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SPE 89338
A Study of IOR by CO2 Injection in the Gullfaks Field, Offshore Norway
H. Agustsson, SPE, STATOIL ASA, G.H. Grinestaff, SPE, PETROTEL INC.
Copyright 2004, Society of Petroleum Engineers Inc.
This paper was prepared for presentation at the 2004 SPE/DOE Fourteenth Symposium on
Improved Oil Recovery held in Tulsa, Oklahoma, U.S.A., 17–21 April 2004.
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streamline-tracer model, scaling the MWAG process up to
field level. The streamline-tracer model interactively optimises
solvent allocation and generates production predictions on a
well-by-well basis. Water flood recovery and incremental IOR
are predicted simultaneously in a single simulation run.
In addition, the general economic limitations and example
technical solutions for implementation of a CO2 MWAG on
the Gullfaks Field are briefly described.
Abstract
This paper describes the feasibility study of a large-scale
miscible CO2-WAG (MWAG) injection scheme in the
Gullfaks Field, offshore Norway. We describe the reservoir
engineering workflow and simulation techniques, the predicted
production and injection profiles, and the main infrastructure
solutions under consideration.
Compositional cross-section models and recently available
streamline-tracer simulation techniques are employed to scale
up from element models to a fast, full-field simulator with a
high degree of flexibility.
Murchison
Gullfaks
Bergen
Shetland
Magnus
Norway
Stavanger
Gullfaks
North Sea
Great
Britain
Snorre
Statfjord
Denmark
Ninian
Veslefrikk
Figure 1: Gullfaks Field Location
The starting point for the workflow is a set of black oil and
streamline front tracking models, history matched on coarse
and fine grids. A fast, finely gridded streamline model is used
to identify the MWAG injection targets, define injection well
locations and completion strategy. Fine gridded cross-sections
are extracted and used in a compositional simulator to study
and quantify the miscible displacement process. These are the
used to derive scaling parameters used in a simple, ultra-fast
Figure 2: Gullfaks Reservoir Structure
Introduction to the Gullfaks Field
The Gullfaks field has been extensively documented in the
literature. For a recent overview of reservoir description and
management, refer to Agustsson, et al1. To summarise, the
field is located 180 km NE of Bergen, Norway, see Figure 1,
2
near the median line between the British and Norwegian
sectors of the North Sea. The Gullfaks is in a mature oil
province, neighbouring many large oil fields. Production is
from sandstones in the Brent Group and the underlying
Statfjord, Cook and Lunde formations. The Brent Group
represents the major part of the producing formations in
Gullfaks. It consists of Jurassic sands, with shallow marine to
fluvial deposits at around 1800m subsea.
Figure 3: Gullfaks Reserves Development
Reservoir quality is generally high to very high, with
porosity around 30-35%, and HCPV weighted average
horizontal permeability of the order of 800 mD. The reservoir
pressure and temperature are around 310 bar and 74OC
respectively, at datum (1850m TVD SS). The oil gravity is
between 32-36o API and the Brent GOR is around 100 v/v.
The reservoir is extensively layered and severely faulted; see
Figure 2, with numerous intercommunicating compartments.
Apart from the lateral segmentation, with the major N-S faults
mostly sealing, the Brent may be roughly divided into three
main hydraulic units vertically, referred to as Upper, Middle
and Lower Brent, nevertheless with a degree of vertical
communication.
Figure 4: Gullfaks Field Installations
SPE 89338
These units also communicate when juxtapositioned across the
many faults in the field. These aspects pose a challenge to both
modelling and managing the reservoir.
The field started production in 1986, and has as of July
2003 produced roughly 300 MSm3 of the currently estimated
reserves of 342 MSm3. In place reserves are around 582
MSm3. Figure 3 shows the development in reserves and
production from 1986 to date. The current production strategy
is through pressure maintenance at above saturation pressure
(230 bar in the Brent) by water injection, augmented by gas
injection and a modest natural water influx. The plans
envisage continued production to 2020, with an overall
recovery factor of 58%.
The field installations are shown in Figure 4. Production is
to three large gravity-base concrete platforms, each with
processing and water injection capabilities, and two with gas
injection facilities. Gas export is by pipeline to shore and the
stabilised oil is stored in tanks and exported by tanker. Third
party processing of fluids from the nearby Tordis and Vigdis
fields, as well as the recent development of the subsea
Gullfaks Satellites, boosts production, but still leaves vacant
process capacity. Primary drilling on Gullfaks is now
completed. Only seven out of a total of 136, drilling slots are
currently vacant, and 120 platform wells are in operation.
IOR and the Gullfaks Field
The Gullfaks Field is currently well into decline and can justly
be described as a mature oil field. In spite of excellent
projected recovery of around 58% at the end of field life at
around 2020, significant volume of oil remains in the ground.
IOR activities have been focused on in Gullfaks almost
from the very beginning. The immiscible hydrocarbon gas
WAG implemented from the early 1990’s is one example of a
successful implementation of an additional reservoir
mechanism. Other uses of associated gas injection include
cyclic gas injection in producers. Together, these mechanisms
have recovered a very significant amount of attic oil. During
high oil prices in the early 1990’s, different chemical IOR
methods, such as surfactants and polymers, were studied but
determined uneconomic.
Additional success has been achieved on a well-by-well
basis, such as conformance control, both mechanical and
chemical, sand control, hydraulic fracturing, and smart wells.
One of the largest contributions has come from successful
infill drilling, targeting the remaining oil mapped through
strategic data gathering, where 4D seismic has lately played a
major role. Inexpensive through tubing drilling is expected to
account for a significant portion of future IOR.
