Optimizing Water Flooding Recovery

RESERVOIR ENGINEERING COURSE
EXERCISE
Title: Water Flooding
Major and Class: Petroleum Engineering, 1801 EN
Student No.:
Name:
Supervisor: Cai Wenbin
June 2021

ii
《Reservoir Engineering》
Course Exercise Assignment
Title Water Flooding
Name
Student
No.
lx1813010207
Major and
Class
PE 1801 EN
Assignments
1. Data given:
Use the REQUIRED DATA inside the tutorial file in the BR file contained in
CMG installation files in Local Disk C.
2. Designassignment
Chapter 1 Objective and methodologies of waterflooding
Chapter 2 Simulation Model Description
2.1 Rock Model
2.2 Property Model
2.3 Fluid Model
2.4 Initial Conditions
2.5 Well completion and production
Chapter 3 History Matching
3.1 Describe History Matching Process (step by step, show results for each
parameters changed)
3.2 History Matching Results
Chapter 4 Development Strategies
4.1 Residual Oil Distribution and Development Suggestions
4.2 Optimize scenario (In this case Water Flooding)
Chapter 5 Conclusion
Beginning
and ending
time
June 16, 2021--- June 30, 2021
Supervisor
Signature
June 16, 2021
Student
Signature
June 16, 2021

iii
Table of Contents
Chapter 1 Objective and Methodologies.....................................................................................1
1.1 Objective................................................................................................................................. 1
1.2 Methodology........................................................................................................................... 2
Chapter 2 Model Description .......................................................................................................2
2.1 Rock Model ............................................................................................................................ 2
2.2 Property Model ....................................................................................................................... 3
2.3 Fluid Model ............................................................................................................................ 5
2.4 Initial Conditions .................................................................................................................... 7
2.5 Well Completion and Production Forecast............................................................................. 8
2.5.1 Validating and running data file using IMEX ................................................................. 8
2.5.2 Adding and creating historical production data ............................................................... 9
2.5.3 Results of production forecasting .................................................................................... 9
Chapter 3 History Matching .......................................................................................................10
3.1 History Matching Process..................................................................................................... 10
3.1.1 Changing rock compressibility ...................................................................................... 10
3.1.2 Adjusting relative permeability curve to match production data................................... 11
Chapter 4 Development Strategies ............................................................................................12
4.1 Residual Oil Distribution and Development Suggestions .................................................... 13
4.1.1 Base case scenario ......................................................................................................... 13
4.1.2 Distribution of residual oil............................................................................................. 14
4.2 Optimization Scenario .......................................................................................................... 15
A Case Study of Water flooding (WF) ................................................................................... 15
Results of Water Flooding...................................................................................................... 16
Chapter 5 Conclusions ................................................................................................................18
References.....................................................................................................................................19

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APPENDIX: GROUP MEMBERS ...........................................................................................21

Xi’an Shiyou University Reservoir Engineering Course Design
1
Chapter 1 Objective and Methodologies
1.1 Objective
In the oil industry, waterflooding or water injection is where water is injected into the oil or
gas formation, to increase pressure in the formation and thereby stimulate production. Water
injection or water flooding is done on- and offshore, to increase oil recovery from an existing oil
or gas reservoir. Water is injected to support the reservoir pressure (also known as voyage
replacement), and also to sweep or displace oil from the reservoir, and drive it towards a production
well[1-3].
Normally only 30% of the oil in a reservoir can be extracted (primary recovery), but water
injection increases that percentage up to 50% (known as the recovery factor) and maintains the
production rate of a reservoir over a longer period. Any source of water can be used for injection.
The following sources of water are used for recovery of oil[4-7].
In water flooding, as can be seen in Fig.1 many reservoirs equivalent volumes of water are
injected into a number of wells in order to reduce the viscosity and subsequently displace the oil in
place more easily towards oil production wells[8-10]. Water flooding may be preferred in shallow
reservoirs containing oils in the viscosity range of 100-1000 cp.
Fig. 1 Waterflooding as a method of enhanced oil recovery
Produced water is often used as injection fluid. It reduces the potential of causing formation
damage due to incompatible fluids, although the risk of scaling or corrosion in injection flow lines.

