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Evaluation of Polymer Flooding for Enhanced Oil Recovery in the Norne Field E-Segment

Pasha Huseynli

Petroleum Engineering

Supervisor: Jon Kleppe, IPT

Department of Petroleum Engineering and Applied Geophysics

Submission date: June 2013

Norwegian University of Science and Technology

NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY DEPARTMENT OF PETROLEUM ENGINEERING AND

APPLIED GEOPHYSICS

MASTER THESIS

Evaluation of Polymer Flooding for Enhanced Oil

Recovery in the Norne Field E-Segment

SUPERVISOR: PROFESSOR, JON KLEPPE

STUDENT: PASHA HUSEYNLI

JUNE, 2013

ii

Acknowledgements

I would like to express my sincere gratitude to my supervisor, Professor Jon Kleppe, for support

and guidance he has provided during this work. I would also like to thank Mehran Namani (PhD

Scholar) and Jan Ivar Jensen (NTNU) for their technical assistance and recommendations.

I would also like to extend my appreciation to Statoil and SINTEF for providing me with Norne

field data and chemical properties, and advises through email.

My sincere appreciation is extended to all Professors and staff of IPT, SINTEF, NTNU, for their

immeasurable amount of help.

I am also thankful to my family for giving me the chance to follow my dreams and the love to

make them a reality.

Trondheim, June 2013

Pasha Huseynli

iii

Summary

Nowadays various recovery methods like water flooding; gas flooding and etc. are widely used

in petroleum industry in order to increase hydrocarbon production as much as possible. Despite

the fact water flooding is the main technology for maintaining reservoir pressure and enhancing

oil production rate, this technology allows us to recover up to 10-40% of original oil from the

fields. The rest amount of oil is divided into two categories: the remaining oil beyond water

flooding process and bypassed oil.

The purpose of this research is to examine efficiency of polymer flooding for improved oil

recovery for Norne field E-segment by doing the simulation study on the black oil reservoir

model.

Firstly, by using Schlumberger’s software Eclipse 100, history matching was performed on the

Norne Field E-segment. The history matching was done by adjusting base reservoir model

properties, changing the shape of relative permeability curve, skin factor and KH values of

production wells. The best possible history match was gained after applying all modifications

which are stated above.

Secondly, before doing field scale enhanced oil recovery research, polymer flooding was

simulated and analyzed on three dimensional synthetic model which was built based on rock and

fluid properties of Norne field E-Segment. By assuming the model is flat and homogenous the oil

recovery with almost 9% was achieved.

In case of the E-Segment the injector well F-3H was chose for EOR study due to high residual

oil saturation around the well compare to F-2H. Two sensitivity analysis: chemical solution

concentration effect and injection rate effect were performed to evaluate the efficiency of

polymer flooding in E-Segment.

Due to the fact that the concentration of polymer was high (0.6 kg/m3) and injection rate low

(1000-3000 Sm3/day), polymer flooding didn’t give high oil production as it was forecasted. It

can be explained as a late introduction of polymer flooding in E-Segment where the mobile oil

saturation is low and aquifer mainly affects production profile, and minor increase in oil

production can be the result of a small effect of polymer in a close area to production wells.

The oil recovery increased in the range of 0.5-1% and it allows us conclude that with the

reservoir model on which the study was done; polymer flooding is not favorable for Norne field

E-Segment as Enhanced Oil Recovery methods.

iv

Table of Contents Acknowledgements ....................................................................................................................................... ii

Summary ...................................................................................................................................................... iii

List of Figures ............................................................................................................................................... v

List of Tables .............................................................................................................................................. vii

1 Introduction ................................................................................................................................................ 8

2 Literature Review ..................................................................................................................................... 11

2.1 Polymer Flooding .............................................................................................................................. 11

2.1.1 Mechanics of Polymer Flooding ................................................................................................ 11

2.1.2 Behavior of Polymer Solutions .................................................................................................. 15

2.1.3 Type of Polymers ....................................................................................................................... 20

2.1.4 Criteria for Polymer Flooding .................................................................................................... 22

2.2 Norne Field ....................................................................................................................................... 25

2.2.1 General Information ................................................................................................................... 25

2.2.2 Geology ...................................................................................................................................... 29

2.2.3 Norne Field E-Segment .............................................................................................................. 30

2.2.4 The Eclipse model of E-Segment ............................................................................................... 30

3 Simulation Results and Discussion .......................................................................................................... 32

3.1 History Matching .............................................................................................................................. 32

3.2 Synthetic Model Simulation.............................................................................................................. 43

3.4 Polymer Flooding in Norne E-Segment ............................................................................................ 46

3.4.1 Polymer Concentration Effect .................................................................................................... 47

3.4.2 Injection Rate Effect .................................................................................................................. 51

Conclusions ................................................................................................................................................. 53

Recommendation ........................................................................................................................................ 54

References ................................................................................................................................................... 55

Appendix ..................................................................................................................................................... 57

A.Polymer Introduction in Eclipse Simulator ......................................................................................... 57

B.Eclipse Data File for Norne Field E-Segment ..................................................................................... 58

C.Polymer Input File ............................................................................................................................... 81

v

List of Figures

Figure 1: Viscosity criteria for EOR processes. .............................................................................................. 9

Figure 2: Depth criteria for EOR methods. .................................................................................................... 9

Figure 3: Permeability criteria for EOR methods. ....................................................................................... 10

Figure 4: Remaining oil saturation after water and polymer flooding [5]. ................................................. 11

Figure 5: The effect of fingering in water and polymer flooding [4]. ......................................................... 12

Figure 6: Influence of viscosity ratio on oil recovery according to TUNN [7]. ............................................ 13

Figure 7: Viscosity Behavior of 500 ppm Polyacrylamide solution [9]. ....................................................... 14

Figure 8: Viscosity Behavior of 500 ppm solution of Xanthomonas polysaccharide. ................................. 14

Figure 9: The relationship between viscosity and shear rate at fixed salinity [11]. ................................... 16

Figure 10: Injected pore volume vs. concentration at outlet [7]. ............................................................... 17

Figure 11: Permeability reduction for different polymer solutions [13]. ................................................... 18

Figure 12: The effect of salinity on permeability reduction [13]. ............................................................... 19

Figure 13: Cellulose microfibrils .................................................................................................................. 21

Figure 14: Polymer Flood Project Evaluation and Development Process [16]. .......................................... 23

Figure 15: Polymer flooding process [17]. .................................................................................................. 24

Figure 16: Location of Norne Field [18]. ..................................................................................................... 25

Figure 17: The segments and wells of Norne field [18]. ............................................................................. 26

Figure 18: The profile of North-South Structure [19]. ................................................................................ 27

Figure 19: Cross-section of fluids contacts [18]. ......................................................................................... 28

Figure 20: Drainage Strategy for the Norne Field from Pre-start to 2014 [18]. ......................................... 28

Figure 21: Stratigraphical sub-division of the Norne reservoir [23] ........................................................... 29

Figure 22: The eclipse model of E-Segment ................................................................................................ 31

Figure 23: Field Oil Production Rate for the model and history. ................................................................ 32

Figure 24: Field Water Production Rate for the model and history. .......................................................... 33

Figure 25: Field Gas Production Rate for the model and history................................................................ 33

Figure 26: Relative permeability curve of base case. ................................................................................. 34

Figure 27: Relative permeability curve after adjustment. .......................................................................... 35

Figure 28: Field Oil Production Rate after adjustment relative permeability curve. .................................. 35

Figure 29: Field Water Production Rate after adjustment relative permeability curve. ............................ 36

Figure 30: Field Gas Production Rate after adjustment relative permeability curve. ................................ 36

Figure 31: Oil Production Rate for well E-2H. ............................................................................................. 37

Figure 32: Oil Production Rate for well E-3AH. ........................................................................................... 38

Figure 33: Water Production Rate for well E-2H. ....................................................................................... 38

Figure 34: Water Production Rate for well E-3AH. ..................................................................................... 39

Figure 35: Oil Production Rate for well E-2H after changing skin and KH values. ...................................... 40

Figure 36: Oil Production Rate for well E-3AH after changing skin and KH values. .................................... 40