In order to lift the recovery even higher, and to contact
maximum possible hydrocarbon volume in one sweeping
operation, the possibilities for miscible gas injection on a field
scale were investigated. As the associated gas is immiscible in
Brent at reservoir conditions, and enrichment by imported
intermediate components was determined to be too expensive,
the focus turned to CO2 injection. A series of PVT
experiments and fluid studies showed the minimum miscibility
pressure of CO2 in the Brent to be below the bubble point
pressure of 230 bar. The current average reservoir pressure is
around 300 bar; close to initial, so miscible conditions prevail.
SPE 89338
3
The Brent group represents the single, most extensive
target of remaining hydrocarbons in the field. Other parts of
the field may represent additional upside potential, but are
outside the scope of the current study.
Feasibility Study of Miscible CO2 Injection (MWAG)
in the Brent Group of the Gullfaks Main Field
Traditionally, a study of miscible gas injection on a full-field
scale relies on some form of upscaling from detailed segment
or sector models. These can range from simply multiplying up
the recovery from one or more pattern models in the case of a
pattern flood, to analytically scaling up wrt hydrocarbon pore
volume from representative segment models, or to extend an
already existing full field model using pseudo-parameters to
describe the effect of the miscible process and calibrated
against fine gridded reference models. Of the latter, the ToddLangstaff (T-L) solvent option is one alternative.
It is generally not considered feasible to run large, fullfield compositional simulation models directly due to the
computational demands associated with fine grids and
simulator options essential to adequately model the miscible
displacement process.
The T-L options is also computationally demanding, and
additionally has inherent difficulty in simultaneously and
reliably predicting gas utilisation and oil recovery. The T-L
omega model works best for first contact miscible process
where well rates are similar and stable, It was therefore
decided to adopt a technique recently made available and
based on streamline-tracer simulation5,6. The main motivation
for this decision was the reported speed of the computation, its
flexibility wrt handling and optimizing injection strategy, and
not least, its track record in application in other reported
studies and actual projects. Conveniently, the technique and
tools had just become commercially available for the first
time.
Gullfaks Simulation Model Family
Main Field, Brent Group
Simulation Tools for the Gullfaks Field. The Gullfaks field
is a large oil field, and operative numerical simulation models
have recently been constructed for the Brent Group, with
which this project is solely concerned. Figure 5 shows a
schematic of the various simulation models currently in use,
the number of blocks they contain and what has been their
primary function. They are all upscaled from one 3D
geological (structural and sedimentological) model gridded to
some 25 million blocks. The model construction process is
described in detail by Jacobsen et al2. The models are
variously run in black oil, compositional or in streamline
formulation. In all the models, the blocks are nominally
80x100m in areal dimension. Those models that are employed
in the MWAG evaluation are highlighted.
Figure 6: Full-field Model FFM104
A short description follows of only the models used in this
MWAG study, in the logical order in
which they are used:
FFM19: 19 Layer Black Oil Model.
FFM19 is the primary history matched
3D Integrated
black oil, finite difference model for
Geological Model
water injection. The simulation layer
25 mill. blocks
thickness varies from around 10 to 60m.
Key history match parameters are fault
FFM52
FFM166
FFM189
FFM19
FFM104
transmissibility and pseudo relative oil240k blocks
Upper Brent
Lower Brent
72k blocks
460k blocks
water permeability curves. Elapsed run
Cross-sections only Cross-sections only
times range from 15-20 hours for the 13
years history and 20 years prediction,
Thruth Models
respectively. We consider this model
2D and 3D
unsuitable for compositional simulation
Cross-sections
due to the coarse grid and the associated
physical and numerical dispersion
FFM3
problems3,4, but it is the primary
Streamline Model
reference, to which the streamline
with Tracer Logic
models described below are compared to
verify
a
history
match
and water flood prediction to start up of
Figure 5: An Overview of Gullfaks Simulation Models
MWAG.
4
SPE 89338
and transmissibilities without any modification. Run with 6
months time steps, elapsed run times of 4-6 hours are
achieved. This front tracking model is used to establish the
following items:
a)
b)
c)
d)
Identify miscible gas injection target areas
Develop well perforation strategy
Calculate the connected hydrocarbon pore volume
(HCPV) for each MWAG injector location
Extract 2D cross-sections and 3D sector Reference
Models to study the displacement process
FFM104 has the advantage of detailed resolution,
capturing essential geological aspects, structural and
sedimentological, governing the fluid flow in the reservoir.
Figure 6 shows the model viewed from the southeast and
above. It shows the extensive layering and contrast in reservoir
quality, as well as the major fault segments and the top erosion
on the eastern flank of the field.
The Compositional Reference Models. The physics of the
MWAG injection and displacement process are studied in a
fine grid, compositional, finite difference simulator. Reference
models, sometimes referred to as “Truth Models” provide
recovery and timing information for calibrating the streamlinetracer model used to upscale to field level. These models are
mechanistic 2D vertical sections of a single injection well, and
primarily represent reservoir description changes and WAG
injection conformance for each area of the field.
Figure 7: Reference “Truth” Model Locations
FFM104: 104 Layer Streamline Front Tracking Model.
FFM104 has been converted from finite difference to
streamline formulation. The grid has an average layer
thickness of 2 meters. An acceptable history match, wrt
FFM19, on a field level, has been verified when using rock
relative permeability curves and directly upscaled properties
Model Description and Fluid Characterization. A total of
six 2D Reference Models were extracted from the high
resolution, streamline, front tracking model FFM104. The
cross-section locations, shown in Figure 7, were chosen to
represent the range of geological variation in each fault block
and the field as a whole. The cross-section orientation was
selected to obtain the best possible alignment with the
streamlines, i.e. flooding pattern, in the full-field model. The
grid was refined by a factor of 8 horizontally, and by 2
vertically in some layers, resulting in an average block size of
12 and 2 meters horizontally and vertically. A refinement by 8
is based upon our past experience with grid resolution effects
in miscible gas displacement simulation. Figure 8 shows each
model grid and the gas saturation after CO2 injection. The
large difference in vertical sweep and solvent distribution
between the models is evident. This shows clearly the need to
use several models, from different locations across the field, to
capture the effect of variation in reservoir architecture on
recovery. The models also have different injector-producer
well spacing to cover the range that exists in the field. The
Reference Models incorporate physics generally considered
essential when simulating miscible displacement such as
hysteresis and gas trapping.