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1.2 Methodology
This reservoir engineering course design will concentrate on modeling reservoir and field
operations aspects of water injection for pressure maintenance and secondary recovery using the
commercial software simulator CMG.
The methodology used in this study is to analyze the waterflooding performance for the
enhancement of oil production of virtual reservoirs using CMG-IMEX (Computer Modeling
Group) reservoir simulation tool.
Chapter 2 Model Description
Modeling of carbonate reservoirs is generally more difficult than modeling clastic reservoirs.
The reason is that carbonate rocks usually undergo a much more complex pattern of diagenetic
processes. As a result, the permeability distribution can be complex and poorly related to original
facies distribution. A further complication can be the occurrence of open fractures.
Reservoir simulation of so-called dual porosity reservoirs is difficult because of the problem
of quantifying the degree of capillary contact across fractures. Recently, methods have been
proposed to tackle the problem of block-to-block interaction. In all cases, carbonate reservoirs
require a considerable amount of core studies and frequent use of the scanning electron microscope
and its auxiliary equipment.
2.1 Rock Model
The topography.
It can be clearly seen from the 3D structure diagram that the entire oil reservoir has an
anticline-like structure with a middle height and a low circumference, and there are obvious faults
at the edges of the reservoir, which brings a lot of water injection outside the sides seen in Fig. 2.
This is a difficulty, so it has also affected the well deployment plan of the oil field as can be seen
in well completions.

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Fig. 2 Topography of the oilfield
The permeability
The permeability distribution in I, J and K directions is non uniform. The permeability for
the I and J directions were directly imported from the log data while the permeability for K
directions equals PermI*0.1.
Fig. 3 Permeability distribution in I, J, K directions
The porosity
The porosity across all the layers of this reservoir is also non uniform. The porosity data
were directly imported from the log data.
2.2 Property Model
The density of oil in this base case model is 800kg/m3 and the density of water is
995.5kg/m3, different fluid selection oil-water viscosity ratio. The oil-water viscosity ratio is 5:1,
and the fluid's PVT relationship is shown in Table 1.

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Table 1 PVT relationship table
P Rs Bo Eg VIso VIsg
101.325 0.444056 1.02676 0.898403 50.081 0.011531
694.57 1.76369 1.02929 6.24003 45.3875 0.011609
1287.82 3.29919 1.03225 11.7247 40.7872 0.011714
1881.06 4.97125 1.03551 17.3572 36.6053 0.011836
2474.31 6.74642 1.039 23.1422 32.9014 0.011975
3067.55 8.60552 1.04269 29.0835 29.6562 0.012129
3660.8 10.536 1.04655 35.1847 26.8243 0.012299
4254.04 12.5288 1.05058 41.4479 24.3543 0.012483
4847.29 14.5771 1.05476 47.8745 22.1968 0.012683
5440.53 16.6757 1.05909 54.464 20.3075 0.012899
6033.78 18.8203 1.06354 61.2141 18.6476 0.013131
6627.02 21.0074 1.06812 68.12 17.1841 0.013381
7220.27 23.2339 1.07283 75.1745 15.8891 0.013647
7813.51 25.4973 1.07765 82.3672 14.7387 0.013931
8406.76 27.7954 1.08259 89.6845 13.7131 0.014232
9000 30.1264 1.08763 97.1096 12.7953 0.014552
14200 51.7457 1.13612 163.106 7.70303 0.018035
19400 75.0632 1.19132 220.187 5.26865 0.022145
24600 99.6989 1.25234 263.328 3.90838 0.026113
29800 125.424 1.31856 295.39 3.06324 0.029653
35000 152.084 1.38951 319.94 2.49698 0.032766
The viscosity-pressure curve and the dissolved gas-oil ratio-pressure relationship curve of
the fluid is respectively drawn as shown in Fig.4 and Fig.5.
Fig. 4 Viscosity curve

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Fig. 5 Dissolved gas oil ratio-pressure relationship curve
2.3 Fluid Model
The relative permeability data of oil and water under reservoir conditions and the relative
permeability data of oil and gas are shown in Table 2 and 3, respectively, and thus the relative
permeability curve of oil, water and oil and gas under reservoir conditions is shown in Fig.6 and
Fig.7.
Table 2 The relative permeability data of oil and water
sw krw krow
0.2 0 0.2
0.225 0.003125 0.154495
0.25 0.0125 0.117236
0.275 0.028125 0.087161
0.3 0.05 0.063281
0.325 0.078125 0.044681
0.35 0.1125 0.030518
0.375 0.153125 0.020023
0.4 0.2 0.0125
0.425 0.253125 0.007327
0.45 0.3125 0.003955
0.475 0.378125 0.001907
0.5 0.45 0.000781
0.525 0.528125 0.000247
0.55 0.6125 4.88E-05
0.575 0.703125 3.05E-06
0.6 0.8 0

