerical simulators to simulate counter-current flow during
phase re-segregation.
2.3. Estimating Bottom-hole Pressure
Due to operational and completion difficulties, it is generally not possible
to record pressure data opposite the perforation zone. Hence, in many
cases, pressure data is recorded at a depth above the sand-face and then
converted to the pressure at the point of interest. For instance, using
Equation 2.1, reservoir pressure can be estimated from THP. Knowledge
of the fluid density gradient is required. Typical fluid density gradients
are shown in Table 2.1.
PR= THP + (depth * fluid density gradient) (Eq 2.1)

9
Table 2. 1: Approximate Fluid Density Gradients
Fluid
Pressure Gradient
(psi/ft.)
Gas <0.15
Oil 0.25 to 0.35
Water 0.40 to 0.55
When there is more than one phase present in the wellbore, the
conversion requires knowledge of the gradient of the fluid between the
pressure gauge and the formation. Due to phase re-segregation, the fluid
distribution can be constantly changing during shut-in.
2.3.1. Reservoir Pressure from Shut-in THP
To approximate reservoir pressure from tubing head pressure data,
engineers routinely use water cut prior to shut-in to calculate the fluid
density gradient. This disregards the phase re-segregation phenomenon
and can lead to erroneous, misleading results.
During annual shutdowns, Fairfield Energy compare pressure build-up
(PBU) data from producing wells with pressure falloff data from injection
wells to estimate reservoir pressure at their Dunlin Field (Fig. 2.2).
For production wells, after sufficient time to let the phases redistribute,
the oil gradient can be used with confidence. For injection wells the water
gradient is used.
Pressures are calculated using Equation 2.1, with the fluid density
gradients from Table 2.2. The datum depth is 9000ft TVDSS.
Table 2. 2: Dunlin Field fluid density gradients
Water Gradient 0.445psi/ft
Oil Gradient 0.35psi/ft

10
Dashed lines are pressure falloff data from injection wells, dots are PBU
data from producers, assuming a 100% oil column during PBU.
Figure 2. 2: Reservoir Pressure - From Shut-in THP Data
(Source: Fairfield Energy, September 2014)
Falloff and build-up data from 06/05/2013 to 22/11/2013 converge at
around 4400psi. If the water-cut prior to shut-in was used instead of the
oil gradient, given water-cuts are around 90%, the calculated pressure
around producers would increase by 400 to 500psi resulting in pressures
greater than around the injectors.
In the pressure traverse plot (Fig 2.3), production wells P6 and P7 were
at water-cuts above 90% whilst producing. Although producers have
higher THPs than the injectors, the reservoir pressures are in fact lower
using oil gradients during the closure.

11
Figure 2. 3: Pressure Traverse. P7 & W4, P6 & W1 are Producer (P) and
Injector (W) wells, Psat = Saturation Pressure at Reservoir Temperature
(Source: Fairfield Energy, September 2014)
The Dunlin Field produces from an under-saturated reservoir and THP
remains above bubble point, however, for a producing well where THP
drops below bubble point, the gas content in the tubing will need to be
considered for calculating the fluid density gradient.
2.4. Skimming/Intermittent Production
Many oil fields in the North Sea are reaching the end of their economic
lifetime and effective reservoir management and application of new
technologies are required to maximise recovery factors.
Well skimming is one way to prolong the lifetime of high water-cut wells
and increase recovery. By periodically shutting in the well for re-
saturation and producing for a short time it is possible to produce oil with
0% water-cut.

12
Table 2.3 considers water production and required water injection (WI)
support for continuous production compared to well skimming for high
water-cut wells.
Table 2. 3: Voidage efficiency, skimming operation compared to
continuous production
Production Water Production
Required WI
Support
Voidage Efficiency
Oil
Volume
Water-cut
Continuous
Production
Skimming
Operation
Continuous
Production
Skimming
Operation
Skimming Operation
Compared to
Continuous Production
10 90% 90 0 100 10 1000%
10 95% 190 0 200 10 2000%
10 99% 990 0 1000 10 10000%
Without accounting for formation volume factors, the table above
demonstrates the exponential benefits of well skimming as a mode of
operation.
2.4.1. Case Study: Fairfield Energy, Dunlin Field (North
Sea)
Fairfield Energy have 6 oil producing wells that they produce by
skimming in their Dunlin Field, North Sea. Production from skimming 6
wells is 4350 barrels in one month. Wells are normally skimmed every 5-
7 days. (Fig 2.4)

13
Figure 2. 4: Production from ‘skim wells’ in the Dunlin Field, showing the
variation in skim frequency and skim volume for each well.
(Source: Fairfield Energy, June 2014.)
One of the important factors is THP of the skim well; normally high shut-
in THP gives a higher amount of flush oil. THP is therefore one of the
main factors when considering skim frequency. Figure 2.5 compares skim
volume to shut-in THP.