We feel that in this situation, and especially if resources
are limited, it is preferable to employ many computationally
light 2D cross-sections in preference to one or few ‘heavy’ 3D
sector models as the basis for full-field upscaling. A selfcontained study of 2D vs 3D behaviour can additionally be
conducted, if desired or deemed necessary.
SPE 89338
5
S e c to r M o d e l S u m m a ry fo r C O 2 S R K 8
M odel
W a te r c u t R e c o v e ry % S T O IIP
N am e
SEC2
SEC3
SEC4
SEC5
SEC6
SEC7
W A G S ta rt
8 9 .8 1
9 5 .0 4
9 3 .0 2
9 2 .3 1
9 3 .5 5
9 3 .9 5
W A G S ta rt
6 6 .5 1
5 4 .2 7
5 2 .4 7
4 8 .8 6
6 3 .3 5
6 1 .8 6
M o d e l T yp e A n a lo g y
In c R e c %
B a se W tfld
7 5 .4 2
6 7 .0 9
6 5 .4 5
6 2 .1 4
7 0 .2 6
7 1 .9 9
IO R
6 .4 2
9 .9 6
7 .4 7
1 4 .2 1
7 .9 2
5 .2 3
W A G (S 2 )
8 1 .8 3
7 7 .0 5
7 2 .9 2
7 6 .3 5
7 8 .1 7
7 7 .2 2
V e rtic a l S w e e p
P oor
G ood
F a ir
G ood
P oor
F a ir
M e c h a n ism
A ttic k O il
S h a le u n d e r-ru n
S h a le u n d e r-ru n
K h D o m in a te d
T h ie f D o m in a te d
K h D o m in a te d
G A S S a tu ra tio n Y e a r 2 0 3 0
SEC2 CO 2 SRK8
SEC6 CO2 SRK8
SEC3 CO 2 SRK8
SEC5 CO 2 SRK8
G SAT
LEGEND
SEC7 CO2 SRK8
SEC4 CO 2 SRK8
Figure 8: Fine Gridded Compositional Reference Model
geology at their location. However, the models must also be
representative of the actual dynamic field conditions, such as
pressure, saturations, recovery factor, and throughput rate for
when they are used to establish incremental recovery. With
this in mind, the Reference Models were conditioned to
represent the field state at expected MWAG start up. Well
perforation strategy is also adapted to reflect of what can
reasonably be anticipated achieved in the field. The models are
run with constant reservoir pressure control, and inject solvent
up to slug sizes of 0.1, 0.5, and 1.0 HPV (hydrocarbon pore
Three EoS (Equation of State) models were developed and
tuned to CCE, CVD, swelling and MMP experiments with
reservoir fluid and CO2. An SRK EoS with 8 pseudo
components was selected for the reservoir simulation work.
Peng-Robinson EoS models with 7 and 10 pseudo components
respectively also matched the fluid experimental data well, but
gave higher miscible recovery from the cross-sections. These
results were used as sensitivities in the subsequent uncertainty
analysis.
Dependence of Recovery on Rate
Dependence of Recovery on Slug Size
Gullfaks Lower Brent I-1 Segment
Gullfaks Lower Brent I-1 Segment
0.20
0.20
0.15
Rec %-HPV
Match Curve
0.123
0.117
0.10
Recoery % HCPV
Recoery % HCPV
Rec % -HPV
0.100
0.072
0.05
0.00
0
0.0
0.15
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0.110
0.10
0.093
0.069
0.052
0.05
0.00
2.0
Match Curve
0
0.0
% TPV Flood Rate
0.2
0.4
0.6
0.8
1.0
1.2
Slug Size, % TPV
Figure 9: A set of Performance, or Solvent Efficiency, Curves
Reference Models Simulation Setup. Cross-section models
are individual entities even though they clearly represent the
volume) fraction at a constant rate of 4.5% TPV (total pore
volume throughput), with a WAG ratio equal to 1 with
quarterly cycles. Rate dependency was also evaluated using
6
properties at the WAG injector. Other authors have reported
similar findings, e.g. from the Forties6 field.
0.12
Dimensionless Recovery vs Solvent Injected
Base Rate=4.5%TPV
10.39%
0.10
9.01%
8.73%
8.57%
0.08
7.32%
Recovery fraction hpv
3.0%, 4.5%, 8.0%, and 10% TPV/year, where the base case for
water flood is 4.5% TPV/year. This results in 6 WAG
simulation runs and 1 base case water flood run to evaluate
MWAG performance, per cross-section.
From these runs, dimensionless performance curves are
computed, quantifying IOR in relation to solvent injection in
terms of slug size as percentage of hydrocarbon pore volume
(%HCPV), and solvent injection rate as percentage of pore
volume throughput (%TPV). Figure 9 shows a set of typical
performance curves. The performance curves describe the
cumulative and incremental effect, i.e. IOR oil production, as a
function of cumulative and incremental solvent injection. They
can also be thought of as describing solvent efficiency. That is
how they are subsequently used in optimizing solvent
allocation to injection wells during the scale up to full-field
level.