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Table 3 The relative permeability data of oil and gas
sl krg krog
0.4 0.8 0
0.434375 0.617981 3.05E-06
0.46875 0.468945 4.88E-05
0.503125 0.348645 0.000247
0.5375 0.253125 0.000781
0.571875 0.178723 0.001907
0.60625 0.12207 0.003955
0.640625 0.08009 0.007327
0.675 0.05 0.0125
0.709375 0.029309 0.020023
0.74375 0.01582 0.030518
0.778125 0.007629 0.044681
0.8125 0.003125 0.063281
0.846875 0.000989 0.087161
0.88125 0.000195 0.117236
0.915625 1.22E-05 0.154495
0.95 0 0.2
Fig. 6 The relative permeability curve of oil, water and oil

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Fig. 7 The relative permeability curve of oil, water and gas
Fig. 8 Relative permeability curve of oil, water and gas under reservoir conditions
2.4 Initial Conditions
The initial conditions in this model involves setting up the number of phases in the model,
values of the reference pressure, reference depth, and water oil contact point.
The number of phases= Water and Oil
Reference pressure (REFPRE)= 20000 kPa
Reference Depth (REFDEP)= 1605 m
Water-Oil contact (DWOC)= 1750 m
Constant Bubble point pressure, PB= 9000 kPa

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2.5 Well Completion and Production Forecast
In this whole reservoir domains, this reservoir model rends 35000 grid blocks: 1750 interior
view blocks and 1750 exterior faces. The grid structure of this numerical reservoir model on
Cartesian form is 50×35×20=35000 blocks with pinch out thickness of 0.0002ft. There are 11
producing wells in total.
Fig. 9 Planar grid structure
Fig. 10 Grid structure showing the 11 production wells location
2.5.1 Validating and running data file using IMEX
Start the CMG Launcher by using the icon on your desktop, or by going through the Start
menu and selecting Programs/CMG/Launcher. After building a base model with the following
properties; the permeability in IJ is directly imported and in the K-direction is equal to Kv/Kh ratio

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of 0.1, rock compressibility of 7.25E-6 1/kPa, reference pressure of 20,000 kPa, the base file is then
saved as IMEX_TUTORIAL.DAT.
After filling in all the data set required for building this base model, we will then click
validate with IMEX to run it. You will be able to make prediction runs without having to rerun the
historical data portion as a result of using the Restart Run feature.
2.5.2 Adding and creating historical production data
We can then go to the main Builder menu and select Well then Import Production/Injection
Data (this is the wizard to import production/injection data into the well & recurrent data for the
simulator and it also defines the status of each well and then create field history data file fhf.file
and save it as IMEX_PRODUCTION_HISTORY.fhf.
2.5.3 Results of production forecasting
By dragging and dropping IMEX_TUTORIAL.irf onto the Results Graph icon in the
launcher, we can be able to plot our production curves. In addition, by selecting the menu item File;
then Open Field History and selecting the IMEX_PROD_HISTORY .fhf file that we created in the
Creating Field Production History section of the tutorial. Click on the Open button.
Fig. 11 Simulated Production data variation with historical data for wel1

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In the same way, plot pressure distribution data for the base model. From the File, select
Open Field History, then browse for the file IMEX_RESERVOIR_PRESSURE_HISTORY.fhf
under your REQUIRED DATA folder. This file contains the historical data and will be used to
compare it with the simulated data.
Fig. 12 Simulated pressure data variation with historical data for wel1
In this plot, we can see a huge variation between our simulation model and field history
data, therefore in order to proceed with prediction, we need to perform history matching.
Chapter 3 History Matching
The history matching in this course exercise is done by changing Rock Compressibility to
Match Pressure Behavior of the field.
3.1 History Matching Process
3.1.1 Changing rock compressibility
In order to match the reservoir pressure, we can change the rock compressibility, as this is
one of the parameters that have an important effect. In the list below there is a selection of values
that can be used to approximate the simulation results to the real data values. By reducing the value
of rock compressibility, the reservoir pressure will decrease. Use the values listed in Table 4 to
create one data set per value:
Table 4 Different values of rock compressibilities
Rock Compressibility Data set
Cr=20e-06 1/psi (2.9e-06 1/kPa) IMEX_TUTORIAL_HM_CR1.DAT
We then open the IMEX TUTORIAL.DAT file in Builder, go to the Reservoir Section.
Double click on Rock Compressibility and input the value of compressibility of 2.9e-06 1/kPa (20e-
06 1/psi). Save the file as IMEX_TUTORIAL_HM_CR1.DAT under your HISTORY MATCH