14
Figure 2. 5: Skim volume compared to shut-in THP (bars: skim volume,
scatter plot: THP).
THP charge can be correlated to the rate of phase re-segregation. As
discussed in 2.2.2. Pressure Transient Analysis, phase re-segregation
results in a net increase in wellbore pressure due to the inability of the
volatile fluid to expand.
During shut-in, the THP of well DA-30 charges slowly, hence it is
skimmed every 7-11 days (Fig 2.6). For well DA-36, THP charges rapidly,
therefore, it is skimmed every 4-5 days (Fig. 2.7).

15
Figure 2. 6: Well DA-30: Tubing Head Pressure v Time
Figure 2. 7: Well DA-36: Tubing Head Pressure v Time

16
THP levelling off indicates the fluids have fully re-distributed in the
wellbore with fluid pressure equalized between the wellbore and the
formation. From Figure 2.7 it can be seen that DA-36 is skimmed once
THP has peaked and levelled off at 89-90 barg. For the next skim (14/05)
shut-in time has been reduced; as soon as THP has exceeded previous
THP shut-in peak (89.57barg) the well is skimmed.
Analysis of the data highlights the importance of shut-in THP charge for
skimming wells. Tracking shut-in THP gives operators a good idea of
when best to skim well in order to optimise skim frequency.
Ideally, the skim frequency would be optimised so the well is produced as
soon as the tubing string has become 100% oil/gas.
2.5. Phase Re-segregation in the Reservoir
During long periods of shut-in it is possible for the phenomenon of phase
re-segregation to occur in the reservoir. North Sea fields that have
experienced such re-saturation include Dunlin, Piper and
Donan/Dumbarton.
Block 10 Area of the Dunlin Field that had been shut-in for 9 years, when
re-developed, produced with a lower water-cut than when it was initially
shut-in (Peters, 2011).
In the Piper field, fluid redistribution and natural aquifer re-pressurisation
occurred during the 4.5 years of shutdown. When Piper Bravo was
redeveloped and came back on-stream, the production rate had
significantly increased over the anticipated 1988 decline and a lower
water-cut was achieved. (Harker, 1998)
The Donan Field reached economic limit and was subsequently
abandoned in 1997 at 71% water-cut, after producing 15.3 million STB.
The field was redeveloped as the Dumbarton Field and ‘second oil’ was
achieved in 2007. Early production performance was in line with

17
expectations and the field produced 20 million STB over the next 2 years.
(Manson, 2009) (Reekie, 2010)
2.6. OLGA
OLGA is the industry standard software for transient simulation of
multiphase flow. (Schlumberger, 2014)
Society of Petroleum Engineers (SPE) publications by Hu et al. (2007)
and Sagen et al. (2011) provide reviews of the software, describing its
applications and solving mechanisms. With reference to these
publications a brief overview is given in 2.6.1 OLGA Overview.
2.6.1. OLGA Overview
Dynamic simulation is used extensively in both offshore and onshore
developments to investigate transient behaviour in pipelines and wells.
Transient modelling is vital for feasibility studies and field development
design. Flow modelling and simulation provides valuable insights into
flow behaviour, including the physics describing flow from reservoir to
processing facilities.
Transient simulation with OLGA provides an added dimension to steady-
state analyses by predicting system dynamics such as time-varying
changes in flow rates, temperature, pressure, fluid compositions and
operational changes.
The software uses an extensive collection of lab and field data to validate
the multiphase flow models. Results are continuously implemented in the
OLGA simulator to continually upgrade the technology to better match
realities of operations.
The simulation outputs provide an accurate prediction of key operational
conditions involving transient flow. At each time step, a set of five

18
coupled mass conservation equations are solved for: the oil droplets, the
water droplets, the oil film, the water film and the gas phase.
Three momentum equations are solved for the oil bulk, the water bulk
and the gas/droplet field. The model is closed by a suitable set of closure
laws describing the friction at the fluid interfaces and at the wall, the
droplet deposition, and the droplet and bubble entrainment.
One energy balance equation is solved for the fluid mixture, which
assumes thermal equilibrium between all the phases at a specific
location.
When applied to simulate well flow transients, the OLGA model is capable
of modelling complex well trajectories, advanced well completions, and
the features of equipment such as valves and pumps.
A heat transfer calculation function accounts for transient heat transfer
between the formation and the annulus, and the annulus and tubing.
(Hu et al. 2007) (Sagen et al. 2011)
The dynamic well model is able to simulate the fluid redistribution during
well shut-in by determining an accurate volume of each fluid phase at
any position in the tubing over time. (Vai Yee, 2010)
2.6.2. Black Oil Correlation
OLGA requires fluid properties to be entered either as a PVT fluid table or
by using a black oil correlation. Separate software is required to
construct a PVT fluid table.
The black oil approach assumes three distinct phases: gas, oil and water.
The oil and gas phases are recognised by their specific gravity, which are
assumed constant. In the black oil model, the gas is considered to be
dissolved in the oil phase, defined by the gas-oil ratio (GOR). The model
typically treats PVT properties of the oil and gas phases as single
functions of pressure and temperature. Therefore, oil and gas properties