SPE 89338
6.66%
6.48%
0.06
4.93%
0.04
3.92%
3.47%
3.37%
3D E300
0.02
2D E300
CO2 E300
0.00
0.00%
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
HPV Slug Size
Figure 11: Comparison of Dimensionless Recovery from
2D and 3D Reference Models
DX
(Meters)
IOR Scale Tracer Model: 3 Layers
Figure 10: Tracer Matching, IOR Oil
Tuning the Tracer Models to the Reference Models. The
Reference Model cross-sections are scaled up to the level of
the streamline-tracer model to calibrate the streamline-tracer
parameters. The tracer adsorption and pore fraction parameters
in the upscaled cross-sections are adjusted to match oil and
solvent rates, cumulative production and solvent breakthrough
time, as predicted by the fine gridded cross-sections. Figure 10
shows a typical set of matches for a single cross-section.
Injection and production of gas and oil are individually
matched.
2D vs. 3D Reference Models. A 3D sector model in a
highly dipping fault block was built in order to quantify the
effect of transversely lateral fluid movement in a dipping
structure, absent in a 2D model where lateral fluid movement
is forced along the cross-section. Areal sweep was evaluated
by running the 3D model in Streamline Front Tracking mode
and evaluating the connected HCPV during MWAG injection
based on time-of-flight. That volume was then used to scale
dimensionless recovery and compare to the 2D reference
model. A comparison of 2D vs. 3D recovery is shown in
Figure 11. The bottom yellow curve is for Ethane injection,
not CO2. The difference between the two top curves, CO2
injection into 2D and 3D models is of the order of 0.1, which
is much smaller than the differences observed between
different 2D models in Figure 10. The dominant factor in 2D –
3D comparison is generally likely to be the reservoir
Black Oil Model: 19 Layers
Streamline Front Tracking: 104 Layers
Figure 12: Comparison of Simulation Grids
FFM3: 3 Layer Streamline-Tracer Model. FFM3 is
scaled up from FFM104, reducing the number of layers from
104 to 3. The 3 layers correspond to the vertical division of the
field into hydraulic flow units as described earlier. The model
includes a tracer option, the purpose of which is to scale up the
miscible displacement process to a full-field level. The
principles are briefly described below, with full details
supplied by Giordano5.
Vertical transmissibility is set to zero and the layers only
communicate across fault juxtapositions. The motivation for
having three layers in the model is to have the possibility of
individual assessment of recovery from these three reservoir
units, whereas conventionally, application of the technique
makes use of only a single layer for the whole reservoir.
SPE 89338
7
Field Oil Production Rate & Total
FFM19
HISTORY
FFM104
FFM3
4.0x10
8
60000
3.5x10
8
3.0x10
8
2.5x10
8
2.0x10
8
1.5x10
8
1.0x10
8
5.0x10
7
Oil Rate (SM3/DAY)
50000
40000
30000
20000
10000
0
86
88
90
92
94
96
98
00
Cummulative Oil (SM3)
70000
0
Field Water Production Rate & Total
FFM19
HISTORY
FFM104
FFM3
70000
60000
Water Rate (SM3/DAY)
40000
30000
20000
10000
0
86
88
90
92
94
96
98
Figure 13: Comparison of History Match, different Models
Input to FFM3 comes from the FFM104 and the Reference
Models:
From FFM104:
•
•
•
MWAG Flooding Units
MWAG well locations, type and definition
Connected HCPV by MWAG-injector
From the compositional Reference Models:
•
•
Tracer Adsorption and Timing parameters
Solvent Efficiency Curves for different slug sizes
and injection rates
In the FFM3 MWAG simulations, the IOR performance is
determined from the cumulative solvent injection into each
injector, the associated set of performance curves and the
tracer control parameters calibrated to each Reference Model.
Each MWAG injector is assigned a performance curve based
upon location or reservoir description. A built-in algorithm
optimises the solvent allocation to the injection wells each
time step by ranking the incremental yield for each MWAG
00
8
2.0x10
8
1.8x10
8
1.6x10
8
1.4x10
8
1.2x10
8
1.0x10
8
8.0x10
7
6.0x10
7
4.0x10
7
2.0x10
7
0
Cummulative Water (SM3)
50000
2.2x10
injector, using the performance curves, slug size
and target WAG ratio.
Oil and water flows (the simulator is 2-phase,
so associated gas production is calculated from
oil production using a fixed solution GOR) are
computed simultaneously for water flood in the
conventional front tracking manner, and for the
miscible displacement by propagating tracers
along oil-water streamlines. The model runs the
combined history and 30-year prediction on a
single CPU in less than half an hour, elapsed
time. The water flood history in FFM3 is
matched to the FFM19 results by adjusting the
pseudo relative permeability curves only.
However, this does not affect the MWAG IOR
prediction because IOR oil and solvent streams
are not subject to model saturations, but are
represented by tracers, independently tuned to
match the results of the compositional Reference
Models previously described. The StreamlineTracer model thus does not model the miscible
process physics. Rather using three tracers, it
mimics the behaviour as modelled by the
compositional Reference Models. The tracers are
defined as follows:
•
•
•
Effective solvent, which mobilises
IOR oil
The IOR oil, and
Ineffective solvent, which does not
mobilise IOR oil
Note that the sum of the effective and ineffective tracer
injected equals the total solvent injection. With time, the ratio
of ineffective to effective tracer increases, representing the
reducing solvent efficiency with cumulative injection.
Model and Type
FFM104 Black Oil, finite diff.
FFM19 Black Oil, finite diff.
FFM104 Streamline
FFM3 Streamline-Tracer
No.
CPUs
Elapsed
Time (hrs)
8
40
4
15
1
7
1
0,25
Table 1: Comparison of Model Run Times
The tracer model accounts directly for vertical sweep,
perforation conformance, geology, and other physical aspects
incorporated into the Reference Models. However, areal sweep
in FFM3 is entirely determined by the conventional water-oil
front tracking method. The assumption that areal sweep for
MWAG will follow water-oil streamlines has not been
reported to be a problem for predictions with streamline-tracer
models in Alaska, where pattern floods and low dip formations
are prevalent. In the case of Gullfaks where formation layers
dip typically between 15-25 degrees, additional 3D sector
model simulations were run to verify that essential areal
8
SPE 89338
identify areas of bypassed oil and to divide the field into
MWAG flooding regions. It is also used to determine the
connected HCPV for each MWAG injector, a key input for the
optimisation algorithm for solvent allocation in FFM3.