Figure 37: Water Production Rate for well E-2H after changing skin and KH values. ................................ 41

Figure 38: Water Production Rate for well E-3AH after changing skin and KH values. .............................. 41

vi

Figure 39: Field Oil Production Rate after all modifications. ...................................................................... 42

Figure 40: Field Water Production Rate after all modifications. ................................................................ 42

Figure 41: Synthetic model. ........................................................................................................................ 43

Figure 42: Field Oil Recovery. ..................................................................................................................... 44

Figure 43: Oil Production Rate. ................................................................................................................... 44

Figure 44: Water Production Rate. ............................................................................................................. 45

Figure 45: Norne E-Segment. ...................................................................................................................... 46

Figure 46: Oil production rate at different polymer concentrations. ......................................................... 47

Figure 47: Water production rate at different polymer concentrations. ................................................... 48

Figure 48: Reservoir pressure at different polymer concentrations. ......................................................... 49

Figure 49: Bottom-hole pressure of injection well at different polymer concentrations. ......................... 49

Figure 50: Total polymer production at different polymer concentrations. .............................................. 50

Figure 51: Total oil production at different polymer concentrations. ........................................................ 50

Figure 52: Total oil production at different injection rates. ....................................................................... 51

Figure 53: Reservoir pressure at different injection rates. ......................................................................... 52

Figure 54: Reservoir pressure at different injection rates. ......................................................................... 52

vii

List of Tables Table 1: Reservoir criteria for the polymer flood project [15]. ................................................................... 22

Table 2: NPD's estimates of recoverable and remaining reserves as of 31.12.2011 [20] .......................... 27

Table 3: Wells Status in the Norne field E-Segment ................................................................................... 30

Table 4: Characteristic Fluid Parameter for Norne Field E-Segment [24] ................................................... 31

Table 5: Completion data for wells E-2H and E-3AH................................................................................... 39

8

1 Introduction

Oil and gas production life of hydrocarbon fields are divided in several phases. In the initial

stage, oil and gas production from the reservoir occurs due to natural mechanisms. In the next

stage when the reservoir pressure is not enough for supporting the production from the

formations, water is injected in order to uphold the hydrocarbon production. The water flooding

is main driving mechanism for maintaining reservoir pressure because of availability and low

cost of injection fluid. But oil recovery in this flooding process is not high enough due to

following reasons [1]:

• reservoir heterogeneity

• problems related to the well siting and spacing

• unfavorable mobility ratio

In the tertiary recovery stage (EOR), it is possible to recovery almost 30-60% of the field’s OOIP

(original oil in place) which is high compare to primary and secondary recovery methods where

recovery factor is equal to 20-40% [2]. The main types of EOR are:

• Thermal recovery

• Gas flooding

• Chemical flooding

• MIOR or Microbial IOR

Thermal recovery is an enhanced oil recovery method where steam or air is injected to the heavy

oil reservoirs to decrease the viscosity of oil. During this process the mobility ratio decreases and

oil flows towards production wells. This EOR method is widely used in unconventional oil fields

of Venezuela and Canada.

Gas flooding has been broadly used in oil industry. In gas injection process the interfacial tension

between water and oil reduces that leads better displacement efficiency. Carbon dioxide is main

injection fluid for this method due to its low cost and because it decreases oil viscosity.

Chemical flooding consists of two processes: polymer flooding and surfactant-polymer flooding

[3]. To produce oil that trapped in reservoir surfactants are injected and then polymer to decrease

the mobility ratio of oil and water which gives favorable volumetric sweep efficiency.

Microbial injection is not usual EOR method nowadays because of its high cost.

9

From figure 1, 2 and 3 it is observable that depth, permeability and viscosity are the key factors

that need to be considered and evaluated before applying enhanced oil recovery methods for

specific oil fields [1].

Figure 1: Viscosity criteria for EOR processes.

Figure 2: Depth criteria for EOR methods.

10

Figure 3: Permeability criteria for EOR methods.

11

2 Literature Review

2.1 Polymer Flooding

Polymer flooding is one of the chemical enhanced oil recovery methods and has been introduced

in late 1960s. In this chemical EOR method polymer is added to injected water in order to

increase injected fluid viscosity and to improve oil displacement in the reservoirs.

According to reports, the first commercially success was gained in Daqing oil field of China

where oil recovery factor increased up to 20% after applying polymer flooding technique [4].

After some successful projects, currently it is believed that polymer flooding can be profitable

EOR technique.

2.1.1 Mechanics of Polymer Flooding

The purpose of polymer flooding is improving sweep efficiency and consequently enhanced oil

recovery which is gained due to the following processes:

Increase in viscosity of injected fluid

Decrease in water and oil mobility ratio

Decrease in a volume of capillary trapped oil

All these processes lead higher oil recovery than water flood case. Figure 4 illustrates the result

of laboratory where clearly can be seen that polymer flooding is more efficient than water

flooding.

Figure 4: Remaining oil saturation after water and polymer flooding [5].

12

The reservoir key parameters of field, specifically, mobility ratio, effective porosity, permeability,

mobile oil saturation, volumetric sweep and etc. should be discussed in detail before starting any

project [6].

Mobility Ratio. Based on the study of DYES, CAUDLE and ERICSON (1954), the mobility

ratio is defined as:

(1)

M - mobility ratio

- relative permeability to water

- relative permeability to oil

- water viscosity

- oil viscosity

According to the equation of mobility ratio, a good displacement happens when the ration is

equal to one or less than one. Therefore to get low M, chemicals are added to injected fluid in

order to increase water viscosity with aim of to lower mobility factor.

The volumetric sweep efficiency is not good throughout water flooding and the main problem is

this recovery method is a fingering effect as shown in figure 5. But during polymer flooding,

sweep efficiency increases due to decreasing the effect of fingering compare to water flooding.

Figure 5: The effect of fingering in water and polymer flooding [4].

.

13

Figure 6 demonstrates the effect of viscosity ratio on oil recovery. It is clear that by increasing

the viscosity of displaced fluid, the oil recovery can be increased.

Figure 6: Influence of viscosity ratio on oil recovery according to TUNN [7].

Permeability. Permeability is a key parameter for polymer flooding. According to studies,

polymer flooding can be applied to field where permeability value is in the range of 20-2300mD

[8].

Effective porosity. It describes pores that are connected with other pores in rock where flow

occurs. The effective porosity also defines the recoverable hydrocarbon of reservoir and the

amount of chemical that will be needed for the polymer flooding

Initial water saturation. According to some studies the reservoirs with high water saturation are

not acceptable candidates for polymer flooding.

Water salinity. The water salinity has a great effect on mobility, adsorption and permeability

reduction features of polymers. Adding salt to polymer solutions leads to the change in shape of

molecules where its shape transforms from inflated to spherical form. Figures 7 and 8 show the

steep decrease in solution viscosity when 3% NaCl is added to polyacrylamides while in case of

Xanthan polysaccharide, added salt does have a big effect.

14

Figure 7: Viscosity Behavior of 500 ppm Polyacrylamide solution [9].

Figure 8: Viscosity Behavior of 500 ppm solution of Xanthomonas polysaccharide.

15

2.1.2 Behavior of Polymer Solutions

Viscosity. A characteristic of fluids that shows their resistance to shear stress or tensile stress. It

is specified as the ratio of the shear stress to the shear rate [10]. The relationship between these

parameters is described as,

(2)

(3)

- shear stress

– viscosity

- velocity gradient or the shear rate

The unit of viscosity is the poise and because one poise signifies a high viscosity; centipoise is

mainly used for field measurements. A liquid’s viscosity depends on the flow velocity, the size

and shape of fluid atoms and the interactions between those atoms.

There are two types of fluids: Newtonian and non-Newtonian. Fluids which have non –

changeable viscosity value at different shear rate or relationship between shear rate and shear

stress can be shown by equation 3 are termed Newtonian fluid; fluids which have non constant

viscosity value at different shear rate are called non-Newtonian fluid. The experiments show that

the viscosity of polymer solution does not remain constant at various shear rates and therefore

polymers are categorized as the non-Newtonian fluid.