19
such as density, viscosity and specific volume are taken from
experimental correlations at each pressure and temperature.
(Pourafshary, 2007)
2.6.3. OLGA-ROCX
Most reservoir simulations use vertical flow performance (VFP) tables to
represent flow in the wellbore. This approach ignores the flow dynamics
in wells, and the downstream processing and transportation. On the
other hand, most dynamic wellbore models use pressure-rate equations
to describe the inflow from the reservoir, which ignores the flow and
pressure transients in the near-wellbore regions.
Neither of the two types of modelling account for the transient reservoir-
wellbore flow interactions.
To bridge this modelling gap ROCX was developed. ROCX is a near-
wellbore reservoir model that can be coupled to the OLGA simulator to
perform integrated wellbore-reservoir transient simulations. ROCX is a
three-dimensional model, capable of simulating three-phase flow in
porous media. (Sagen et al, 2011)
Flow and temperature equations are solved in three dimensions for
saturations, temperatures and pressures in space and time. Flow rates of
each phase are calculated at the well boundary at each time step.
Input data required for the model include permeability and porosity of
the formation, thermal properties of the rock and fluids, and fluid
transport properties. Well and reservoir boundary conditions must be
given. Initial conditions including pressure and saturation for each phase
must also be defined. Outputs are in the standard industry formats,
suitable for plotting with Microsoft Excel or reservoir simulator, Eclipse.
The reservoir model is considered a plug-in to the wellbore model, with
the integrated simulation fully controlled by the wellbore model. The

20
numerical coupling between the two models is implemented in an implicit
scheme, outlined in Appendix B.
Hu et al. (2007) tested the integrated models with hypothetic cases. The
dynamic phenomena of the selected cases was known, and therefore
used to qualitatively verify the performance of the integrated model.
Test results showed that the integrated model can more accurately
predict well flow transients during shut-in/start-up and gas lift casing
heading compared to the Inflow Performance Relationship (IPR)
approach. Dynamic coning and cross-flow were also simulated
successfully.
The integrated model was also used to simulate a pressure build-up and
drawdown test on an appraisal gas well. Results confirmed that the
model can accurately match well testing data by tuning the skin factor.
Thus, indicating the integrated model’s suitability for well testing design
and estimating BHP when down-hole measurements are not possible.
Chupin (2007) applied the integrated wellbore/reservoir model to
examine liquid loading in a gas well. The integrated model provided more
realistic results compared to methods where the reservoir and the
wellbore were modelled separately.
Hu et al (2010) tested the use of the integrated model to evaluate the
cycling capability of liquid-loaded gas wells. The coupled model
successfully simulated the well cycling. The results confirmed that the
selected well can be cycled for a long period if the operator starts the
cycling before the well becomes loaded with liquid. Outputs also showed
that the average gas production can be more than doubled compared
with the stable production rate if the choke was open permanently.
Sagen et al. (2011) investigated two further applications for the OLGA-
ROCX coupling. The first case aimed to simulate chemical squeeze of a
low pressure layer in order to determine the most suitable operation
procedure for chemical placement and start-up after the treatment. The
second case aimed to calculate the pressure gradient at the near-

21
wellbore area to optimise the bean-up procedure and prevent any sand
production due to a high pressure gradient.
Both cases were successfully simulated with results confirming that the
integrated reservoir-wellbore model can easily find practical applications
for well operations and interventions.

22
Chapter Three
OLGA MODEL
3.1. OLGA Well Data: Base Case
The OLGA Well Graphical User Interface (GUI) allows the user to model a
complete well from reservoir inflow to tubing head.
Initially, a number of wells were modelled and simulated; well data and
conditions were varied, and outputs recorded.
As discussed in 2.6.1 OLGA Overview, the software takes into account all
conditions and parameters affecting the fluids. For a simulation to run
conditions must satisfy the governing equations and limitations of OLGA;
any inaccuracies or unrealistic data result in simulation failure.
Therefore, it was necessary to create a model similar to a real well.
With reference to data from the Dunlin DA-36 well, a model was
constructed (Fig. 3.1). Data and conditions of the real well were used;
although the well model was made vertical, whereas DA-36 is deviated.
Complete OLGA input data can be found in Appendix C.

23
Well Model
Figure 3. 1: OLGA Well Model: Base Case
Casing
Casing data is important for heat transfer calculations. Properties and
depths were adapted from Well DA-36 to fit the vertical well. (Tab. 3.1)

24
Table 3. 1: OLGA Input Casing Data
Tubing
Tubing properties are outlined in Table 3.2. Tubing length is 9317ft and
inner diameter (ID) is 4.02in. The tubing head valve is at 495ft TVD
(seabed) and there is a packer at 8089ft TVD.
Table 3. 2: OLGA Input Tubing Data
Reservoir
The reservoir was modelled as under-saturated, where:
( ) (Eq 3.1)
The top of the reservoir is at 11000ft TVD. Reservoir inflows are spread
between 11000 and 12000ft TVD, each with Productivity Index (PI) = 10
STB/psi/day, making total PI = 50 STB/psi/day which is the estimated PI
of Dunlin DA-36 well. Each inflow has conditions described in Table 3.3.

