Enhanced Oil Recovery by Water Alternating Gas (WAG) Injection

Enhanced Oil Recovery by
Water Alternating Gas (WAG)
Injection: The Opportunity and
the Challenge
Centre for Enhanced Oil Recovery & CO2
Solutions
Characterisation of Three Phase Flow and
Water Alternating Gas (WAG) Injection
Studies JIP
Institute of Petroleum Engineering,
Heriot-Watt University, Edinburgh
Scotland, UK
Contact:
Prof. Mehran Sohrabi
Telephone: +44 (0)131 451 3568
Email: [email protected]
Sohrabi M., Fatemi M., Ireland S.
Presented by: Mobeen Fatemi
06 May 2014
North-Sea WAG Injection Potential
MGI
31%
SWAG
5%
FAWAG
11%
WAG
48%
MEOR
5%
Distribution of EOR field applications by method in the North Sea (total of 19
projects). (SPE 99546; 2006)
2
 WAG Injection
O
W
3
 WAG Injection
G
O
W
4
 WAG Injection
WAG involves major
complexity and
hysteresis, caused by
injection alternation
that happens during
process.
G+O
G+W+O
O
W+ O
5
WAG Injection

WAG involves major complexity and hysteresis, caused by
alternating injection that happens during process.Therefore,
numerical simulation of WAG injection becomes extremely
complex (involves the 2-phase and 3-phase Pc and kr and also
their hysteresis behavior).

Our current understanding of the physics (and sometime
chemistry) involved in three-phase flow is currently limited
and hence quantifying and predicting the outcome of these
processes are difficult.
6
WAG Injection
 Measuring 3-phase kr is very difficult and time consuming
hence many correlations have been proposed for calculating
3-phase kr from the more readily available 2-phase data
Note: These models are usually based on water-wet systems and high
IFT gas/oil.
7
WAG Injection
 Formulation available in the existing reservoir simulators are
not capable of adequately account for the complex interplay
of hysteresis, capillary pressure, wettability, IFT, trapped
phase saturation and their impact on flow under three-phase
flow regime.
8
Reliability of Reservoir Performance Prediction

Water Flood

Gas injection

Alternating slugs of gas and water (WAG)?

Sequence of gas and water injection?

Simultaneous injection of water and gas (SWAG)?

Wettability?

Interfacial Tension (gas type)?

Rock type?

Rock Permeability?

Miscibility?