Figure 9 illustrates the experimental results where relationship between the viscosity of polymer

solution and shear rate was investigated [11]. According to the laboratory study, polymer

solution behaves as Newtonian fluid at low rate of deformation while at higher shear rate acts as

non-Newtonian fluid. And based on this experimental study, correlation between the viscosity of

polymer solution and the rate of deformation was defined as,

(4)

- power-law coefficient

- exponent

16

Figure 9: The relationship between viscosity and shear rate at fixed salinity [11].

Polymer adsorption and retention. Adsorption or retention of polymer has a big effect on

flooding process. Based on previous studies, polymer adsorption depends on water salinity; as

salinity of water increases, the polymer adsorption rate also increases. It is desired to achieve

sufficient quantity for adsorption [7].

Inaccessible pore volume. During the polymer flooding chemicals do not occupy all the

effective pore volumes. This volume that is not occupied by polymers is called inaccessible pore

volume or IPV. Inaccessible pore volume is occupied by water with no polymer that leads to

change in polymer concentration. This process was studied and reported by Dawson and Lantz in

1972.

IPV is key parameter that needs to be studied due to it’s a great effect on reservoir performance.

Because the less contact with the rock surface compare to total pore volume will cause decrease

in quantity of chemical adsorption which consequently affect the efficiency of polymer flooding.

In the experiments, Littman observed that the velocity of polymer-mixed water in reservoir was

higher than the velocity of a tracer where polymer was injected and which was resulted in earlier

breakthrough in polymer than tracer (Figure 10). And this fact also proves that some of pore

volume is inaccessible to the chemicals.

17

Figure 10: Injected pore volume vs. concentration at outlet [7].

Permeability reduction.

The polymer adsorption causes to the reduction of porous media ( ) or decrease in the volume

interacted pores which can lead to no flow [8]. The permeability reduction can be defined as the

ratio of water to polymer solution at same flowing condition:

(5)

- permeability reduction

- permeability of water

- permeability of polymer

18

The shear rate, the molecular weight of polymer solution, the polymer type and pore structure

can affect permeability reduction [12].

Figure 11 shows the result of experiment where the relationship between and polymer

concentration was studied. Based on the graph, it was concluded that the permeability reduction

and concentration of associative polymer solution have nearly linear relationship. The

permeability reduction is also sensitive to salinity. The effect of salinity was investigated by

adding 2 wt% NaCl and 10 wt% NaCl to the polymer solution. It was founded that by increasing

the salinity of the conventional and associative polymer, the permeability reduction decreases

because of its lower viscosity [13].

Figure 11: Permeability reduction for different polymer solutions [13].

19

Figure 12: The effect of salinity on permeability reduction [13].

20

2.1.3 Type of Polymers

Polymers used in enhanced oil recovery methods are divided into two groups: synthetic polymers

and biopolymers.

Synthetic polymers.

This is a type of polymers that are produced synthetically and polyacrylamide - water soluble

polymers are the one of the widely used synthetic polymers for EOR. Polyacrylamides can be in

various forms: in liquid phase, gels, powder and so on.

Biopolymers.

Biopolymers are formed by living organisms. The molecular weight and structure of

biopolymers are smaller than synthetic polymers. Therefore it gives hardness that causes a good

viscosifying effect in salinity water and a bad viscosifying effect in fresh water [14].

In the late 80-ties, Statoil was involved in a large project with a biopolymer called Xanthan. It is

a polysaccharide secreted by the bacteria Xanthomonas campestris. It is an anionic polymer with

tolerance for salinity and fair tolerance for hardness ion temperature tolerance varies with water-

phase components, but starts to degrade around 93 to121°C. It is susceptible to bacterial attack

and does not tolerate extreme pH20. Even though very promising, Xanthan was found not

profitable at that time. [15]

One of the possible new areas of application for debris from the paper and pulp industry can be

polymers. Three kinds of polymers are present in wood: cellulose, hemicelluloses and lignin.

Cellulose is the framework polymer, comprising 40-50% of wood; whereas hemicelluloses and

lignin are the matrix substances present between cellulose microfibrils.

Cellulose microfibrils constitute layers (lamellas) which form the cellulose fiber as can be seen

in Figure 13. The microfibrils consist of 20-100 cellulose chains organized more or less in

parallel. The degree of parallel orientation of the cellulose chains is termed crystal Unity. The

cellulose chains consist of 5-10 000 glucose monomer units which give the microfibrils a high

aspect ratio (length/diameter =L/D). The microfibrils are 1-50 nm thick and may have an aspect

ratio of more than 100.

21

Figure 13: Cellulose microfibrils

A: Wood structure, B: Microfibrils, C: Bundle of microfibrils, D: Single microfibril, E:

Crystallite cellulose, F: Crystallite cellulose cell, G: Repeating cellulose unit.

These types of polymers have many beneficial properties. They are generally strong, hydrophilic,

and insoluble in water, stable to chemicals, generally recognized as safe to living creates,

renewable, recyclable, and easily available.

22

2.1.4 Criteria for Polymer Flooding

In order to find appropriate reservoir candidate for polymer flooding several parameters have to

be evaluated. Table 1 demonstrates basic screening criteria for polymer flooding. One oil field

that matched to these criteria is Daqing field where the incremental oil recovery about 200

MMSTB was achieved due to polymer flooding [14].

The oil field in which oil recovery is low and the water production is high, the commercial

performance of hydrocarbon production is not good.

Properties Standard

Oil Viscosity From 10 to 3000 cp

Temperature up to 120°C

Permeability 10 md to 10 Darcy

Reservoirs sandstone (preferred)

Oil gravity >15° APl

Salinity < 250,000 TDS

Oil saturation >50%

Water injectvity Good

Table 1: Reservoir criteria for the polymer flood project [15].

23

In 2007 Kaminsky et al. proposed the schematic of processes for the appraisal and development

of polymer flood projects (Figure 14).

The first step is the screening of reservoir where reservoir geometry and fluid, rock features are

studied due to the passing criteria. If the properties of suggested reservoir are matched with the

screening criteria, further deep investigations like modeling, laboratory works, and reservoir

specification can be considered. Eventually these phases result in a technical-economical

evaluation.

The next phase is to determine targets and structure the pilot test. After successful study on pilot

test, the profitable scenario is developed and improved; this involves field scale modeling and an

operation strategy that examines realization, observation and operations.

Figure 14: Polymer Flood Project Evaluation and Development Process [16].

24

Based on the literature, there are two fundamental arguments for employing the selection rules

[8]:

• Find reservoirs with high mobility ratio and poor volumetric sweep efficiency

• Define if the properties of reservoir meet the screening criteria for polymer flooding.

Figure 15 shows the process of polymer flooding. The process starts with injecting low salinity

water, followed by the polymer injection at appropriate concentration. The last stage is injecting

the water in order to push the chemical into the reservoir.

Figure 15: Polymer flooding process [17].

25

2.2 Norne Field

2.2.1 General Information

The Norne oil field is found in Norwegian Sea, 200 km from the Norwegian shore and 85 km

from the nearby oil field - Heidrun. The field is located on the blocks 6608/10 and 6508/1 where

the water depth is almost 380 m. The figure 16 illustrates the location of the Norne field compare

to other fields of the Norwegian Sea.

Figure 16: Location of Norne Field [18].

26

There are two separate oil compartments in the Norne field:

• The C, D and E segments – Norne Main Structure, discovered in 1991 and contain nearly

96% OIIP (oil in place)

• Norne G-Segment (Figure 17)

Figure 17: The segments and wells of Norne field [18].

The Norne main structure is relatively flat contains 110 m oil thickness in the formations Tofte

and Ile, gas cap in the Garn formation above the Not formation shale and acts as a barrier. This

was proved by studies that there is no communication between formations across Not shale

formation (Figure 18).

27

Figure 18: The profile of North-South Structure [19].

The type of wells of Norne field is horizontal and the first well was drilled in 1996. The oil

production started in 1997 and water injection was only drive mechanism for maintaining the

reservoir pressure. Re-injecting produced gas was also used to maintain the pressure of

formations but as a result of later researches this process was ceased in 2005 because of no

communication between the Garn and Ile formations and injected to water zone in order to

prevent early gas breakthrough (Figure 19&20).