25
Table 3. 3: OLGA Input Reservoir Conditions
Fluid
The Black oil approach was used (see 2.6.2. Black Oil Correlation), Gas-
oil Ratio (GOR) and Bubble Point (BP) values were taken from a sample
Dunlin fluid.
Table 3. 4: Fluid Properties Base Case
SG Oil 0.85
SG Gas 1
SG Water* 1
GOR 300 scf/STB
Water-cut at Time of Shut-in 90%
Bubble Point Pressure at
Reservoir Temperature
66.33 bara
*Dunlin produced water, SG = 1.028 (approx.). Value of 1 used for ease
of calculation.
Initial Conditions
The simulation starts from shut-in conditions; pressures and
temperatures correspond with DA-36 skim well data. (Table 3.5, 3.6)

26
Table 3. 5: Casing Initial Conditions
Table 3. 6: Tubing Initial Conditions
Outputs
Each simulation was run for 7 days; minimum time step 0.1s and
maximum time Step 1s. Any larger time-step caused instabilities during
simulation.
For each simulation, outputs were requested to determine the rate of
phase re-segregation. This was achieved using a profile plot of Phase
Volume Fraction v Tubing Length. Therefore, at any time during the shut-
in and at any position in the tubing the volume fraction of each phase
was known.
The THP response during shut-in is significant as discussed in 2.4.
Skimming/Intermittent Production. A trend plot of Tubing Head Pressure
v Shut-in Time was used.

27
Chapter Four
RESULTS/DISCUSSION
In order to investigate the rate of phase re-segregation, for each case,
the time taken for the tubing string to become 100% oil/gas was
recorded.
After running sensitivities on the well model; the near-wellbore
simulator, ROCX, was coupled to the wellbore model to simulate well
skimming and determine phase re-segregation occurring in the reservoir.
4.1. Base Case
Starting from an initial shut-in water-cut of 90%, all of the water has
gravitated out of the tubing and is replaced by oil/gas after 1.24 days.
The rate of phase re-segregation in the tubing is constant throughout the
shut-in period. (Fig. 4.1)
Due to the initial shut-in THP being below bubble point pressure, some
gas bubbles out of solution to form a gas cap at top of tubing. As THP
charges above bubble point the gas re-dissolves.

28
period
Figure 4.2 shows THP starting to level off once the phases have fully re-
distributed in the tubing at Time = 1.24 days. THP continues to rise at a
steadier rate until it levels off completely at a peak of 92 bara at Time =
1.6 days. This continued THP charge after re-segregation in the tubing is
due to phase re-segregation continuing in the wellbore (7” liner). The
THP charge is steadier due to the increase in wellbore volume; Tubing ID
4.02”, Liner ID 6.185”.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 0.2 0.4 0.6 0.8 1 1.2 1.4
FluidinTubing(vol%)
Shut-in Time (Days)
gas
oil
water

29
Figure 4. 2: Base Case: Plot of THP v Shut-in Time also showing the
in period
Figure 4.3 shows pressure response during the shut-in at a specified
position in the tubing string, 3000ft TVD. As the oil/water contact level
drops below the position of interest there is a sharp increase in pressure
response due to the higher compressibility of the oil phase.
Figure 4. 3: Pressure response during shut-in at 3000ft TVD

30
4.2. Sensitivities
For sensitivity analysis, conditions were kept the same as the base case,
only changing the respective sensitivity.
4.2.1. Water-cut 60 – 90%
Water-cut % at time of shut-in was varied from 60% to 90%.
Table 4. 1: Simulation Results
Water-cut
(%)
Re-segregation Time
- Tubing 100% oil/gas (Days)
60 0.79
70 0.919
80 1.047
90 1.24
A lower initial water-cut results in a higher initial THP due to the higher
volume of compressible fluid (oil/gas) in the wellbore. THP charges and
peaks quicker, corresponding with a faster rate of phase re-segregation.
For water-cuts 60-80%, THP charges rapidly to a value greater than
bubble point pressure so practically no gas is released (Fig. 4.4).

31
Figure 4. 4: Plot of THP v Shut-in Time also showing when the tubing
has become 100% oil/gas
4.2.2. Water-cut 90 – 98%
Water-cut % at time of shut-in was varied from 90% to 98%.
As water-cut % is increased above the base case, THP charges slower
and the fluids take longer to segregate.
Table 4. 2: Water-cut 90 – 98% Simulation Results
Water-cut
(%)
Re-segregation Time
- Tubing 100% oil/gas (Days)
90 1.24
94 2.029
98 6.01
The slower rate of THP charge results in some gas coming out of solution,
for water-cut 94% and 98%. This is evident as a small hump in the THP
response between Day 0 and Day 2 on Figure 4.6.