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folder and run this simulation repeated for all the three different data sets and select the data set
with lowest possible error.
Fig. 13 Simulated production model vs. historical production data
As it can be observed from Fig.13, the only parameter that improved in relation to the real
data trend was the water cut, but for the rest of parameters the effect was minimal. The next step is
to change the relative permeability curves in order to improve the production.
3.1.2 Adjusting relative permeability curve to match production data
We can then change Relative Permeability Curves to Match Production. History Matching
is a technique that takes a long time to get a perfect match. It is an iterative process and it is not
expected that a perfect match will be obtained in the course. Therefore, the best possible match you
will obtain in the limited time will be considered as acceptable. It is advisable to try changing the
relative permeability perms and updating Results Graph in order to observe the difference that was
made.
Open the IMEX_TUTORIAL_HM_CR3.DAT file in Builder and save the file as
IMEX_TUTORIAL_HM_CR3_KRS.DAT. Go to the Rock Fluid section and double click on Rock
Fluid Types, click on the Tools button and select Generate Tables Using Correlations. Change the

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value of the end point for the Oil curve, KROCW and KROGCG from 0.2 to 0.4, and apply the
changes made.
Fig. 14 Effect of relative permeability curves on oil production for wl1
Due to limited time, final history matched data IMEX_TUTORIAL_HM_CR3_KRS.DAT
was then selected and saved as (IMEX_TUTORIAL_HM_MATCHED.DAT), as being best HM
model. We will now proceed with predictions under different scenario.
Chapter 4 Development Strategies
As previously observed from the historical data, the oil production is declining through the
time as a result of lack of pressure support in the reservoir. In order to provide extra support into
the reservoir, the injection of fluids will be performed by converting some producer wells into
injectors.
For this reservoir engineering course design exercise, base case and another scenario of
water injection will be considered and the results will be compared to quantify the benefit in terms
of the recovery factor with base case scenario.

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4.1 ResidualOil Distribution and DevelopmentSuggestions
4.1.1 Base case scenario
In this scenario, consideration is made on the prediction under primary depletion with the
same number of production wells and constraints based on the stage of history. This scenario will
be used as a reference to compare the effect of additional predictions under secondary recovery and
in this exercise will be water injection/flooding and the distribution of residual oil for possible
1.Open history matched file using Builder (IMEX_TUTORIAL_HM_MATCHED.DAT).
2. Save the file IMEX_TUTORIAL_PRED_BASE.DAT in the Prediction folder.
We will then run this base file with new simulation dates of up to January 1st, 2020. And as
well setting two new well constraints: Well Bottom Hole Pressure BHP as a main constraint (200
KPa), MONITOR as a second constraint to prevent unnecessary results when the well is producing
below the limit of 3 m3 /day of oil production.
Go to the CMG launcher and open the IMEX_TUTORIAL_HM_MATCHED.irf by
dragging and dropping the file onto the Results Graph icon. Plot the property of Well Bottom-hole
Pressure for all the 11 producing wells.
Fig. 15 Base scenario prediction results

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Fig. 16 Field production results for the base case
4.1.2 Distribution of residual oil
Observations of the pressure behavior within a time period show evidence that this parameter
declines by more than 60% of its original value. Since pressure represents the main source of energy for
production wells, the decline of pressure and oil production reduction are related. Therefore, we need to
provide extra support in the reservoir in order to increase the reservoir pressure and hence oil production in
the wells.
Results 3D/Graph was then used to display different properties that can be useful to take
decisions for the stage of prediction.

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Fig. 17 A cross section of wl16 showing water saturation at the end of history
Based on the position of the water oil contact, one of the candidate wells for conversion
from the producer to the injector is wl16. For more analysis you can go back to the Results Graph
and see the property of Water Cut per well in order to have an idea of the amount of water produced
by this well. It can be seen this well producers more water, so using as injection well will make its
produced act as an oil drive mechanism.
The criteria for selection of the second candidate for injection well will be based on those
with less oil production rates and location. The base case results indicate that one of the wells with
less oil production is wl5; additionally, this well is located on the other side of the reservoir, which
can be an advantage from the pressure distribution perspective.
4.2 Optimization Scenario
A Case Study of Water flooding (WF)
Conversion of Producer Wells into Water Injectors.
In a simulation we are unable to switch the same well from production to injection and vice
versa. However, in order to mimic this change, we need to create a new well in the same location
with the same trajectory, perforations and characteristics but with the opposite functionality, in
other words, if the original well is a producer the new well should be an injector. We will then convert
wl16 and wl5 into injector wells.
Setting constraints for the new injection wells.

