Omar El Khatib Teaching and Research Assistant Cairo ... Koval, E. J., (1963) Claridge, E. L., (1972) Paul, G. W. et al. (1984) Walsh, M. P. and Lake, L. W. (1988) Mollaei, A., (2011)

Omar El KhatibTeaching and Research Assistant

Cairo University

Under Supervision of:Prof. Dr. Mohamed Helmy SayyouhProf. Dr. El Sayed El TayebProf. Dr. Ahmed Hamdy El Banbi

OGUFDSESSION 17

Abstract ID: 635

Development of a Predictive Model for Miscible EOR Processes

Dedication

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Contents

1. Introduction & Background

2. Statement of the Problem

3. Objective

4. Model Development, Capabilities and Validation

5. Conclusions & Recommendations

6. Discussion

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• Enhanced Oil Recovery (EOR) technology is gaining anincreasing importance due to the present difficulties indiscovering new reservoirs and the increasing energy needs

• In 2010, EGPC (Egyptian General Petroleum Corporation) hasdeveloped a strategic plan to evaluate the residual reserve inEgyptian mature reservoirs to determine the applicability ofthe different EOR methods.

• In 2014, EGPC signed a corporation protocol with MSRC, CairoUniversity to develop an EOR Map for all the reservoirs.

Introduction & Background

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• In 2013, Cairo University Research Team developed a generalapplied research methodology to determine the most suitableEOR methods for any field.

• Predictive software package that is able to predict theperformance of different EOR methods is one of the toolsrequired for this methodology

• The software package includes the following EOR Methods:1. Chemical Flooding - Finished2. Miscible Flooding – In Progress3. Thermal Flooding – In Progress4. Unconventional EOR (Seismic) – In Progress


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1. Analogical methods

2. Experimental methods

3. Mathematical methods (Analytical – Empirical – Material

Balance – Decline Curve Analysis)

4. Predictive methods (A combination of modelling approaches)

5. Numerical methods (Reservoir Simulation)

Modelling Approaches


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1. Screening Guides (Initial indicator)

2. Predictive Models

3. Reservoir Simulation Software

Early Stage Studies for EOR Applications


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Early Stage Studies of EOR Applications

Screening Guides Predictive Models Reservoir Simulation

Advantages

• Simplest tool for applicability of EOR methods

• Consideration of reservoir and fluid properties and behavior

• Fast and simple prediction

• Most accurate method of reservoir performance

• Mixing and physics of fingers are considered

Disadvantages

• No consideration of any characteristic of fluids or the porous medium

• No indication of economic feasibility

• Assumptions made in their formulation

• Expensive and time consuming

• Lack of necessary data


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Miscible Predictive Models (Factors Affecting Miscible Displacement)

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Comparison

Items

Koval, E.

J., (1963)

Claridge,

E. L.,

(1972)

Paul, G.

W. et al.

(1984)

Walsh, M. P.

and Lake, L.

W. (1988)

Mollaei,

A.,

(2011)

Jain, L.,

(2013)

Heterogeneity √ √ √ N/A √ √

Viscous

fingering√ √ √ N/A √ √

Gravity

segregationN/A N/A √ N/A √ √

Loss of

miscibilityN/A N/A N/A N/A N/A N/A

Interference of

wavesN/A N/A N/A √ N/A √

Diffusion N/A N/A N/A N/A N/A N/A

Cross flow N/A N/A N/A N/A N/A N/A

Comparison

Items

Koval, E.

J.,

(1963)

Claridge,

E. L.,

(1972)

Paul, G.

W. et al.

(1984)

Walsh, M. P.

and Lake, L.

W. (1988)

Mollaei,

A.,

(2011)

Jain, L.,

(2013)

PatternLine

drive5-spot

Line drive

5 spotLine drive

Line

drive

Line

drive

Type of flow Diffuse Diffuse Diffuse Diffuse Segregat. Segreg.

Solvent type Any Any CO2 Any Any Any

Chase fluids N/A N/A N/A √ N/A N/A


Miscible Predictive Models (Injection Strategies)

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Statement of the Problem

As concluded from the literature survey, there is no model that

takes all factors, affecting EOR processes, into consideration.

In addition, commercial software covering this branch of models

are rare. Therefore, it is essential to develop a software package

that can quickly and effectively predict the performance of

different EOR methods by taking into consideration all the features

accompanying the process.