Six 2D cross-sections, the Reference Models, are extracted
from FFM104, representative of areas previously identifies as
MWAG flood regions. They are run in a compositional
Summary of the Simulation Models. The simulation
simulator to generate the Performance Curves for each region.
models that have been described represent a wide range of grid
The curves are entered into FFM3, the 3-layer full-field
resolution and geological detail. The upscaling processes, both
streamline-tracer simulator, where each MWAG injector is
as regards static reservoir parameters and the dynamic
assigned a particular performance curve according to its
miscible fluid displacement process, are intended to capture
location in the reservoir. The performance curves enable the
the essential aspects of how these phenomena affect oil
estimation of incremental IOR and solvent efficiency, each
recovery and solvent utilisation in such a way as to be able to
simulation time step, for the MWAG injectors. The solvent
be brought forward to a fast, accurate and practical tool to
efficiency is used to optimize solvent allocation to the
scale detailed Reference Model results to field level.
injectors throughout the simulation.
Figure 12 compares the different full field models
The Reference Model cross-sections are also upscaled to
FFM104, FFM19 and FFM3, illustrating the difference in
layering analogous to that in FFM3, and used to calibrate the
resolution and complexity. It shows a schematic of plan view
tracers to match IOR oil and solvent production in the
and cross-sections from the 3 full-field simulation models used
corresponding finely gridded, compositional Reference
for the Gullfaks gas displacement IOR evaluation. The plan
Models. The calibrated tracer parameters are then exported to
view on the left is coloured by block grid increment which
FFM3 to control tracer propagation on a field scale. The
ranges from 50-150 meters, where each cross-section of the
solvent is propagated along all the streamlines emanating from
right of Figure 12 is coloured by PermZ showing shale in dark
each MWAG injector, resulting in mobilisation of IOR oil,
blue. As may be seen, the model with 3 layers does not have
solvent entrapment and breakthrough. As it is a 2-phase
vertical heterogeneity, whereas 19 layers result in thick blocks
simulator, the associated gas production is calculated from the
of sand and shale that are highly upscaled. Using 104 layers
oil production using a fixed solution GOR. The water flood
has minimal upscaling of vertical variation and shows discrete
process is calculated in the conventional streamline – front
sand and shale packages.
tracking manner, with the miscible process mimicked by
Export MWAG areas
the tracers.
and connected
FFM3
FFM104
In summary, this technique has the unique ability to
pore volume / injector
StreamlineStreamline
simultaneously generate profiles for the water and
Tracer Model
Model
Upscale 104 to 3 layers
miscible flood recovery. The production and injection
(104 layers)
(3-layers)
constraints are the individual platform and well
Extract X-sections
and refine
capacities and the total solvent supply. The last consists
Extract X-sections
upscale to 1 layer
of imported solvent and reinjection fraction for the back
produced solvent. Solvent allocation during each
Reference Models
StreamlineCompositional
Tracer Model
simulation time step is determined by the number of
Simultaneous
2D Cross-sections
1D Cross-sections
Full-Field
available injection wells, the WAG-ratio and predicted
(100-200 layers)
(1-layer)
Export
WI and MWAG
IOR oil production according to the efficiency given by
Performance
Recovery
Calibrate
Curves
the individual wells’ performance curves.
Tracer Controls
Estimates
displacement behaviour of the solvent was satisfactorily taken
into account using only 2D Reference Models. As mentioned
earlier, this result was also observed in the case of the Forties
work6, although it should not be taken as a general
observation, but checked in each individual case.
to match oil and solvent
Recovery and Timing
Compute
Performance
Curves
Estimates
Export Tracer Controls
Figure 14: Overview of Simulation Workflow
Figure 13 shows the water flood history and prediction for
these models, showing that they all give a result at field level
that is acceptable. Table 1 lists the elapsed times for running
these models. Although the absolute numbers will depend on
the type of hardware, a comparison of the relative speed is
instructive.
Simulation Workflow. Figure 14 shows a somewhat
simplified diagram of the simulation workflow. FFM104 is the
104-layer streamline front tracking model used to develop the
injection strategy through selection of injector locations,
Development of the MWAG Injection Strategy.
Although it is essential for a successful miscible
injection project to employ a thermodynamically
efficient injectant, it is probably even more important to
have an injection strategy that places the injectant optimally in
the reservoir, over time. This is in fact true of any recovery
mechanism; good well locations are a must for efficient
drainage. With costly injectant, this is paramount to obtain
maximum reserves for every ton or cubic metre of injectant.
Gullfaks has traditionally been developed with water
injection as the primary reservoir energy source. The water has
been largely injected, into key ‘super injectors’ in the aquifer,
below the original OWC (oil-water contact). This way,
reservoir pressure has been maintained successfully through
voidage replacement. Some over-injection has also taken
place, resulting in partial pressure support through the regional
aquifer to nearby fields. The current well network in the field
is therefore primarily designed for long distance volume
SPE 89338
9
replacement with water through the aquifer, but with some
injection wells placed closer to the producers, in what with
time has become the flushed zone. This strategy is unsuitable
for an MWAG for a variety of reasons, some of the most
important ones being:
1.
2.
3.
producers, including 5 future well targets that will be turned to
MWAG injection, either immediately or in due course.
The operations required to prepare each well for injection
are routine on the Gullfaks field, and the time, equipment and
costs associated well known from experience. It is assumed
that all the well work can be completed in 2007 and 2008.
The long distance between peripheral injectors and
oil zone producers would result in late solvent
breakthrough. A shorter distance is desirable in
order to have better vertical sweep and rapid reuse
of the expensive solvent.