The table 2 shows the total hydrocarbon production, estimated recoverable and remaining

reserves to 31st of December 2011 (Norwegian share).

Table 2: NPD's estimates of recoverable and remaining reserves as of 31.12.2011 [20]

28

Figure 19: Cross-section of fluids contacts [18].

Figure 20: Drainage Strategy for the Norne Field from Pre-start to 2014 [18].

29

2.2.2 Geology

The reservoir rock of Norne field is categorized by sandstones that are located at a depth of

2500-2700 m and affected by diagenesis which causes the reduction in reservoir rock quality

because of mechanical compaction. The porosity of field is approximately 25-30% while the

permeability is 20-2500 mD [21].

The reservoir consists of two main groups the FANGST which consists of the Garn, Not and Ile

formations and the BÅT which includes the ROR, Tofte, Tilje and Åre formations and these

formations comprises sub formations (Figure 21) [22].

Figure 21: Stratigraphical sub-division of the Norne reservoir [23]

30

2.2.3 Norne Field E-Segment

The Norne E-Segment is also a part of Norne main structure; Tofte and Ile are main formations

of it because of nearly 80% of oil in the field contained in these formations. There is no

communication between E-Segment and the rest parts of field based on assumption of constant

flux boundary that means no quantity difference between the fluid inflow and outflow of

segment.

According to the eclipse model of field there are 5 wells in the Norne field E-Segments (Table

3).

Table 3: Wells Status in the Norne field E-Segment

2.2.4 The eclipse model of E-Segment

The Norne field E-Segment is was modeled with non-vertical faults in Eclipse 100. The model is

a fully implicit, three dimensional, three phase black oil. The reservoir model has 46 grids in the

X-direction, 112 in the Y-direction and 22 layers and each reservoir zone is signified by a layer,

for instance, the layers 5-11 embody the Ile and the layers 12-18 represent the Tofte. The

simulation starts from 1997 and the historical data are available until December 2004.

Table 4 gives some Norne field E-Segment’s fluid properties while Figure 22 shows the

coarsened simulation model of Norne Field E-segment.

31

Table 4: Characteristic Fluid Parameter for Norne Field E-Segment [24]

Figure 22: The eclipse model of E-Segment

32

3 Simulation Results and Discussion

3.1 History Matching In order to simulate future reservoir performance, we need to have the history matched reservoir

simulation model. The procedure of adjusting the model input data until getting the minimum

difference between the performance of the model and the history of a reservoir is termed history

matching.

The process is a crucial study to verify the reservoir rock and fluids specification throughout

model building. There is usually the limited quantity of historical data presented to characterize a

hydrocarbon reservoir. Therefore we have to get a very accurate history matched model which

we can use in making predictions.

Few decades ago, we were used to create a single model, adjust it and perform single predictions

for numerous cases due to cost, computers, methods and time restrictions. But nowadays because

of developed technology it is possible to build, evaluate more models and use them for various

prediction scenarios.

The history matching can be done automatically but the many petroleum engineers prefer to do it

manually by reason of restrictions and cost of today’s existing automatic techniques. For this

study I have done traditional (manual) history matching.

Figure 23: Field Oil Production Rate for the model and history.

33

Figures 23, 24 and 25 show the difference between the reservoir simulation model and history

data.

Figure 24: Field Water Production Rate for the model and history.

Figure 25: Field Gas Production Rate for the model and history.

34

The figures above show that there is deference between actual field data and reservoir model

data, and in order to make accurate future EOR study we need to minimize the gap between real

and model data.

For the history matching procedure used key parameters are:

Relative Permeability Of Oil to Water

Transmissibility factor

Adding an Aquifer

Skin factor

KH values around the production wells

The original case of relative permeability is shown in figure 26. The possible best matching was

gained by modifying the shape of relative permeability curve which is shown in figure 27.

Figure 26: Relative permeability curve of base case.

35

Figure 27: Relative permeability curve after adjustment.

Figure 28: Field Oil Production Rate after adjustment relative permeability curve.

36

Figure 29: Field Water Production Rate after adjustment relative permeability curve.

Figure 30: Field Gas Production Rate after adjustment relative permeability curve.

37

As might be seen from the figures 28, 29 and 30 change in the shape of relative permeability

gives better match till 2000 but after that period the difference between base and historical cases

is still high.

The next key parameter of reservoir, transmissibility factor was modified, but change of

transmissibility factors around the wells did not conclude with estimated outcomes. Also the

results of history matching after adding aquifer were subjectively assessed as "unsatisfied."

Therefore the production wells were analyzed separately in order to get a better history match.

The graphs below show that there is gap between actual and model oil and water production data

of wells E-2H and E-3AH (Figures 31, 32, 33, 34).

Figure 31: Oil Production Rate for well E-2H.

38

Figure 32: Oil Production Rate for well E-3AH.

Figure 33: Water Production Rate for well E-2H.

39

Figure 34: Water Production Rate for well E-3AH.

In order to get history match for the WOPR, WWPR of wells E-2H and E-3AH, the KH value

and skin factors of the production wells were modified. In base case the skin factor of these wells

were set to zero however I adjust it to -3 and KH values was reproduced to 9 times assuming that

there are some natural stimulation nearby wells bore of wells E-2H and E-3AH.

Table 5: Completion data for wells E-2H and E-3AH.

40

Figure 35: Oil Production Rate for well E-2H after changing skin and KH values.

Figure 36: Oil Production Rate for well E-3AH after changing skin and KH values.

41

Figure 37: Water Production Rate for well E-2H after changing skin and KH values.

Figure 38: Water Production Rate for well E-3AH after changing skin and KH values.

42

The results for history matching after applying all modifications are given below:

Figure 39: Field Oil Production Rate after all modifications.

Figure 40: Field Water Production Rate after all modifications.

43

3.2 Synthetic Model Simulation

The polymer flooding process first was studied on the synthetic model which was built based on

fluid and rock properties of Norne field.

The synthetic model has two phases: oil and water. The model is homogeneous and consists of

11x11x3 grid block where the porosity value of system is equal to 0.28. There are two active

wells; one producer and one injector which are positioned in blocks 11,11,3 and 1,1,3

correspondingly (Figure 41). The simulation lasted 600 day where the water is injected for the

first six months then polymer injection at concentration of 0.5 kg/m3 starts lasting fourteen

months.

Figures 42, 43 and 44 represent the results of simulation, where blue line is water flooding (base

case) and red line is polymer flooding. Figure 42 demonstrates that by applying the polymer

flooding the oil recovery factor increased almost 9%, from 0.78 to 0.86.

Figure 41: Synthetic model.

44

Figure 42: Field Oil Recovery.

Figure 43: Oil Production Rate.

45

Figure 44: Water Production Rate.

It is readily observable that after 200 days there is low water production from day 200 to day 450

and then it increases to its highest rate which is 480 Sm3/day because water occupies the space

left by residual oil as they form a bank and move towards producing wells (Figure 44).

The EOR study on the synthetic model confirms the efficiency of polymer flooding and allows

us to do the same study for actual Norne E-segment model. However, it is probable not to gain

predictable results from the study on actual case because in the synthetic model, it is assumed

that the system is homogeneous and flat.

46

3.4 Polymer Flooding in Norne E-Segment

As it mentioned in previous chapter, there are 2 active injectors: F-1H and F-3H, 2 active

producers: E-2H and E-3AH in Norne E-Segment. In order to have effective EOR results, the

proper injector needs to be selected.

Due to the fact F-1H is placed in water region, while F-3H is located in the oil region, injector F-

3H was selected as a good option for polymer flooding study. Because in the case of F-1H,

polymer will spread out in water zone and lot of polymer will be needed for injection to increase

oil recover and it will be non-economical for EOR project.

The prediction was made from 2005 to 2017 where the injection of polymer starts from January

2006 and ends at January 2009. Then through the rest of simulation water was injected. For the

project two sensitivity analyses were studied:

Polymer concentration effect

Injection rate effect

Figure 45: Norne E-Segment.