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We will rename wel16 and wl5 as wl16_inj and wl5_inj and set new constraints as OPERATE,
BHP MAX=20,000Kpa, CONTREPEAT. By creating wl16_inj and wl5_inj as a group of injectors,
and setting their constraints GTARGET=4000m3. Then by applying the above changes, then run
the simulation to obtain production results.
Results of Water Flooding
A production curve of water injection model is then plotted and compared with the
production curve of the primary production.
Fig. 18 Comparison between base and water injection case
In this case, oil and gas production has significantly increased compared to primary
production method. And, the water cut slightly increases to about 11% then dropped to about 7%
as seen in Fig.18. Considering the amount of water injection rates per day, this is significantly an
acceptable value of water production from the wells as a result of this water flooding strategy.

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Fig. 19 Comparison between base and water flooding case
It can be observed from Fig.19 production curves, that converting two wl16 and wl5
increased recovery factor, from 12.0 % to about 16% of the original in place (OOIP).
For reservoir pressure distribution in the two cases: we can then plot the average pressure
distribution for both the base case and that of water flooding.

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Fig. 20 Comparison between production curves of both base and water injection cases
It can be observed from Fig.20 that water flooding improved the pressure distribution inside
the formation which is significant in contributing to the drive of oil from formation to the ground
surface through the well bore.
Chapter 5 Conclusions
Through this reservoir engineering course design exercise, it has been realized that
waterflooding is an effective method to achieve efficient oil displacement and waterflooding
represents the most reliable and economic oil recovery technique. The main components of water
flood projects are water source, injection water treatment, injection wells, reservoir, production
wells, processing of production streams, and water disposal; although each of which present a
challenge on its own.
In this work, a brief objective and methodology of water flooding in enhancing oil recovery
factor of producing wells is discussed into detail. Then a black oil model was created, history
matched with the field data and then a water injection field development strategy was then studied
and modelled. The results of the two cases then compared and the appropriate development method
is proposed.

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During primary production, the results showed that although the oil daily output is not high
enough though it maintained stable production, and the moisture content is also maintained at an
acceptable level. However, this recovery rate was still unsatisfactory, and there was still much room
and need for improvement thus bringing in the idea of water injection.
From the oilfield production curve of the water injection plan, it can be seen that the oilfield
maintained stable production. Although the water production rose relatively steadily but with
relatively low water cuts scenario, the oil production then maintained a stable production rate,
extending the life of the oilfield. The effect and benefit of water injection can be seen to outweigh
that of primary production.
For this case study, water injection is preferred and recommended over primary production
but other methods of enhanced oil recovery such as gas injection, addition of extra horizontal well,
polymer or surfactant flooding can be considered for future maximization of oil production from
this field.
References
1. Li, J., et al. Optimizing water flood performance toimprove injector efficiency in fractured low-
permeability reservoirs using streamline simulation. in SPE Kingdom of Saudi Arabia Annual
Technical Symposium and Exhibition. 2016. OnePetro.
2. Liu, F., C. Guthrie, and D. Shipley. Optimizing water injection rates for a water-flooding field.
in SPE annual technical conference and exhibition. 2012. OnePetro.
3. Ibiso, K., E.O. Emmanuel, and G.C. Nmegbu, Accepted and Published Manuscript.
4. van den Hoek, P.J., et al., Optimizing recovery for waterflooding under dynamic induced
fracturing conditions. 2009. 12(05): p. 671-682.
5. Vittoratos, E., et al., Optimizing heavy oil waterflooding: are the light oil paradigms
applicable? 2006.
6. Azamipour, V., et al., An efficient workflow for production allocation during water flooding.
2017. 139(3).
7. Imuokhuede, P.I., I. Ohenhen, and O.A. Olafuyi. Screening Criteria for Waterflood Projects in
Matured Reservoirs: Case Study of a Niger Delta Reservoir. in SPE Nigeria Annual
International Conference and Exhibition. 2020. OnePetro.
8. Asadollahi, M. and G. Naevdal. Waterflooding optimization using gradient based methods. in
SPE/EAGEReservoir Characterization & Simulation Conference. 2009. European Association

20
of Geoscientists & Engineers.
9. van Essen, G., et al., Robust waterflooding optimization of multiple geological scenarios. 2009.
14(01): p. 202-210.
10. Capolei, A., et al., Waterflooding optimization in uncertain geological scenarios. 2013. 17(6):
p. 991-1013.

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APPENDIX: GROUP MEMBERS
Group Title Name Student No.
Water
Flooding

Optimizing Water Flooding Recovery

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