Significant volumes of solvent would be trapped
and lost out in the aquifer and would not mobilise
any oil
Control over the slug size applied to each flood
pattern becomes impossible with the long
throughput time and uncertain flow paths in the
absence of breakthrough in wells
Figure 16: MWAG Injection Pattern
The MWAG flooding areas are shown in Figure 17. There
are 11 areas represented by the 6 different Performance Curves
applied to the 33 MWAG injectors. Reservoir coverage with
this well configuration is estimated at 72%, using FFM104.
Results
Figure 15: Classical Aquifer Water Injection Pattern
Rapid circulation of solvent through the IOR target
accelerates the recovery, and each flooding area can receive
concentrated flood treatment before moving on to the next,
rapidly expanding the treatment as more solvent is available
from back production. Figures 15 and 16 illustrate the
difference in the reservoir flood pattern, where on one hand
the energy is expended and dissipated over long distances by
peripheral aquifer injection, and on the other hand through
closely spaced injector-producer pairs in the hydrocarbon
zone, resulting in a more even coverage aerially and
contacting more of the oil in place.
Injection Well Locations for the MWAG. In order to
achieve timely and efficient sweep of the IOR target, many
watered-out producers were reassigned to MWAG injection.
In all, 33 wells are assigned to MWAG injection from 2008.
Most of the wells will require a degree of workover such as
plugging, zone isolation, re- and additional perforating and
tubing replacements. Of the 33 wells, 14 are currently water
injectors (including one WAG injector) and the rest are
CO2 MWAG Reservoir Management Impact. The current
development strategy for the Gullfaks Field is to inject water
and modest quantities of associated gas to 2006, and only
water thereafter. Considerable effort has been put into
optimizing this scenario, but mostly by optimizing injection,
production and well utilization (completion strategy,
workovers, etc) within the constraints of the existing injection
well pattern and from drilling infill producers. The full field
simulation tools are useful aids in exploring alternative
management strategies for the field.
The MWAG scenario represents a considerable change in
reservoir management. Injection would now take place mostly
above the original OWC, utilizing many watered-out
producers. This will result in a much more rapid circulation of
injected fluids due to closer well spacing. The simulator
predicts accelerated oil production, as well as more rapid
sweep to lower oil saturation in the inter-well space. The effect
of the water injection alone is significantly enhanced with the
new strategy, with additional benefits being brought by the
miscible displacement by CO2.
10
SPE 89338
H7
AQ
I5
G6 H5
I2
G4
F4
F3
I3
I1
G2
Figure 17: MWAG Flooding Regions
Segregated Processing and Direct Reinjection. Several
options exist for implementation of a CO2 MWAG in the
Gullfaks field. We will describe one that is relatively simple in
terms of infrastructure upgrades and modification is termed
“Segregated Processing and Direct Injection”.
The Gullfaks field is a processing centre for 3rd party
production from nearby fields. Many of these rely on gas sales
as a main source of revenue. If contamination of the sales gas
by CO2 is to be avoided, it can be achieved by dedicating one
of the two processing trains to the production stream from the
MWAG areas on the Gullfaks-A and -C platforms, whilst the
other trains is reserved for non-CO2 contaminated production.
The capacities of the processing trains conveniently enable
such an arrangement.
Figure 19: Solvent Saturation in 2008 at startup
Figure 20: Solvent Saturation in 2029
Figure 18: Oil Saturation in 2008, Top Reservoir
Additionally, to simplify the recovery of back produced
injectant, the entire gas production; solvent and hydrocarbon
gas, from the MWAG trains is mixed with the CO2 import
from shore and injected.
Calculations show that the inclusion of the hydrocarbons in
the injectant has only minor negative consequences. The
maximum dilution of the injectant is 40% on GFA in the first
year, and then rapidly reduced to less than 20% and further, as
increasing amounts of CO2 are backproduced. In order to
approximate this strategy in the 2-phase streamline-tracer
simulator, the imported solvent mass is adjusted up to reflect
the contribution of the hydrocarbon gas in the injectant. In the
current study, the hydrocarbon gas production is simply
averaged, assuming that the return rate of hydrocarbon
injection gas is the same as for solvent, over the entire period
and – in the simulator - adding a corresponding reservoir
volume of solvent to the import. By avoiding having to extract
the solvent from the production stream for reinjection, the
solvent utilization is also increased. Some CO2 must
nevertheless be expected lost, and the reinjection fraction in
the simulator is set at 95%.
SPE 89338
11
Results
/
Up to Year:
Cumulative Injectant
GSm3
(includes hydrocarbon gas) Mt
Imported Injectant
GSm3
Mt
Backproduced Injectant
GSm3
Mt
Incremental Oil, MWAG
MSm3
due to CO2 alone, MSm3
Net Efficiency
ton CO2 / Sm3 oil
Gross Efficiency ton CO2 / Sm3 oil
2020
2030
47
87.4
25
46.5
18
33,5
48
24
2.0
3.7
60
111.6
25
46.5
32
57.7
58
31
1.5
3.6
Table 2: CO2 MWAG Project Parameters,
Directly Simulated Figures
1.
CO2 MWAG Injection and Production Profiles. The CO2
supply level of approximately 5 Mt/year over a 10-year period
is based on an evaluation of quantities that can be realized
within the project time frame.