32
in period
in period

33
Using the profile plot, the oil-water contact (OWC) can be determined
during the shut-in period (Fig. 4.7). During the early period of shut-in
(<0.5 days) fluids are unstable and OWC is not distinguishable.
Tubing Depth is from the top of tubing, which is at seabed level. Tubing
length is 9317ft, the data labels show when tubing becomes 100%
oil/gas.
Figure 4. 7: OWC for different WC % at time of shut-in
4.2.3. Gas-Oil Ratio (GOR)
The effect of GOR on rate of re-segregation was investigated.
Results showed that as GOR increases the time taken for phase re-
segregation decreases. (Fig. 4.8)
1.24, -9317 2.03, -9317 6.01, -9317
-10000
-9000
-8000
-7000
-6000
-5000
-4000
-3000
-2000
-1000
0
0 1 2 3 4 5 6 7
TubingDepth(ft)
Shut-in Time (Days)
Oil-Water Contact Level During Shut-in
WC = 90%
WC = 94%
WC = 98%

34
Figure 4. 8: The effect of changing GOR on Re-segregation Time
A higher GOR results in a faster rate of phase re-segregation. This
correlates with a steeper rise in THP, and higher THP peak.
Figure 4. 9: Plot of THP v Shut-in Time for GOR 100 – 500 scf/STB
1.05
1.1
1.15
1.2
1.25
1.3
1.35
100 200 300 400 500
Re-SegregationTime(Days)
GOR (scf/STB)
Re-segregation Time v GOR

35
The results show that changing GOR affects the rate of phase re-
segregation. However, in reality, a change in GOR would also change the
oil density and bubble point pressure.
4.2.4. Oil Density
In order to compare the effects of different densities of oil, sample cases
for heavier oil and a more volatile oil were created.
Oil specific gravity (SG) was altered as well as GOR and Bubble Point
Pressure to represent typical properties of heavier oil and a volatile oil.
Oil properties were taken from McCain (1990) and bubble points
estimated based on the GLASO correlation for the North Sea. Table 4.3
shows the oil properties and the simulation results.
Table 4. 3: Oil Properties and Simulation Results
SG 0.75
(Volatile Oil)
SG 0.85
(Base Case)
SG 0.95
(Heavy Oil)
APIo
57.5 35 17.5
GOR (scf/STB) 800 300 100
Bubble Point Pressure
(bara)
150 66.3 30
Re-segregation Time
(Tubing 100% oil/gas)
1.18 days 1.24 days 1.52 days

36
Figure 4. 10: Plot of THP v Shut-in Time for Oil SG 0.75 – 0.95
For volatile oil (SG = 0.75), the gas coming out of solution results in
rapid THP charge, and fast phase re-segregation.
period
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 0.2 0.4 0.6 0.8 1 1.2
FluidinTubing(vol%)
Shut-in Time (Days)
gas
oil
water

37
For heavy Oil (SG = 0.95), there is no gas coming out of solution, high
density oil means difference in densities between oil and water is small
resulting in slow THP charge and longer time for re-segregation.
period
Fig. 4.13 compares the OWC level during shut-in for the different sample
cases. Data labels show when the tubing becomes 100% oil/gas.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
FluidinTubing(vol%)
Shut-in Time (Days)
gas
oil
water

38
Figure 4. 13: OWC for different WC % at time of shut-in
4.2.5. Tubing Size
Sample cases showed that a smaller tubing ID results in faster THP
charge and a faster rate of phase re-segregation (see plots in Appendix
D). This can be attributed to the reduced volume of the tubing string;
less space for oil/gas expansion and less fluids in the tubing to
segregate.
4.2.6. Deviated Well
A deviated well was constructed, with inclination increasing 7.5o
for every
1000ft TVD, well data and simulation results are in Appendix E.
Simulation results show that for wells with shut-in water-cut of 90% and
94%, phases segregated quicker in a deviated well compared to a
vertical well. The deviated well has larger wellbore volume (Deviated MD
1.18, -9317 1.24, -9317 1.52, -9317
-10000
-9000
-8000
-7000
-6000
-5000
-4000
-3000
-2000
-1000
0
0.4 0.6 0.8 1 1.2 1.4 1.6
TubingDepth(ft)
Shut-in Time (Days)
Oil-Water Contact Level During Shut-in
Oil SG = 0.75
Oil SG = 0.85
Oil SG = 0.95

39
= 17598ft, Vertical MD = 12000ft) which will affect the rate of phase re-
segregation.
Additionally, different flow regimes could explain the faster rate of phase
re-segregation. For a high water-cut production well the likely flow
regime is bubble flow – droplets of oil evenly dispersed in water.
However, in deviated wells, there could be stratified or wavy stratified
flow. As pipe deviation is increased; gravity ensures there is a higher
concentration of oil in the upper section (Fig 4.14). (Catala, 1996)
Figure 4. 14: Fluid distribution for different well deviations
(Adapted from Catala, 1996)
Further investigation would be required to determine flow regimes during
production and how this affects the rate of phase re-segregation during
shut-in conditions.
4.3. OLGA-ROCX
The dynamic wellbore model (OLGA) was coupled to a near wellbore
reservoir model (ROCX) to simulate well skimming and investigate fluid
behaviour in the near wellbore area during a prolonged shut-in.
The coupled model creates a more accurate representation of fluid
dynamics in the wellbore and near wellbore by taking into account
reservoir effects. The OLGA wellbore reservoir inflow considers PI,