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Developing an effective screening

Tool

Developing predictive models for

EOR methods

Software package

Screening tool(Done)

Miscible model Thermal model Seismic model(In progress)

Chemical model (Done)

Pro

gre

ss B

ar

2015 2016 2017

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12

Miscible displacement

model

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Developing an effective screening

Tool

Developing predictive models for

EOR methods

Software package


13

Objective

The main target of the present work is to develop a rigorous

software package that can predict the performance of

miscible flooding without throwing away the advantages of

predictive models of fast calculations and easy use.

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Model Structure

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Model Capabilities

Injection Features

Pattern type Line Drive & 5-spot

Type of injection

(Continuous / WAG) & /

Chase Fluids with different injection strategies

Optimum WAG determination

Solvent type Any

Type of Reservoir

Stratification and heterogeneity

Stratified / Not stratified

Miscible Process Features

Effect of mobile water blocking

Considered / Not Considered

Effect of phase behavior

Considered / Not Considered

Viscous fingering Considered / Not Considered

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Model Approach

Recovery Factor = 𝐸𝑑𝑖𝑠𝑝𝑙𝑎𝑐𝑒𝑚𝑒𝑛𝑡 ∗ 𝐸𝑎𝑟𝑒𝑎𝑙 ∗ 𝐸𝑣𝑒𝑟𝑡𝑖𝑐𝑎𝑙

Fractional Flow Theory (Graphical)

Areal Sweep Models

Layered Calculations

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𝜕𝑆𝑤𝜕𝑡𝐷

+𝜕𝑓𝑤𝜕𝑆𝑤

∗𝜕𝑆𝑤𝜕𝑥𝐷

= 0

1. Aqueous phase mass conservation equation:

2. Oleic phase mass conservation equation:

𝜕(𝐶𝑠𝑜𝑆𝑜)

𝜕𝑡𝐷+

𝜕(𝐶𝑠𝑜𝑓𝑜)

𝜕(𝐶𝑠𝑜𝑆𝑜)∗𝜕(𝐶𝑠𝑜𝑆𝑜)

𝜕𝑥𝐷= 0

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Model Approach


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Model ApproachModel

Approach

Areal Sweep Efficiency

Mahaffey et al. Experimental model for 5-spot

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Model Approach

Vertical Sweep Efficiency

Vertical Sweep is considered by performing (Ed*EA) calculations on every layer and summing them up at the producer to reach the recovery efficiency

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Model Approach

Swept Zone

Non Swept Zone

Model Development

Assumptions

1. Isothermal porous medium 2. Independency of fluid properties on pressure3. Ideal mixing of fluids (Fluids don’t interact with the solid

phase)4. Negligible dispersion and diffusion 5. Presence of only oil and water at initial conditions6. Simultaneous injection of water with solvent or water with

chase fluid7. Two immiscible phases (aqueous and oleic)8. Full miscibility (First contact miscibility) of two components

(Solvent and oil) in the oleic phase

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Input Data

1. Relative permeability data

2. Fluid properties

3. Reservoir characteristics

4. Injection pattern provisions

5. Solvent specifications

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Model Development

Output Data

1. Oil production rate vs. time

2. Cumulative oil production vs. time

3. Water cut vs. time

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Model Development

Model Validation Cases

Input Data 1st Case 2nd Case

Type of injection Continuous injection Continuous injection

Pattern Line Drive 5-Spot

Injection rate (res bpd) 500 500Distance between producer & injector (ft)

4300 1320

Bo (res bbl/STB) 1.1 1.1Bw (res bbl/STB) 1 1Oil viscosity (cp) 1.5 1.5Water viscosity (cp) 1 1Solvent viscosity (cp) 0.3 0.3

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Input Data 1st Case 2nd CasePorosity (fraction) 0.18 0.18Pattern Area (ft2) 871200 871200

Swc 0.25 0.25Swi 0.25 0.25

Sorm 0.05 0.05Total thickness (ft) 20 20

Permeability insertion mode

Data points Data points

1st Case (Line Drive →M =5)

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0

50000

100000

150000

200000

250000

300000

350000

400000

450000

0 2000 4000 6000 8000

Cu

mu

lati

ve P

rod

uct

ion

, res

b

bl

Time, days

Walsh + Dyes - Program

Koval - Program

Eclipse

1st Case (Line Drive →M =5)

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0

100

200

300

400

500

600

0 2000 4000 6000 8000

Qo

, res

bp

d

Time, days

Walsh+Dyes - Program

Koval - Program

Eclipse

2nd Case (5-spot →M =5)