400M
50K
300M
40K
200M
30K
20K
100M
10K
Cumulative Oil Production, Sm3
Oil Production Rate (SM3/DAY)
60K
0
0
12/86 12/90 12/94 12/98 12/02 12/06 12/10 12/14 12/18 12/22 12/26 12/30
Figure 21: Oil Production, Base Case Water flood and
MWAG
70G
14M
60G
(SM3/DAY)
50G
10M
40G
8M
30G
6M
20G
4M
10G
2M
0
12/00
12/04
12/08
12/12
12/16
12/20
12/24
12/28
Field Cumulative Solvent Product (SM3)
16M
12M
At that level, a useful reservoir slug size is also achieved
during the field’s operating lifetime, and the resulting injection
and production profiles can be accommodated within the
platform capacities, with manageable upgrades where
necessary. Greater injection rates and an extended injection
period can be accommodated, but a cost-benefit analysis
would reveal the optimum. The project parameters presented
are considered a reasonable starting point. Table 2 shows the
simulation constraints and results.
Figure 18 shows the oil saturation at top reservoir in 2008
and Figures 19 and 20 show the solvent saturation in 2008 and
2029, showing the high degree of reservoir coverage
Figure 21 shows comparison of the oil production profiles
for three separate cases:
0
Figure 22: Solvent Injection and Production, MWAG
2.
3.
Conventional water and gas injection (current
strategy) as predicted by FFM19. The profile is run
to 2020 only, as the economic limit for the field life
according to current strategy is shorter.
Water flood only using the 33 well injection pattern
from 2008, and
CO2 MWAG. The two latter profiles are run to 2030
in the expectation that economic life for the field in
these scenarios can be extended well beyond 2020.
In the simulations, all the new injection wells come on line
simultaneously, even though it is acknowledged that it will
take two years to prepare the extra wells for injection.
However, at the current stage of the investigation, this is not
considered to be of major importance, but will be corrected if
and when plans proceed towards implementation.
Figure 22 shows the solvent injection and back production
profiles. The MWAG contribution to the field’s economic life
can be roughly estimated, albeit in a simplified manner, by
examining Figure 21. Assuming that the field life with the ‘noaction’ strategy is around 2018, one can see that with the
MWAG, that level of production, or more, is maintained to
2029. If the future OPEX of the field per unit production
volume is maintained or even reduced through efficiency
gains, extension of field life could be realized, other things
being equal.
Sensitivity Parameters and Uncertainty
Several sensitivities have been run, and others incorporated
from previous and separate studies of water flooding. The
main sensitivities are listed in Table 3.
“Attic Oil” refers to a subtraction from simulated IOR
recovery due to attic oil already produced from dry gas
injection. The other parameters are associated with the ability
to maintain and run the offshore infrastructure, including
wells. The CO2 flooding parameters are those specifically
related to the prediction of results from the miscible
displacement.
As can be seen from the P50 recoverable reserves in Table
3, a significant portion of the MWAG benefit is predicted to
be attainable through water injection alone, using the well
pattern that has been developed with miscible CO2 flooding in
mind. Whereas this may represent a significant opportunity for
Gullfaks, it detracts to a large extent from the potential for a
miscible CO2 flood.
12
SPE 89338
It remains, however, to ascertain that such intensive water
flooding of the Gullfaks field is manageable. This work is
currently underway. Some of the major obstacles are:
•
•
•
•
Increased power requirements for water injection
systems
does any infrastructure exist on land for CO2 removal or
transport either on land or at sea. An entire infrastructure from
capture, to transport to injection has therefore to be built
nearly from scratch to realize a commercial IOR project such
as that being considered here.
Increased water production, liquid processing capacity,
cleaning and disposing of greater volumes of produced
water
Melkøya, 0,7
Increased potential for H2S production
Gullfaks
Increased Sand Production. Increased liquid production
through fewer wells (many producers are reemployed
as water injectors) restrained by MSFR (Maximum
Sand Free Rate) is a challenge
P50 Recoverable
Reserves, MSm3
Attic Oil
CO2 Flood
Parameters
Operational
Parameters
Well Economic Limit
Processing Capacity
WCT
Reservoir Performance
CO2 Supply
EoS Fluid Description
Attic Oil that is already
produced before CO2
MWAG
Mongstad, 2,2
Kårstø, 0,2 +
Brae
Grenland, 0,5 - 2
Sleipner
Ålborg, 3 + 2
Comments
Well reliability, wear
and tear
Platform gas and liquid
production and injection
capacity
Well production limit
due to water cut
Reflects the maximum
variation in reservoir
performance from E300
Truth Models
Uncertainty in CO2
supply
PR07 results in higher
oil recovery than SRK8
The streamline-tracer
simulator is two phase,
and cannot directly
account for attic oil that
has been removed by
dry gas injection
34
47
CO2 MWAG to 2020
CO2 MWAG to 2030
22
28
CO2 part only to 2020
CO2 part only to 2030
Table 3: Main Sensitivity Parameters and Results from
Risk analysis
Esbjerg, 2,0
Kalundborg, 2,0 +
Egernsund3,0
Brunsbüttel , 0,65
Drax
~9,0
Antwerp /Rotterdam, 2 - 3
Figure 23: Sources of CO2 around the North Sea Region
Figure 23 shows a map of the North Sea and the
surrounding region. Current sources of industrial CO2 are
marked on the figure, showing the quantity in MT/year. The
sources are geographically scattered over a large, densely
populated area. This makes the gathering of CO2 to a single
point of export very difficult, if not impossible. Parallel
transport, e.g. pipelines from several sources to Gullfaks, is
likewise not an economically viable alternative.
In the technical solution alternatives where the
backproduced CO2 is transported onshore with the
hydrocarbon gas, the captured CO2 from the associated gas is
returned from shore to Gullfaks. However, this adds cost. The
option of mixing and reinjecting the contaminated
hydrocarbon gas with the imported CO2 is considered to be the
preferred alternative. Simulations have shown that the effect
on recovery is minimal.