40
pressure, temperature and fluid properties; whereas, OLGA coupled with
ROCX also considers the reservoir characteristics and properties.
4.3.1. Skimming
A vertical well model was setup with TVD 11300ft (Fig 4.15), for
complete well data see Appendix F.
The near-wellbore model was coupled to the wellbore at 11250ft. The
wellbore penetrates vertically through the centre block of the reservoir
grid.
Figure 4. 15: Well Model OLGA-ROCX
The near-wellbore reservoir data is summarized in Tables 4.4 - 4.6. For
full ROCX input data, see Appendix G. Reservoir conditions are constant
throughout the simulation.

41
Table 4. 4: Reservoir properties
Reservoir Grid (x, y, z) (5x20m) x (5x20m) x (5x10m)
Porosity (Φ) 0.25
Rock Compressibility 6.525 x 10-5
1/bar (Pref 413.8 bara)
Permeability (x, y, z) 1000 mD
SWC 0.15
SOR 0.18
SGR 0
Initial Pressure 344.46 bara
Temperature 104.44 o
C
There are two boundaries of the coupled model, the wellbore/well
interface and the reservoir outer boundary.
Table 4. 5: Well boundary conditions
Pressure
(bara)
Skin PI Temperature
(o
C)
Sw So Sg
344.46 0 50 104.44 0.9 0.1 0
Table 4. 6: Reservoir boundary conditions
Pressure
(bara)
Temperature
(o
C)
Sw So Sg
344.46 104.44 0.9 0.1 0
Results
Parameters such as shut-in period, skim time and valve opening (%)
were varied to optimise skimming frequency and skim time.

42
Simulation results show that after a shut-in period of 2.092 days the
tubing is 100% oil/gas, and after 2.89 days the full wellbore is 100%
oil/gas (Fig 4.16).
Figure 4. 16: Well Skimming: Plot of THP v Shut-in Time also showing
shut-in period
Therefore, the well is shut-in for 3 days (72 hours) and then opened for 4
hours to get flush oil out before re-introduction of high water-cut (Fig
4.17 – 4.19).
Figure 4. 17: Volumetric Flow Rates during well skimming

43
Figure 4. 18: Volumetric Flow Rate, 70 - 80 hours
Figure 4. 19: If the valve is opened for longer (5 hours), high WC is
reinstated
The results show that well skimming can be effectively simulated and
frequency of skimming and skim time can be optimised to maximise
recovery of dry oil.

44
4.3.2. Re-segregation in the Reservoir
An integrated model was setup, a smaller reservoir grid was used to
maximise simulation duration.
A vertical well model was setup with TVD 11300ft, for well data see
appendix F.
The near-wellbore model was coupled to the wellbore at 11250ft. The
wellbore penetrates vertically through the centre block of the reservoir
grid.
The near-wellbore reservoir data is summarized in Tables 4.7 - 4.9.
Apart from the reservoir grid model, input data is the same as detailed in
Appendix G. Reservoir conditions are constant throughout the simulation.
Table 4. 7: Reservoir properties
Reservoir Grid (x, y, z) (5x5m) x (5x5m) x (5x5m)
Porosity (Φ) 0.25
Rock Compressibility 6.525 x 10-5
1/bar (Pref 413.8
bara)
Permeability (x, y, z) 1000 md
SWC 0.15
SOR 0.18
SGR 0
Initial Pressure 344.46 bara
Temperature 104.44 o
C
There are two boundaries of the coupled model, the wellbore/well
interface and the reservoir outer boundary.

45
Table 4. 8: Well boundary conditions
Pressure
(bara)
Skin PI Temperature
(o
C)
Sw So Sg
344.46 0 50 104.44 0.9 0.1 0
Table 4. 9: Reservoir boundary conditions
Pressure
(bara)
Temperature
(o
C)
Sw So Sg
344.46 104.44 0.9 0.1 0
Results
ROCX outputs are produced as text files and can be plotted with Eclipse
plotting tool, Floviz. From the simulation, commencement of re-
segregation is clear at Day 20. (Fig. 4.19, 4.20)

46
Figure 4. 20: Day 1, Oil Saturation ~0.1 (90% WC)
Figure 4. 21: Day 20, Oil Saturation ~0.16 at the top of reservoir, near-
wellbore area.
In the wellbore during shut-in, the phase re-segregation phenomenon
sees oil rise above water with the OWC level dropping. Simulation results

47
show that the phenomenon continues into the reservoir during a
prolonged shut-in.
4.4. Evaluation of software
OLGA has been proven to be an effective tool and has many potential
applications for production operations and well intervention activities.
Due to the level of accuracy of the outputs, there is a lot of data input
required, if sufficient data is not available this can be problematic.
When coupling the reservoir model to the wellbore model; the time step
to avoid instabilities has to be 0.1s-1s, whereas the ROCX time-step can
be set to 1 hour. As the models run together, the OLGA time step limits
the speed and produces large files as outputs are calculated at every
time step. Consequently, for the coupled model the maximum simulation
duration was 20 days.
In the version of ROCX used, sources could not be used in combination
with the black-oil mode. Therefore, it was not possible to include a water
injection well in the reservoir model. This is only possible when a PVT
fluid table used, which requires separate software.