47

3.4.1 Polymer Concentration Effect

The simulation has been run with three different concentration values to investigate polymer

concentration effect. The graphs below show the results of study with polymer concentration of

0.3, 0.6, 0.9 kg/m3. In this case water is injected for the first eight years from 1997 to 2005 then

polymer injection lasts from 2006 to 2009 and finally from 2009 to 2017 water is injected.

Total oil, water and polymer production, the production rate of oil and water, reservoir pressure

and bottom-hole pressure of injection well (F-3H) have been plotted for analysis.

Figure 46: Oil production rate at different polymer concentrations.

Figure 46 illustrates that polymer flooding causes higher oil recovery as compare to water

flooding where red line curve shows the result of polymer flooding at concentration of 0.3 kg/m3

green line curve injection at concentration of 0.6 kg/ m3 while blue one injection of chemical at

concentration of 0.9 kg/m3.

From the figure above it is obvious that after applying the polymer flooding in 2006, there was

considerable increase in oil production rate and the highest oil production for all injected

polymer concentrations is attained between 2007 and 2009, then hydrocarbon production rate

came down the base case. The reason is oil saturation; because of notable sweep performance,

48

oil production rate is higher in early stage and then after 2009 trend goes down by reason of low

oil saturation which left behind breakthrough front. But based on graph 29, polymer flooding at

different concentrations increased oil recovery in a small range of 0.5-1%.

From figure 47 it is clear that the polymer injection has a great effect on sweep efficiency;

polymer flooding at concentration of 0.9 kg/m3 causes enhanced sweep efficiency and less field

water production compare to base case. Despite the fact that the water production rate is lower at

early stage, it increases faster over other cases after 2012.

Figure 48 illustrates the reservoir pressure of all cases which is sustained over the bubble point

(251 bara) and less the maximum restriction (300 bara). According to simulation results, higher

polymer concentration follows with higher reservoir pressure. As a solution concentration

increases, injector pressure and the pressure around injector also increase (Figure 49). Polymer

flooding at concentration of 0.9 kg/m3 gives big increase in oil recovery compares to other cases

but at that concentration the bottom-hole pressure of injection well rises from 320 bara to 420

bara which makes this case inapplicable.

Figure 47: Water production rate at different polymer concentrations.

49

Figure 48: Reservoir pressure at different polymer concentrations.

Figure 49: Bottom-hole pressure of injection well at different polymer concentrations.

50

Figure 50: Total polymer production at different polymer concentrations.

Figure 51: Total oil production at different polymer concentrations.

51

3.4.2 Injection Rate Effect

Injection rate is another crucial parameter which needs to be studied in EOR projects. In this

chapter injection rate sensitivity analyses is performed with three different fluid injection rates:

1000 sm3/day, 4000 sm3/day and 7000 Sm3/day where 4000 sm3/day is initially given injection

rate for well F-3H and is used as a base case to compare with other cases. For all cases the

polymer flooding was applied at concentration of 0.6 kg/m3.

From figure 52, for the case where injection rate is higher than the base case total oil production

is lower which can be explained as a result of early water breakthrough and at injection rate of

1000 Sm3/day, the oil recovery is slightly higher than base case.

There is low pressure drop in reservoir at lower injection rate and vice versa. The pressure of

formation and the pressure of injector (Figure 53 and Figure 54) behaves similarly at injection

rate of 1000 Sm3/day and 4000Sm3/day which let us conclude that 1000 Sm3/day is most

favorable rate for polymer flooding process for Norne E-segment.

According to sensitivity analyses, the polymer flooding is an effective EOR technique compare

to water flooding due to slightly high oil recovery factor, low water production and better

mobility factor. Studies show that total oil production increases with injecting polymer at high

concentration because of improved mobility ratio and high injection rate causes reduction in oil

production due to early water breakthrough.

Figure 52: Total oil production at different injection rates.

52

Figure 53: Reservoir pressure at different injection rates.

Figure 54: Reservoir pressure at different injection rates.

53

Conclusions

History Matching:

Modifying the shape of relative permeability curve for Norne E-Segment helps to

minimize the difference between actual and reservoir model data.

The skin factor and KH values of wells have been adjusted in order to get low water and

high oil production into the wells.

A closer match was gained for Norne E-Segment by applying all parametric

modifications which are stated above.

Prediction:

A better result was achieved when EOR study was performed after 2006.

F-3H is best candidate as an injector for polymer flooding in Norne E-Segment.

Polymer flooding causes increase in oil recovery in range of 0.5-1%.

Production of oil is higher for higher polymer concentration.

Polymer flooding at concentration of 0.6 kg/m3 gave the same result of oil production but

with less polymer usage compared to 0.9 kg/m3.

Fluid injection rate at 1000 Sm3/day can be better case for polymer flooding due to its

high oil recovery and low injection pressure.

54

Recommendation

The type and chemical property of polymer that was used in this study may not be truthful.

Therefore the detailed laboratory works need to be done in order to use the right polymer which

will be appropriate for field rock and fluid characteristics.

The injection time is another crucial parameter which needs to be studied because polymer

flooding is more effective when reservoir oil saturation is high.

55

References

1. Lyons, William C and Plisga, Gary J. Standard Handbook of Petroleum and Natural Gas Engineering.

s.l. : Gulf Professional Publishing, 2011.

2. Enhanced Oil Recovery/CO2 Injection. United States Department of Energy. [Online] 2011.

www.energy.gov.

3. Sheng, James J. Modern Chemical Enhanced Oil Recovery ( Theory and Practice). USA : Elsevier Inc,

2011.

4. Wang, D, et al. The Influence of Visco-Elasticity on Micro Forces and Displacement Efficiency in pores,

Cores and in the Field. s.l. : SPE 127453.

5. Xia, H, et al. Effect of Elastic Behavior of HPAM Solutions on Displacement Efficiency Under Mixed

Wettability Conditions. s.l. : SPE 90234, 2004.

6. Medad, Tweyho. Polymer Flooding EOR. s.l. : Statoil ASA, 2006.

7. Littmann, J. Polymer Flooding: Developments in Petroleum Science vol 24. Amsterdam : Elsevier Inc,

1988.

8. Sorbie, K. Polymer Improved Oil Recovery. Blackie, Glasgow-London : s.n., 1991.

9. Polymer Flooding Technology –Yesterday, Today and Tomorrow . s.l. : SPE 94553, 1978.

10. Symon, Keith. Mechanics. Third ed. s.l. : Addison-Wesley, 1971.

11. Lake, L. Enhanced Oil Recovery. NJ : Prentical Hall, 1989.

12. Dawson, R. and Lantz, R. Inaccessible pore volume in polymer flooding. s.l. : SPEJ, 12:448- 452, 1972.

13. Monrawee, Pancharoen. PHYSICAL PROPERTIES OF ASSOCIATIVE POLYMER (Master Thesis). s.l. :

STANFORD UNIVERSITY, 2009.

14. Selle, Olav. An Experimental Study of Viscous Surfactant Flooding for Enhanced Oil Recovery .

Trondheim : NTNU, 2005.

15. [Online] http://en.wikipedia.org/.

16. Dong, H. Z., et al. Review of Practical Experience of Polymer Flooding at Daqing. s.l. : Paper SPE

114342, 2009.

17. Screening Criteria. SNF. [Online] [Cited: May 22, 2013.] http://www.snf-oil.com/.

56

18. Kaminsky, R. D., Wattenbarger, R. C. and Szafranski, R. Guidelines for Polymer Flooding Evaluation

and Development. s.l. : Paper IPTC 11200, 2007.

19. Lindley, J. Chemical Flooding (polymer). s.l. : http://www.netl.doe.gov, 2001.

20. Annual Reservoir Development Plan for Norne & URD Field. s.l. : Statoil, 2006.

21. Reservoir Management Plan Norne Field’ 01A05*183. s.l. : STATOIL PL 128 NORNE, 2001.

22. The NPD's fact. NPD. [Online] [Cited: June 20, 2013.]

http://www.npd.no/engelsk/cwi/pbl/en/field/all/43778.htm.