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0

50000

100000

150000

200000

250000

300000

350000

400000

450000

0 2000 4000 6000 8000

Cu

mu

lati

ve P

rod

uct

ion

, res

b

bl

Time, days

Walsh + Mahaffey - Program

Claridge - Program

Eclipse

2nd Case (5-spot →M =5)

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0

100

200

300

400

500

600

0 1000 2000 3000 4000 5000 6000 7000 8000

Qo

, res

bp

d

Time, days

Walsh +Mahaffey - Program

Claridge-Program

Eclipse


Input Data 3rd Case 4th Case

Type of injection Continuous injection Continuous injection

Pattern Line Drive 5-Spot

Injection rate (res bpd) 500 500Distance between producer & injector (ft)

4300 1320

Bo (res bbl/STB) 1.1 1.1Bw (res bbl/STB) 1 1Oil viscosity (cp) 1.5 1.5Water viscosity (cp) 1 1Solvent viscosity (cp) 0.06 0.06

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3rd Case (Line Drive →M =25)

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0

50000

100000

150000

200000

250000

300000

350000

400000

450000

0 5000 10000 15000 20000

Cu

mu

lati

ve P

rod

uct

ion

, res

bb

l

Time, days

Koval - Program

Eclipse

Walsh + Dyes - Program

3rd Case (Line Drive →M =25)

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0

100

200

300

400

500

600

0 1000 2000 3000 4000

Qo

, res

bp

d

Time, days

Koval

Eclipse

Walsh + Dyes - Program -

4th Case (5-spot →M =25)

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0

50000

100000

150000

200000

250000

300000

350000

400000

450000

0 1000 2000 3000 4000 5000 6000 7000 8000

Cu

mu

lati

ve P

rod

uct

ion

, res

bb

l

Time,days

Claridge - Program

Eclipse

Walsh +Mahaffy - Program -

4th Case (5-spot →M =25)

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0

100

200

300

400

500

600

0 2000 4000 6000 8000 10000

Qo

, res

bp

d

Time, days

Claridge - Program

Eclipse

Walsh+Mahaffey - Program


Layers 5th Case 6th Case

Oil viscosity (cp) 1.5 1.5Water viscosity (cp) 1 1Solvent viscosity (cp) 0.3 0.3

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Thickness Porosity Absolute Permeability20 0.18 1010 0.15 205 0.1 15

15 0.2 610 0.25 3

5th Case (Line Drive - Layered →M =5)

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0

200000

400000

600000

800000

1000000

1200000

1400000

0 5000 10000 15000 20000

Cu

mu

lati

ve O

il P

rod

uct

ion

, re

s b

bl

Time, days

Walsh+Dyes

Koval Layers only

Koval Vdp only

Eclipse

5th Case (Line Drive - Layered →M =5)

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0

200

400

600

800

1000

1200

0 500 1000 1500 2000 2500 3000 3500 4000

Qo

, res

bp

d

Time, days

Walsh+Dyes

Koval Layers only

Koval with Vdp only

Eclipse

6th Case (5 Spot – Layered →M =5)

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0

200000

400000

600000

800000

1000000

1200000

1400000

0 5000 10000 15000

Cu

mu

lati

ve P

rod

uct

ion

, res

b

bl

Time, days

Walsh + Mahaffey

Claridge

Claridge - no layering

Eclipse

6th Case (5 Spot – Layered →M =5)

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0

200

400

600

800

1000

1200

0 2000 4000 6000 8000

Qo

, res

bp

d

Time, days

Walsh + Mahaffey

Claridge

Claridge - no layering

Eclipse

Conclusions & Recommendations

1. A predictive model of miscible flooding has beenconstructed and validated against reservoir simulator(Eclipse)

2. The model accounts for different injection and chase fluidsstrategies and considers factors like waves interference andloss of miscibility near the wellbore of the producer

3. The graphical solution of fractional flow theory is used todetermine displacement efficiency

4. Mahaffey’s areal sweep model is used for determination ofareal sweep efficiency in 5 spot and Dyes for line drive

5. The developed model may be extended further to accountfor other heterogeneity effects other than stratification (i.edispersion) and gravity segregation

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THANK YOU

Omar El KhatibTeaching and Research Assistant

Cairo University

Documents

Omar El Khatib Teaching and Research Assistant Cairo ... Koval, E. J., (1963) Claridge, E. L., (1972) Paul, G. W. et al. (1984) Walsh, M. P. and Lake, L. W. (1988) Mollaei, A., (2011)