48
Chapter Five
CONCLUSIONS AND RECOMMENDATIONS
5.1. Conclusions
Phase re-segregation was successfully simulated using dynamic wellbore
modelling and well skimming was effectively simulated with an integrated
wellbore-reservoir model. It was also possible to demonstrate the onset
of phase re-segregation in the reservoir during a prolonged shut-in.
Rate of phase re-segregation
1. Simulation results show that as the water-cut at time of shut-in is
increased the time taken for phase re-segregation increases.
Results confirmed empirical observations that in 90% water-cut
wells, the phases redistribute completely in less than a week with
the tubing becoming 100% oil/gas; all the water gravitated out of
the well, being replaced by reservoir oil. For the sample well
model, for a shut-in water-cut of 90% the tubing is 100% oil after
1.24 days. If shut-in water-cut set at 98% the tubing string is
100% oil/gas after 6.01 days.
2. Simulation output plots confirmed that the rate of phase re-
segregation is linked to THP charge. THP is expected to increase
initially for a period after shut in and eventually stabilise after the
well has been shut in long enough for fluids to come to
equilibrium. Results showed that a rapid THP charge correlates
with a faster rate of phase re-segregation. This is consistent with
data analysed from the North Sea, Dunlin Field.
It is evident from simulation results that any gas coming out of
solution during shut-in period results in rapid THP charge, this
agrees with theory based on the inability of the gas to expand in a
closed system.

49
3. Oil density (SG) was altered as well as GOR and bubble point to
represent typical properties of heavier oil and volatile oil. Results
show that for the heavier oil phase re-segregation takes longer.
This is attributed to the smaller difference in densities between oil
and water and no release of gas due to the lower bubble point
pressure. For the volatile oil, gas coming out of solution results in
rapid THP charge, and the larger difference in densities results in a
faster rate of phase re-segregation.
Skimming
4. Well skimming was successfully simulated with OLGA-ROCX. For a
well with water-cut 90% at time of shut-in, it was possible to
optimise skim time and frequency of skimming to maximise
recovery of dry oil. Simulation results show dry oil can be
produced for 4 hours once every 3 days.
5. The THP character was the same as Fairfield skimming data,
charging at a constant rate during phase re-segregation and
levelling off once fluids have fully redistributed.
Re-segregation in the Reservoir
6. From the Eclipse simulation it is evident that phase re-segregation
will occur in the reservoir during a prolonged shut-in. There is
potential for re-saturation to occur in any reservoir during a
prolonged period of closure for any well with water-cut less than
100% at time of shut-in. This suggests vast opportunity for the
redevelopment of abandoned fields.

50
5.2. Recommendations
1. From the simulations carried out with sample well models, it is
clear that if a model is set up to match a producing well it is
possible to determine the rate of phase re-segregation.
For this, an exact model would need to be set up with accurate
well, production and reservoir data. The input data requirements
and limitations of OLGA make this a complex undertaking.
Model inputs can be manipulated to match flowing conditions of a
well. Once the model is correlated with real data it is then possible
to save the case at a specific time during the simulation as a
restart case. This means separate identical models can be
duplicated and initial conditions set to the restart case. Thus,
allowing the user to investigate different cases and varying
parameters for the same initial conditions.
2. Potential to produce dry oil from redundant wells is very appealing.
Well skimming allows production of dry oil from mature fields
where water-cut is too high to produce continually. This method of
production is worth consideration to maximise economic recovery
from mature North Sea oil fields.
3. As software advances, in the future we can expect to accurately
simulate phase re-segregation in the reservoir using wellbore-
reservoir modelling.
4. A potential application of OLGA-ROCX is the modelling of cross-
flow in long term shut-in wells. Particularly in abandoned fields
where different zones in wells are left open, leaving fluids free to
use them as pathways for reservoir fluid distribution.

51
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59
Appendix A
Stokes Law
( )
(Eq A.1)
Where:
v = velocity of the rising oil droplet, cm/s
gc = gravitational acceleration constant, cm/s2
Δρ = difference in density between the oil and water phases, g/cm3
dp = oil droplet diameter, cm
μL = viscosity of the water, g/cm.s
(Malhorta, 2009)