23. Welcome to IO Center-Norne Benchmark Case, Introduction to Norne Field. IO-Center. . [Online]

[Cited: Jun3 20, 2013.] http://www.ipt.ntnu.no/~norne/wiki/data/media/english/gfi/introduction-to-

the-norne-field.pdf.

24. PDO-Reservoir Geology, Support Documentation. s.l. : Statoil, 1994.

25. Reservoir Management Plan Norne Field’ 01A05*183. s.l. : Statoil PL 128, 2001.

26. Plan for Development and Operation Support Document-Reservoir Engineering. s.l. : Statoil , 1994.

27. Oil Field Glossary. Schlumberger. [Online] 2013. [Cited: 05 19, 2013.]

http://www.glossary.oilfield.slb.com/.

57

Appendix

A.Polymer Introduction in Eclipse Simulator

Before presenting the results let us shortly discuss how polymer flooding might be presented in

Eclipse simulator. The option is activated by the keyword POLYMER in the RUNSPEC

section. The mixing parameter data is obligatory and should be defined using the keyword

TLMIXPAR. The maximum number of mixing parameter regions is set using the parameter

NTMISC in RUNSPEC keyword MISCIBLE. The maximum polymer and salt concentrations to

be used in calculating the effective fluid component viscosities are entered under the keyword

PLYMAX The polymer adsorption data should be entered using the keyword PLYADS in the

PROPS section. Other polymer-rock parameters such as the rock mass density used in the

adsorption calculation, the dead pore space, the residual resistance factor are input using the

keyword PLYROCK. The shear thinning model is activated if the PLYSHEAR keyword is

present in the PROPS section. The shear thinning data consists of tables of viscosity reduction

as a function of local velocity. The values of used to calculate the velocity can be printed out

using the mnemonic POLYMER (38th switch) in the RPTGRID keyword [10].

The definition of the polymer/salt well injection streams should be set using the keyword

WPOLYMER in the SCHEDULE section. Grid arrays reports can be produced for polymer

concentration, salt concentration, adsorbed polymer concentration and the permeability

reduction factor for the aqueous phase at each report time.

2 different tables of parameters were used in polymer flooding; one of them is standard

defaulted values from ECLIPSE TECHNICAL description, while second one was kindly

presented by SINTEF ASA. After comparison (in term of running) of this data were concluded

that data given by the company suits our simulation better compare to ECTD.

58

B.Eclipse Data File for Norne Field E-Segment

-- water injection rate of F-1, F-2, and F-3 by 50

----------------------------------------------------------------------------

-- Ny model July 2004 build by marsp/oddhu

-- New grid with sloping faults based on geomodel xxx

-------------------------------------

RUNSPEC

--LICENSES

--'NETWORKS' /

--/

DIMENS

46 112 22 /

--NOSIM

--

-- Allow for multregt, etc. Maximum number of regions 20.

--

GRIDOPTS

'YES' 0 /

OIL

WATER

GAS

59

DISGAS

VAPOIL

METRIC

-- use either hysteresis or not hysteresis

--NOHYST

HYST

START

06 'NOV' 1997 /

EQLDIMS

5 100 20 /

EQLOPTS

'THPRES' / no fine equilibration if swatinit is being used

REGDIMS

-- ntfip nmfipr nrfreg ntfreg

22 4 1* 20 /

TRACERS

-- oil water gas env

1* 10 1* 1* /

WELLDIMS

--ML 40 36 15 15 /

130 36 15 84 /

--WSEGDIMS

-- 3 30 3 /

60

LGR

-- maxlgr maxcls mcoars mamalg mxlalg lstack interp

4 2000 693 1 4 20 'INTERP' /

TABDIMS

--ntsfun ntpvt nssfun nppvt ntfip nrpvt ntendp

110 2 33 60 16 60 /

-- WI_VFP_TABLES_080905.INC = 10-20

VFPIDIMS

30 20 20 /

-- Table no.

-- DevNew.VFP = 1

-- E1h.VFP = 2

-- AlmostVertNew.VFP = 3

-- GasProd.VFP = 4

-- NEW_D2_GAS_0.00003.VFP = 5

-- GAS_PD2.VFP = 6

-- pd2.VFP = 8 (flowline south)

-- pe2.VFP = 9 (flowline north)

-- PB1.PIPE.Ecl = 31

-- PB2.PIPE.Ecl = 32

-- PD1.PIPE.Ecl = 33

-- PD2.PIPE.Ecl = 34

-- PE1.PIPE.Ecl = 35

-- PE2.PIPE.Ecl = 36

-- B1BH.Ecl = 37

-- B2H.Ecl = 38

-- B3H.Ecl = 39

-- B4DH. Ecl= 40

-- D1CH.Ecl = 41

-- D2H.Ecl = 42

61

-- D3BH.Ecl = 43

-- E1H.Ecl = 45

-- E3CH.Ecl = 47

-- K3H.Ecl = 48

VFPPDIMS

19 10 10 10 0 50 /

FAULTDIM

10000 /

PIMTDIMS

1 51 /

NSTACK

30 /

UNIFIN

UNIFOUT

--RPTRUNSPEC

OPTIONS

77* 1 /

---------------------------------------------------------

--

-- Input of grid geometry

--

---------------------------------------------------------

GRID

62

NEWTRAN

GRIDFILE

2 /

-- optional for postprocessing of GRID

MAPAXES

0. 100. 0. 0. 100. 0. /

GRIDUNIT

METRES /

-- do not output GRID geometry file

--NOGGF

-- requests output of INIT file

INIT

MESSAGES

8*10000 20000 10000 1000 1* /

PINCH

0.001 GAP 1* TOPBOT TOP/

NOECHO

--------------------------------------------------------

--

-- Grid and faults

--

--------------------------------------------------------

--

-- Simulation grid, with slooping faults:

--

63

-- file in UTM coordinate system, for importing to DecisionSpace

INCLUDE

'./INCLUDE/GRID/IRAP_1005.GRDECL' /

-- '/project/norne6/res/INCLUDE/GRID/IRAP_0704.GRDECL' /

--

INCLUDE

'./INCLUDE/GRID/ACTNUM_0704.prop' /

--

-- Faults

--

--

INCLUDE

'./INCLUDE/FAULT/FAULT_JUN_05.INC' /

-- Additional faults

--Nord for C-3 (forlengelse av C_10)

EQUALS

MULTY 0.01 6 6 22 22 1 22 /

/

-- B-3 water

EQUALS

'MULTX' 0.001 9 11 39 39 1 22 /

'MULTY' 0.001 9 11 39 39 1 22 /

'MULTX' 0.001 9 9 37 39 1 22 /

'MULTY' 0.001 9 9 37 39 1 22 /

/

-- C-1H

EQUALS

'MULTY' 0.001 26 29 39 39 1 22 /

/

64

--------------------------------------------------------

--

-- Input of grid parametres

--

--------------------------------------------------------

--

INCLUDE

'./INCLUDE/PETRO/PORO_0704.prop' /

--

INCLUDE

'./INCLUDE/PETRO/NTG_0704.prop' /

--

INCLUDE

'./INCLUDE/PETRO/PERM_0704.prop' /

-- G segment north

EQUALS

PERMX 220 32 32 94 94 2 2 /

PERMX 220 33 33 95 99 2 2 /

PERMX 220 34 34 95 97 2 2 /

PERMX 220 35 35 95 98 2 2 /

PERMX 220 36 36 95 99 2 2 /

PERMX 220 37 37 95 99 2 2 /

PERMX 220 38 38 95 100 2 2 /

PERMX 220 39 39 95 102 2 2 /

PERMX 220 40 40 95 102 2 2 /

PERMX 220 41 41 95 102 2 2 /

/

-- C-1H

MULTIPLY

65

PERMX 4 21 29 39 49 16 18 /

PERMX 100 21 29 39 49 19 20 /

/

COPY

PERMX PERMY /

PERMX PERMZ /

/

-- Permz reduction is based on input from PSK

-- based on same kv/kh factor

-- ******************************************

-- CHECK! (esp. Ile & Tofte)