Trapped phase saturation and hysteresis?
9
06/05/2014
10
06/05/2014
10
JIP at Heriot-Watt University: Research Approach
 To experimentally study parameters and understand mechanisms
involved in GF, WAG and SWAG injections.
 To generate 2-phase and 3-phase relative permeability curves using
the results of the coreflood experiments.
 Evaluate existing 3-phase models
 Develop improved methodologies for obtaining 3-phase kr and
hysteresis for reliable numerical simulation of WAG injection.
11
Experimental Condition
 Different injection scenarios
WAG, SWAG
Continuous Gas
Continues Water
 Different IFT values
High IFT (immiscible)
Low IFT (intermediate)
Very low IFT (near-miscible)
 Different wettability conditions
Water-Wet, Oil-Wet & Mixed-Wet
 Different Core Samples
Carbonates, Sandstones
12
Micromodel Experiments
 This research programme was first launched on November
1997 with main aim of understanding the process of WAG
injection. The scope of work was later extended to threePhase flow (including WAG).
Inlet
Outlet
Cover plate
Two-dimensional etched pore structure
13
Core Flood Experiments
Injection
Production
Core properties
Core
Length
/ cm
Diameter
/ cm
Porosity
/ frac.
Permeability
/ mD
Core 1
67.0
4.98
0.17
1000
Core 2
60.5
5.08
0.19
64
Fluid properties
Pressure
/psia
Temperatur
e
o
/C
Ρg
/kgm-3
ρL
/kgm-3
µg
/mPa.s
µL
/mPa.s
IFT
/mNm-1
1200
1790
1840
37.8
37.8
37.8
86.6
184.8
211.4
466
345
317
0.0141
0.0206
0.0249
0.0793
0.0474
0.0405
2.7
0.15
0.04
14
Effect of IFTo/g: (1000 mD, Gas Injection, Mixed-wet)
1.0
Oil Recovery (Core PV)
0.8
σ = 0.04
0.6
σ = 2.70
0.4
0.2
1000mD, GF, MW, 1825 psi
1000mD, GF, MW, 1200 psi
0.0
0
2
4
6
8
10
Injected Gas (Core PV)
15
Effect of IFTo/g: (65 mD, Gas Injection, Mixed-wet)
σ = 0.04
σ = 2.70
16
Performance of Different
Injection Scenarios
Mixed-Wet Rock (65mD vs. 1000 mD; σg/o = 0.04 mN.m-1)
1
WAG
Oil Recovery (Core PV)
Oil Recovery (frac. IOIP)
1
0.8
0.6
GF
0.4
WAG, MW, 65mD
Water Injection, MW, 65mD
0.2
SWAG (Qg/Qw=0.25), MW, 65mD
Gas Injection, MW, 65mD
0
0
2
4
6
8
Injected Fluids (Core PV)
65mD, Mixed-Wet
10
WAG
0.8
GF
0.6
0.4
WAG Injection, MW, 1000mD
Water Injection, MW, 1000mD
0.2
SWAG (Qg/Qw = 0.25), MW, 1000mD
Gas Injection, MW, 1000mD
0
0
2
4
6
8
Injected Fluids (Core PV)
1000mD, Mixed-Wet
17
Effect of Injection Scenario on
Injectivity
Mixed-Wet Rock (65mD Vs. 1000 mD; σg/o = 0.04 mN.m-1)
100
25
SWAG (Qg/Qw=1), MW, 65mD
WAG, 65mD, MW, IDIDID
Water Injection, MW, 65mD
Gas Injection, MW, 65mD
60
20
Pressure Drop (psi)
Pressure Drop (psi)
80
SWAG, MW, 1000mD
WAG, MW, 1000mD
Water Injection, MW, 1000mD
Gas Injection, MW, 1000mD
40
20
0
15
10
5
0
0
2
4
6
8
Injected Fluids (Core PV)
65mD, Mixed-Wet
10
0
2
4
6
8
Injected Fluids (Core PV)
1000mD, Mixed-Wet
18
Effect of Gas/Oil IFT on WAG
G W G W G W G W
Sw,im=18% , Soi=82%
O
0.9
65 mD
WAG-IDIDIDID
Mixed-wet
Produced Oil (frac. Sorw)
0.8
σ = 0.04
0.7
0.6
0.5
0.4
WAG-IDIDIDID, 65mD, MW, 1840 psia
WAG-IDIDIDID, 65mD, MW, 1790 psia
0.3
WAG-IDIDIDID, 65mD, MW, 1215 psia
0.2
σ = 0.15
0.1
σ = 2.70
0
0
2.5
5
7.5
10
12.5
Injected WAG (Core PV)
19
Effect of IFTOil/Gas on Injectivity
σ = 0.04
σ = 2.70
W1
W2
W1
W3
W2
W3
100
W1
σ = 0.15
W2
Injectivity (cc/psi)
W3
10
W1
1
W2
W3
0.1
0
0.5
1
1.5
2
2.5
3
Injected Brine (Core PV)
20
A unique set experimental data
One of the major achievements of this research is a
growing set of core flood data covering a wide range
of pertinent parameters (IFT, Wettability, Hysteresis,
K, Rock Type, etc) investigating various injection
strategies.
As far as we know, no such comprehensive data is
available in published literature.
21
Three-phase kr Determination