60
Appendix B
OLGA-ROCX Coupling
The numerical coupling between the integrated models is implemented in
an implicit scheme described by Hu et al (2007) and Sagen et al (2011).
The notion is that the reservoir model calculates a sensitivity coefficient
for the production rate with respect to the wellbore pressure at each time
step and makes it available for the wellbore flow model. At the next time
step, the wellbore model uses this sensitivity coefficient to solve the new
wellbore pressure.
The principle of the model coupling is summarised below:
1. Assuming the models have been integrated up to time step n, the
wellbore model begins integration to time step n+1 by requesting
the reservoir model to calculate the sensitivity coefficients and
, which are used in Equation B.1:
(Eq B.1)
Where is the pressure in the wellbore, is the mass flow rate
with the subscript referring to the phase, ie. gas, oil or water.
2. The wellbore model uses the above relationship as a boundary
condition and solves for the complete model. The wellbore model
has now completed time step n+1 and sends and to the
reservoir model.
3. The reservoir model completes its time step n+1 calculation by
using the wellbore model supplied boundary condition.
The sensitivity coefficient is calculated by:
(Eq B.2)
And is given by:
(Eq B.3)

61
Appendix C
OLGA Well Base Case: Input Data
Casing
Table C. 1: OLGA Input Casing Data
Figure C. 1: Casing Visualisation (depth in metres)

62
Figure C. 2: Casing Specifications

63
Tubing
Table C. 2: OLGA Input Tubing Data
Figure C. 3: Tubing Visualisation (depth in metres)

64
Heat Transfer
Table C. 3: Ambient Temperature
Table C. 4: Formation Heat Transfer Properties
Table C. 5: Fluid outside production tubing
Reservoir
The reservoir was modelled as under-saturated, where:
( ) (Eq 3.1)
The top of the reservoir is at a depth of 11000ft TVD. Reservoir inflows
are spread between 11000 and 12000ft TVD. 5 inflows, each PI = 10
making total PI of 50 STB/psi/day which is the estimated PI of Dunlin
DA-36 well.
Table C. 6: Each inflow has conditions set

65
Fluid
The Black oil approach was used (see 2.6.2. Black oil Correlation), GOR
and Bubble Point values were taken from a sample Dunlin fluid.
Table C. 7: Fluid Properties Base Case
SG Oil 0.85
SG Gas 1
SG Water* 1
GOR 300 scf/STB
Water-cut at Time of Shut-in 90%
Bubble Point Pressure at
Reservoir Temperature
66.33 bara
*Dunlin produced water, SG = 1.028 approx. Value of 1 used for ease of
calculation.
Table C. 8: Production Top Boundary Conditions
Initial Conditions
Table C. 9: Casing Initial Conditions

66
Table C. 10: Tubing Initial Conditions

67
Appendix D
Tubing Size
Tubing ID 3”: Re-segregation Time (Tubing 100% oil/gas) = 1.171 days
in period

68
Tubing ID 4.02”: Re-segregation Time (Tubing 100% oil/gas) = 1.24
days
Figure D. 2: Tubing ID 4.02”: Plot of THP v Shut-in Time also showing
shut-in period
Tubing ID 5”: Re-segregation Time (Tubing 100% oil/gas) = 1.898 days
in period

69
Appendix E
Deviated Well
Profile
Table E. 1: Deviated Well Profile TVD 12000ft, MD 17598ft

70
Figure E. 1: Deviated Well Survey
Casing and Tubing
Casing is the same as the base case (see Appendix C); the 7” liner is
extended to MD 17598ft. Tubing string is same length as vertical well,
9317ft. The tubing head valve is at 495ft TVD (seabed) and there is a
packer at 8089ft TVD.
Reservoir
Reservoir inflows are located between 11000 and 12000 TVD, consistent
with the base case.

71
Fluid data and conditions are consistent with the base case, as described
in Appendix C.
Results
WC 90%: Re-segregation Time (Tubing 100% oil/gas) = 0.858 days
during shut-in period

72
WC 94%: Re-segregation Time (Tubing 100% oil/gas) = 1.029 days
during shut-in period

73
Appendix F
OLGA-ROCX Well Data
Well Model
Figure F. 1: Well Model OLGA-ROCX

74
Casing and Tubing
Table F. 1: OLGA-ROCX Casing Data
The tubing head valve is at 495ft TVD (seabed) and there is a packer at
8089ft TVD.
Table F. 2: OLGA-ROCX Tubing Data
Near-wellbore
The near-wellbore model is coupled to the wellbore model at 11250ft
TVD.
Fluid data and conditions are consistent with the base case, as described
in Appendix C.

75
Appendix G
ROCX Input File
Figure G. 1: ROCX Grid
Figure G. 2: ROCX Fluid Properties

76
Figure G. 3: ROCX Reservoir Properties
Figure G. 4: ROCX Kr and Pc

77
Figure G. 5: ROCX Initial Conditions
Figure G. 6: ROCX Boundary Conditions (Well)

78
Figure G. 7: ROCX Boundary Conditions (Reservoir)
Figure G. 8: ROCX Simulation

MSc Thesis. Jonathan Roche - Investigate the rate of phase re-segregation in a shut-in multiphase well for a range of starting water cuts using transient well modelling. Software; OLGA-ROCX.

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MSc Thesis. Jonathan Roche - Investigate the rate of phase re-segregation in a shut-in multiphase well for a range of starting water cuts using transient well modelling. Software; OLGA-ROCX.