-- ******************************************

MULTIPLY

'PERMZ' 0.2 1 46 1 112 1 1 / Garn 3

'PERMZ' 0.04 1 46 1 112 2 2 / Garn 2

'PERMZ' 0.25 1 46 1 112 3 3 / Garn 1

'PERMZ' 0.0 1 46 1 112 4 4 / Not (inactive anyway)

'PERMZ' 0.13 1 46 1 112 5 5 / Ile 2.2

'PERMZ' 0.13 1 46 1 112 6 6 / Ile 2.1.3

'PERMZ' 0.13 1 46 1 112 7 7 / Ile 2.1.2

'PERMZ' 0.13 1 46 1 112 8 8 / Ile 2.1.1

'PERMZ' 0.09 1 46 1 112 9 9 / Ile 1.3

'PERMZ' 0.07 1 46 1 112 10 10 / Ile 1.2

'PERMZ' 0.19 1 46 1 112 11 11 / Ile 1.1

'PERMZ' 0.13 1 46 1 112 12 12 / Tofte 2.2

'PERMZ' 0.64 1 46 1 112 13 13 / Tofte 2.1.3

'PERMZ' 0.64 1 46 1 112 14 14 / Tofte 2.1.2

'PERMZ' 0.64 1 46 1 112 15 15 / Tofte 2.1.1

'PERMZ' 0.64 1 46 1 112 16 16 / Tofte 1.2.2

'PERMZ' 0.64 1 46 1 112 17 17 / Tofte 1.2.1

'PERMZ' 0.016 1 46 1 112 18 18 / Tofte 1.1

'PERMZ' 0.004 1 46 1 112 19 19 / Tilje 4

66

'PERMZ' 0.004 1 46 1 112 20 20 / Tilje 3

'PERMZ' 1.0 1 46 1 112 21 21 / Tilje 2

'PERMZ' 1.0 1 46 1 112 22 22 / Tilje 1

/

--------------------------------------------------------

--

-- Barriers

--

--------------------------------------------------------

-- 20 flux regions generated by the script Xfluxnum

--

INCLUDE

'./INCLUDE/PETRO/FLUXNUM_0704.prop' /

-- modify transmissibilites between fluxnum using MULTREGT

--

INCLUDE

'./INCLUDE/PETRO/MULTREGT_D_27.prop' /

NOECHO

MINPV

500 /

EQUALS

'MULTZ' 0.00125 26 29 30 37 10 10 / better WCT match for B-2H

'MULTZ' 0.015 19 29 11 30 8 8 / better WCT match for D-1CH

'MULTZ' 1 6 12 16 22 8 11 / for better WCT match for K-3H

'MULTZ' .1 6 12 16 22 15 15 / for better WCT match for K-3H

67

/

COARSEN

-- I1 I2 J1 J2 K1 K2 NX NY NZ

6 29 11 44 1 3 1 1 3/

6 29 11 44 5 22 1 1 18 /

16 19 45 67 1 3 1 1 3 /

16 19 45 67 5 22 1 1 18 /

20 25 45 67 1 3 1 1 3 /

20 25 45 67 5 22 1 1 18 /

26 29 45 67 1 3 1 1 3 /

26 29 45 67 5 22 1 1 18 /

30 41 63 75 1 3 1 1 1 /

30 41 63 75 5 20 1 1 16 /

30 41 63 75 22 22 1 1 1 /

30 41 76 93 1 3 1 1 1 /

30 41 76 93 5 9 1 1 5 /

30 41 76 93 12 20 1 1 9 /

30 41 76 93 22 22 1 1 1 /

30 37 58 62 1 3 1 1 1 /

30 37 58 62 5 22 1 1 18 /

30 34 54 57 1 3 1 1 1 /

30 34 54 57 5 18 1 1 14 /

30 34 54 57 20 22 1 1 3 /

30 32 51 53 1 3 1 1 1 /

30 32 51 53 5 22 1 1 18 /

30 30 48 48 1 3 1 1 1 /

30 30 50 50 1 3 1 1 1 /

30 30 48 48 5 22 1 1 18 /

30 30 50 50 5 22 1 1 18 /

33 33 52 53 1 3 1 1 1 /

33 33 52 53 5 22 1 1 18 /

35 36 57 57 1 3 1 1 1 /

35 36 57 57 5 22 1 1 18 /

68

38 38 59 60 1 3 1 1 1 /

38 38 59 60 5 22 1 1 18 /

38 39 61 62 1 3 1 1 1 /

38 39 61 62 5 22 1 1 18 /

17 19 68 85 1 3 1 1 1 /

17 19 68 85 5 22 1 1 18 /

17 19 86 89 1 3 1 1 1 /

17 19 86 89 5 22 1 1 18 /

22 25 68 70 1 3 1 1 1 /

26 29 68 70 1 3 1 1 1 /

20 21 68 70 5 22 1 1 18 /

20 21 68 69 1 3 1 1 1 /

22 25 68 69 5 22 1 1 18 /

26 29 68 69 5 22 1 1 18 /

10 15 45 51 1 3 1 1 3 /

10 15 45 51 5 22 1 1 18 /

13 15 52 57 1 3 1 1 3 /

13 15 52 57 5 22 1 1 18 /

11 12 52 54 1 3 1 1 3 /

11 12 52 54 5 22 1 1 18 /

12 12 55 56 1 3 1 1 3 /

12 12 55 56 5 22 1 1 18 /

10 10 52 53 1 3 1 1 3 /

10 10 52 53 5 22 1 1 18 /

13 15 58 59 1 3 1 1 3 /

13 15 58 59 5 22 1 1 18 /

14 15 60 61 1 3 1 1 3 /

14 15 60 61 5 22 1 1 18 /

15 15 62 64 1 3 1 1 3 /

15 15 62 64 5 22 1 1 18 /

16 16 68 69 1 3 1 1 3 /

16 16 68 69 5 22 1 1 18 /

8 9 45 46 1 3 1 1 3 /

8 9 45 46 5 22 1 1 18 /

69

9 9 47 48 1 3 1 1 3 /

9 9 47 48 5 22 1 1 18 /

31 41 94 95 1 3 1 1 1 /

31 41 94 95 5 22 1 1 18 /

34 41 96 97 1 3 1 1 1 /

34 41 96 97 5 22 1 1 18 /

36 41 98 99 1 3 1 1 1 /

36 41 98 99 5 22 1 1 18 /

39 41 100 102 1 3 1 1 1 /

39 41 100 102 5 22 1 1 18 /

/

--------------------------------------------------

PROPS

--------------------------------------------------------------------------------

--

-- Input of fluid properties and relative permeability

--

---------------------------------------------------------

NOECHO

-- Input of PVT data for the model

-- Total 2 PVT regions (region 1 C,D,E segment, region 2 Gsegment)

--

INCLUDE

'./INCLUDE/PVT/PVT-WET-GAS.DATA' /

TRACER

'SEA' 'WAT' /

'HTO' 'WAT' /

'S36' 'WAT' /

70

'2FB' 'WAT' /

'4FB' 'WAT' /

'DFB' 'WAT' /

'TFB' 'WAT' /

/

----------------------------------------------------------

--

-- initialization and relperm curves: see report blabla

--

----------------------------------------------------------

-- rel. perm and cap. pressure tables --

--

INCLUDE

'./INCLUDE/RELPERM/HYST/swof_mod4Gseg_aug-2006.inc' /

--Sgc=10 0.000000or g-segment

--

INCLUDE

'./INCLUDE/RELPERM/HYST/sgof_sgc10_mod4Gseg_aug-2006.inc' /

--

--INCLUDE

-- './INCLUDE/RELPERM/HYST/waghystr_mod4Gseg_aug-2006.inc' /

'./INCLUDE/RELPERM/HYST/waghystr.inc' /

--RPTPROPS

-- 1 1 1 5*0 0 /

--------------------------------------------------------------------------------

71

REGIONS

--

INCLUDE

'./INCLUDE/PETRO/FIPNUM_0704.prop' /

--

INCLUDE

'./INCLUDE/PETRO/SATNUM_0704.prop' /

EQUALS

'SATNUM' 102 30 41 76 112 1 1 /

'SATNUM' 103 30 41 76 112 2 2 /

'SATNUM' 104 30 41 76 112 3 3 /

/

--

INCLUDE

'./INCLUDE/PETRO/IMBNUM_0704.prop' /

EQUALS

'IMBNUM' 102 30 41 76 112 1 1 /

'IMBNUM' 103 30 41 76 112 2 2 /

'IMBNUM' 104 30 41 76 112 3 3 /

/

--

INCLUDE

'./INCLUDE/PETRO/PVTNUM_0704.prop' /

EQUALS

'PVTNUM' 1 1 46 1 112 1 22 /

72

/

--

INCLUDE

'./INCLUDE/PETRO/EQLNUM_0704.prop' /

-- extra regions for geological formations and numerical layers

INCLUDE

'./INCLUDE/PETRO/EXTRA_REG.inc' /

---------------------------------------------------------------------------------