Measuring 3-phase kr is very difficult and time
consuming hence many correlations have been
proposed for calculating 3-phase kr from the more
readily available 2-phase data.
2Ph Oil & Gas
2Ph Oil & Water
1.0
0.8
k rog
0.6
+
k rg
0.4
0.2
k ro
k row
0.01
0.6
0.4
k rw
0.0
0.0
0.2
0.4
Sg
0.6
0.8
1.0
0.0
0.2
0.4
0.6
Sw
0.80
Sw
0.2
0.0
r
S g =1
1.0
0.8
kr
3Ph Oil k
0.8
1.0
Use 2Ph
and 2Ph
So
k rg in 3Ph
k rw in 3Ph
22
22
Evaluation of 3-phase kr Modells
Unsteady state 2-phase test
Fluid injection
Swir =18%, k=65 mD
2-phase kr
WAG experiment
Fluid injection
Swir =18%, k=65 mD
Simulation of WAG
test using 3-phase kr
models
Comparing experiment and simulation results e.g.
recovery and pressure representing the accuracy
of that particular 3-phase kr model.
23
23
Numerical Simulation of WAG (Mixed-Wet)
0.2
0.2
0.18
EXPERIMENT
0.18
0.16
EXPERIMENT
EXPERIMENT
EXPERIMENT
EXPERIMENT
STONE1
EXPERIMENT
STONE1
STONE1
EXPERIMENT
STONE2
STONE2
STONE2
STONE2
STONE2
0.16
0.12
0.1
0.08
0.14
Oil Recovery, PV
Oil Recovery, PV
0.14
0.12
0.1
SWI
EXPERIMENT
SWI
0.08
SWI
SWI BAKER1
BAKER1
BAKER1
BAKER1
BAKER2
BAKER2
BAKER2
BAKER2
BAKER2
BAKER2
BAKER2
LARSEN
0.06
0.06
0.04
0.04
0.02
LARSEN
0
0.02
0
2
4
PVinj
6
8
STONE-EXPONENT
0
0
2
4
PVinj
6
8
24
Existing three-phase kr models lead to large errors
in prediction of WAG performance.
What is the actual 3-phase kr during WAG
?
2525
Direct 3-phase kr - 3RPSim
Another major achievement of the project is development
of a software for obtaining three-phase kr and Pc.
3-phase kr can be obtained directly instead of indirectly from
2-phase.
kro =kro (Sw, Sg)
krw =krw (So, Sg)
Water
Gas
Water
Oil
Gas
Oil
 krg =krg (Sw, So)
26
Determination of 3-phase kr by
history matching experimental
results:
injection
core
using our in-house simulator
(3RPSim) to estimate 3-phase
kr values by history matching
experimental
results
e.g.
recovery and pressure
27
Numerical Simulation of WAG (Mixed-Wet)
0.2
0.18
EXPERIMENT
0.2
0.16
0.18
STONE1
EXPERIMENT
EXPERIMENT
EXPERIMENT
EXPERIMENT
EXPERIMENT
EXPERIMENT
STONE1
STONE2
STONE1
STONE1
EXPERIMENT
STONE2
STONE2
SWI
STONE2
STONE2
STONE2
SWI
EXPERIMENT
BAKER1
SWI
BAKER1
SWI
SWI
BAKER1
BAKER2
BAKER2
BAKER1
BAKER1
BAKER2
BAKER2
LARSEN
BAKER2 LARSEN
BAKER2
BAKER2
BAKER2
LARSEN
STONE-EXPONENT
0.16
0.14
0.12
Oil Recovery, PV
Oil Recovery, PV
0.14
0.1
0.08
0.06
0.12
0.1
0.08
0.06
0.04
0.02
0.04
STONE-EXPONENT
0
0
0.02
2
4
PVinj
6
8
Heriot-Watt
Simulator
0
0
2
4
PVinj
6
8
28
New Hysteresis model
three-phase pore occupancy
kri3Ph  f   krij krjk  krik krkj 
Saturation function
accounting cyclic
Hyst
f 
Si
(1  S j )(1  Sk )
Two-phase kr
Required two-phase data for running this model
1. Oil/water : krow
2. Oil/gas :
krog
SPE #152218. Three-Phase Relative Permeability
3. Gas/water : krgw, krwg
and Hysteresis Model for Simulation of Water
Alternating Gas (WAG) Injection. Mehran
Sohrabi
29
Three-Phase Flow JIP at Heriot-Watt University
Core-flood Experiment
Micromodel Experiment
Mechanisms of Flow
Examining different
injection Scenario
Mechanisms of Flow
Generating kr and Pc
data
Analyse experimental
data
Evaluate capability of existing simulators and models
Three-Phase kr
Three-Phase Pc
Hysteresis
Trapped
saturation
IFT scaling
Viscous
fingering
Modelling
Deliverable
New improved mathematical
model for calculating flow
parameters (kr , Pc , trap
phase, hysteresis..)
High quality measured data
for different rock and fluid
conditions (kr & Pc)
In-house Software
(3RPSim)
methodologies to correct the SCAL
data due to experimental artefact
(viscous fingering, end-Effects)
30
Project’s Sponsors
31
32

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