Simulation of Carbonated Water Injection (CWI), Challenges ... · PDF fileDEVEX 2014 -...
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DEVEX 2014 - Aberdeen
Simulation of Carbonated Water Injection
(CWI), Challenges and Solution
Foroozesh J., Jamiolahmady M. (Jami) , Sohrabi M.
Presented by: Jalal Foroozesh
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Outline
• Introduction
• Objectives
• Our modelling approach
• Governing equations.
• GA optimisation tool.
• Experimental conditions.
• Simulation results and discussions
• Summary and conclusions
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Introduction - 1
• CWI is an augmented water injection (WI) process
with great EOR potentials.
• During CWI, CO2 is transferred from water into oil
due to its higher CO2 solubility, resulting in higher
oil recovery.
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Carbonated Water
(CO2 + Water)Oil
CO2
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Introduction - 2
• CWI can be used when limited source of CO2 isavailable.
• CO2 is in solution rather than free, so less risk of earlygas breakthrough (EOR aspect).
• A good technique for safe CO2 storage with less risk ofleakage (Environmental aspect).
• Compared to experimental investigation of the subject,mathematical modelling of CWI has received lessattention.
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Introduction - 3
• Viscosity reduction, oil swelling and
wettability alteration are among the main
mechanisms giving more oil recovery during
CWI.
• It is believed that compositional simulation of
the process better captures the process.
• Current compositional reservoir simulators are
based on instantaneous equilibrium assumption.
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Introduction - 4
• Our experimental studies have shown that CO2
transfer from water to oil is a slow and non-
equilibrium based process during CWI.
• Therefore this multi-physics (fluid flow and
mass transfer) process can not be simulated
realistically using available simulators.
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Objectives
• Mathematical modelling/numerical simulation
of CWI Process.
• Develop a compositional simulator that captures
CWI multi-physics process realistically.
• The simulator needs to be based on non-
equilibrium conditions by capturing the kinetics of
mass transfer.
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Governing Equations
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𝝋𝝏(𝝆𝒐𝒔𝒐𝝎𝒐
𝒐)
𝝏𝒕= −𝜵 𝝆𝒐𝒖𝒐𝝎𝒐
𝒐 𝟏 𝝋𝝏 𝝆𝒐𝒔𝒐𝝎𝒐
𝒄𝒐𝟐
𝝏𝒕= −𝜵 𝝆𝒐𝒖𝒐𝝎𝒐
𝒄𝒐𝟐 + 𝑼 (𝟐)
𝝋𝝏(𝝆𝒘𝒔𝒘𝝎𝒘
𝒘)
𝝏𝒕= −𝜵 𝝆𝒘𝒖𝒘𝝎𝒘
𝒘 𝟑 𝝋𝝏(𝝆𝒘𝒔𝒘𝝎𝒘
𝒄𝒐𝟐)
𝝏𝒕= −𝜵 𝝆𝒘𝒖𝒘𝝎𝒘
𝒄𝒐𝟐 − 𝑼 𝟒
• Mass transfer term (U=f(concentration, overall mass transfer coefficient, Sw))controls the amount and the rate of CO2 transfer from water to oil phase.
• Equations are solved for P, sw, 𝑤𝑤𝑐𝑜2, 𝑤𝑜
𝑐𝑜2.
• Fully implicit method was used to solve the coupled equations.
• Viscosity and density change due to CO2 transfer between oil and water phases.
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Genetic Algorithm (GA)
• Mass transfer coefficient (MTC) and Kr wereunknown in our CWI simulation.
• In our approach these unknown parameters aredetermined by history matching the TOP and DPexperimental data.
• To achieve this, a GA based optimization programwas developed that could be linked to oursimulator.
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Core Flooding Experimental Conditions
• Water-wet ( WI and CWI )
• Mixed-Wet ( WI and CWI )
• Decane with well defined properties used as
oil in these tests conducted at 2500 psi.
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Water + Decane + CO2fully saturated with Decane
(Swi=0)
CW
q=20 cc/hr
Clashach Core:
WW: k=850 mD, PV=120 cc
MW: k=1 D, PV=180 cc
CW CO2 content=5%
CW-C10, Partition coefficient=3-4
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DEVEX 2014 - Aberdeen
Simulations Results and Discussions
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In-house Simulator - Consistency Check
• Water injection (WI) was simulated first usingour simulator under its black oil mode.
• A Kro-w curve that simulates the WI test wasobtained by history matching of thecorresponding production data using GA.
• Results of our simulator were compared tothose of E100 demonstrating good agreement.
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Water-Wet Core - 1
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WI and CWI WI
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Water-Wet Core - 2
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Tuned MTC value of 1.5 E-5 with oil-water Kr.
0
10
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30
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50
60
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80
90
100
0 5 10 15 20
TO
P(c
c)
Time(hr)
Exp
Model
CWI
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Mixed-Wet Core - 1
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Mixed-Wet Core - 2
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Summary and Conclusions - 1
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• A compositional based simulator has been developed.
• The simulator is based on non-equilibrium assumption and
captures the kinetics of CO2 transfer.
• A Genetic Algorithm (GA) based optimization program has
been developed.
• Kr and MTC can be tuned by GA.
• WI or CWI core flood tests of water-wet and mixed-wet cores
when they were fully saturated with Decane were simulated.
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DEVEX 2014 - Aberdeen
Summary and Conclusions - 2
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• WI tests were simulated first and later the results were used for
the simulation of the corresponding CWI tests.
• For water-wet cores, water-oil kr curve obtained was used and
only MTC was tuned to match CWI production data.
• Main mechanism: Swelling.
• For mixed-wet cores, kr curve and MTC were tuned to match
CWI production data.
• Main mechanism: Wettability alteration and Swelling.
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Acknowledgement
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• The support of the following industrial partners acknowledged.
• The UK Department of Energy and Climate Change (DECC),
• Petrobras,
• Total Exploration and Production,
• ADCO,
• BG Group, and
• Galp Energia.
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Thank you for your attentions
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