SOLUTION

RPTRST

BASIC=2 /

RPTSOL

FIP=3 /

---------------------------------------------------------------------------------

-- equilibrium data: do not include this file in case of RESTART

--

--

INCLUDE

'./INCLUDE/PETRO/E3.prop' /

-- restart date: only used in case of a RESTART, remember to use SKIPREST

--RESTART

-- 'BASE_30-NOV-2005' 360 / AT TIME 3282.0 DAYS ( 1-NOV-2006)

THPRES

1 2 0.588031 /

1 3 0.787619 /

1 4 7.00083 /

73

/

-- initialise injected tracers to zero

TVDPFSEA

1000 0.0

5000 0.0 /

TVDPFHTO

1000 0.0

5000 0.0 /

TVDPFS36

1000 0.0

5000 0.0 /

TVDPF2FB

1000 0.0

5000 0.0 /

TVDPF4FB

1000 0.0

5000 0.0 /

TVDPFDFB

1000 0.0

5000 0.0 /

TVDPFTFB

1000 0.0

5000 0.0 /

-------------------------------------------------------------------------------

SUMMARY

FOE

RUNSUM

SEPARATE

EXCEL

74

--

INCLUDE

'./INCLUDE/SUMMARY/summary.data' /

--------------------------------------------------------------------------------

SCHEDULE

NOWARN

-- use SKIPREST in case of RESTART

--SKIPREST

-- No increase in the solution gas-oil ratio?!

DRSDT

0 /

-- Use of WRFT in order to report well perssure data after first

-- opening of the well. The wells are perforated in the entire reservoir

-- produce with a small rate and are squeesed after 1 day. This pressure

-- data can sen be copmared with the MDT pressure points collected in the

-- well.

NOECHO

--------------------------------------------

--=======Production Wells========--

--------------------------------------------

--

INCLUDE

'./INCLUDE/VFP/DevNew.VFP' /

75

--

INCLUDE

'./INCLUDE/VFP/E1h.VFP' /

--

INCLUDE

'./INCLUDE/VFP/NEW_D2_GAS_0.00003.VFP' /

--

INCLUDE

'./INCLUDE/VFP/GAS_PD2.VFP' /

--

INCLUDE

'./INCLUDE/VFP/AlmostVertNew.VFP' /

--

INCLUDE

'./INCLUDE/VFP/GasProd.VFP' /

-- 01.01.07 new VFP curves for producing wells, matched with the latest well tests in Prosper. lmarr

--

INCLUDE

'./INCLUDE/VFP/B1BH.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/B2H.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/B3H.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/B4DH.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/D1CH.Ecl' /

76

--

INCLUDE

'./INCLUDE/VFP/D2H.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/D3BH.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/E1H.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/E3CH.Ecl' /

--

INCLUDE

'./INCLUDE/VFP/K3H.Ecl' /

--------------------------------------------

--=======Production Flowlines========--

--------------------------------------------

--

-- 16.5.02 new VFP curves for southgoing PD1,PD2,PB1,PB2 flowlines -> pd2.VFP

--

INCLUDE

'./INCLUDE/VFP/pd2.VFP' /

--

-- 16.5.02 new VFP curves for northgoing PE1,PE2 flowlines -> pe2.VFP

--

INCLUDE

'./INCLUDE/VFP/pe2.VFP' /

-- 24.11.06 new matched VLP curves for PB1 valid from 01.07.06

77

--

INCLUDE

'./INCLUDE/VFP/PB1.PIPE.Ecl' /

--24.11.06 new matched VLP curves for PB2 valid from 01.07.06

--

INCLUDE

'./INCLUDE/VFP/PB2.PIPE.Ecl' /

--24.11.06 new matched VLP curves for PD1 valid from 01.07.06

--

INCLUDE

'./INCLUDE/VFP/PD1.PIPE.Ecl' /

--24.11.06 new matched VLP curves for PD2 valid from 01.07.06

--

INCLUDE

'./INCLUDE/VFP/PD2.PIPE.Ecl' /

--24.11.06 new matched VLP curves for PE1 valid from 01.07.06

--

INCLUDE

'./INCLUDE/VFP/PE1.PIPE.Ecl' /

--24.11.06 new matched VLP curves for PE2 valid from 01.07.06

--

INCLUDE

'./INCLUDE/VFP/PE2.PIPE.Ecl' /

--------------------------------------------

--=======INJECTION FLOWLINES 08.09.2005 ========--

--------------------------------------------

78

-- VFPINJ nr. 10 Water injection flowline WIC

--

INCLUDE

'./INCLUDE/VFP/WIC.PIPE.Ecl' /

-- VFPINJ nr. 11 Water injection flowline WIF

--

INCLUDE

'./INCLUDE/VFP/WIF.PIPE.Ecl' /

--------------------------------------------

--======= INJECTION Wells 08.09.2005 ========--

--------------------------------------------

-- VFPINJ nr. 12 Water injection wellbore Norne C-1H

--

INCLUDE

'./INCLUDE/VFP/C1H.Ecl' /


--

INCLUDE



--

INCLUDE



--

INCLUDE


-- VFPINJ nr. 16 Water injection wellbore Norne C-4AH

79

--

INCLUDE

'./INCLUDE/VFP/C4AH.Ecl' /

-- VFPINJ nr. 17 Water injection wellbore Norne F-1H

--

INCLUDE

'./INCLUDE/VFP/F1H.Ecl' /


--

INCLUDE


-- VFPINJ nr. 19 Water injection wellbore Norne F-3 H

--

INCLUDE



--

INCLUDE


TUNING

1 10 0.1 0.15 3 0.3 0.3 1.20 /

5* 0.1 0.0001 0.02 0.02 /

--2* 40 1* 15 /

/

-- only possible for ECL 2006.2+ version

ZIPPY2

80

'SIM=4.2' 'MINSTEP=1E-6' /

/

--WSEGITER

--/

-- PI reduction in case of water cut

--

INCLUDE

'./INCLUDE/PI/pimultab_low-high_aug-2006.inc' /

-- History and prediction --

--

INCLUDE

'./INCLUDE/BC0407_2004.SCH' /

END

81

C.Polymer Input File PLYSHEAR --Polymer shear thinning data -- Wat. Velocity Visc reduction

-- m/day CP

0.0 1.0 2.0 1.0 /

PLYVISC -- Polymer solution Viscosity Function

-- Ply conc.

Wat. Visc.

mult.

-- kg/m3

0.0 1.0

0.1 1.55

0.3 2.55

0.5 5.125

0.7 8.125

1.0 21.2 /

PLYADS -- Polymer Adsorption Function

-- Ply conc. Ply conc. Adsorbed

-- kg/m3 by rock, Kg/kg

0.0 0.0

0.5 0.0000017

1.0 0.0000017 /

TLMIXPAR -- Todd-Long staff Mixing Parameters 1 1* /

PLYMAX -- Polymer-Salt concentration for mixing maximum polymer and salt concentration

-- Ply conc. Salt conc.

-- kg/m3 kg/m3 1.0 0.0 /

PLYROCK

--Polymer-Rock Properties

--dead pore residual resistance mass Ads. max. Polymer

-- space factor density Index adsorption

0.16 1.0 2650 1 0.000017 /

evaluation of polymer flooding for enhanced oil recovery ... · pdf fileevaluation of polymer...

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