A number of alternatives have been evaluated, with two
described briefly below:
CO2 from Danish Coal Fired Power Plants. This scenario,
illustrated in Figure 24, assumes supply from Danish coal fired
power plants with a single point of export. Two transport
options have been considered for this scenario:
Example Solution for Implementation of CO2 MWAG
in the Gullfaks Field
•
CO2 Supply Scenarios. Commercial injection using external
CO2 sources is not currently taking place anywhere in the
North Sea. There are no natural sources of CO2 in the North
Sea or vicinity that are significant in the current context. Nor
•
Option 1: Ship transport to a CO2 hub located onshore
in western Norway, and pipeline transport from there
to the field.
Option 2: Transport by pipeline directly to the field.
SPE 89338
13
The first option has greater flexibility with regard to
adding other sources, but involves more complex logistics. It
is also
CO2 from Multiple Continental and Norwegian Sources.
This scenario illustrated in Figure 25 assumes that CO2
supplied from two continental chemical plants and captured
for disposal at the Norwegian Snøhvit condensate field in the
Arctic, is delivered to a hub at the Mongstad oil terminal on
the Norwegian west coast. Additional CO2 is captured from
existing emissions at Mongstad to make up the volume to
around 5 Mt/year. Transport is by ship from the external
sources to Mongstad, and by pipeline from Mongstad to the
field.
Figure 25: Multi-source CO2 Supply and Transport
Figure 24: Single Source CO2 Supply and Transport
Modifications and Upgrades of Field Installations. To
implement CO2 MWAG injection on Gullfaks, considerable,
but manageable, modifications to the field installations are
required:
•
•
•
•
•
New wells, well conversions (already mentioned)
The aspect of material upgrades warrants a further
mention, as this would in many cases be a ‘show stopper’ for
implementation of a project of this type in a field with ageing
installations. Fortuitously, the Gullfaks installations were
extensively upgraded during the 1990’s to 13% Cr
specifications in anticipation of increasing H2S production,
which subsequently has been mitigated to large extent. All the
producers are completed with production tubing of the same
material. This makes Gullfaks, amongst other fields of similar
age in the North Sea, uniquely competent to handle corrosive
well and process streams. Nevertheless, some material
upgrades would be necessary. Although not trivial, they are
considered manageable.
Economic Constraints. Supplying CO2 to the North Sea
fields is a costly affair. Some of the major reasons for this are:
•
•
De-bottlenecking of production systems
•
CO2 injection systems and manifolds on all three
platforms
•
Additional intra-field pipelines, and
Material upgrades
These modifications and upgrades are responsible for a
significant portion of the total project CAPEX.
Long distance to sources capable of supplying CO2 in
industrial quantities
No transport solutions for CO2 in the requisite
quantities exist, and must be built from scratch
Power plants that represent a significant potential
source of CO2 do not have capture implemented
The sources are scattered over a large area and across
national borders, in heavily populated areas with dense
economic infrastructure
Many of the large North Sea fields that would be desirable
to include in starting up a new phase of industrial oil
exploitation that CO2 MWAG in reality is, are nearing the end
of their economic life:
14
•
•
SPE 89338
Recovery from North Sea fields by water injection is
already high, in many cases 50-70%. The remaining oil
is scattered in the large reservoirs, representing a
difficult MWAG target
Conclusions
The potential for CO2 MWAG injection in The Gullfaks Field
has been estimated using a commercially available streamlinetracer simulation tool for upscaling to field level.
Field installations are ageing, and many couldn’t
handle CO2 back production without major
refurbishment
Optimisation of the MWAG injection strategy has been
greatly aided using a streamline front tracking simulator with
high grid resolution to first segment the field into flooding
units, then to employ an inbuilt module for optimising solvent
allocation on a well-by-well basis during runs with the
upscaled streamline-tracer simulator. Both tools are extremely
fast compared to other alternatives known to us.
The technical potential for IOR is considered to be present
in the case of the Gullfaks field, but the present economic
conditions prevent the project from going ahead on
commercial grounds.
The procurement of CO2 represents the greatest single cost
element. The other main cost elements are the CAPEX and
OPEX. Even if some reductions could be achieved in these,
they are likely to be modest. Therefore, a radical reduction in
the cost of CO2 is required for commercial viability.
Considerable uncertainty is associated with the potential
income from CO2 quota trading and its value to possible future
sequestration in the Gullfaks field once commercial oil
production is over. CO2 tax credits and delayed field
abandonment costs are only modest income elements.
To make the project economically attractive, efforts could
be made to form alliances to share the cost of the necessary
infrastructure, consortium of several fields for implementation,
also changes to national fiscal systems to adapt to late life
production, increasing need for IOR.
The simulation tools and workflows developed for the
Gullfaks study are having a positive impact on the
management of a reservoir that has been diligently worked for
over 20 years; these tools are expected to be used well into the
future for development and operational activities, irrespective
of CO2 flooding goes ahead or not.
Even if the conclusion is that the economic conditions for a
CO2 MWAG are unfavourable, a significant opportunity to
enhance the water flood strategy has possibly been identified
through a radical redesign of the injection pattern.
Acknowledgements
The authors would like to thank the operator, Statoil, and
partners in the Gullfaks license, Norsk Hydro and Petoro, for
their support and permission to publish this paper.
Discussion
References
Further Work. Because of advances in computing power in
recent years there is more industry focus on field scale
compositional simulation. The owners of the Gullfaks field
have embarked upon a field-wide composition model using 52
layers and approximately 240,000 active cells. From working
with the Reference Models, we estimate that considerably
more detailed grid would be required for reliable results,
although e.g. segment models with a flux option and/or local
grid refinement may be of help. Nevertheless, incorporating
the requisite physics, such as hysteresis and gas trapping
would additionally increase computing requirements.
The streamline-tracer simulator is still only 2-phase, and so
cannot model reinjection of associated gas. The addition of
free gas as an additional tracer, development of a 3-phase
streamline-tracer simulator, or a compositional streamline
simulator might enhance the applicability of this methodology.
The attic oil produced on Gullfaks by dry gas injection
cannot be taken into account directly by the streamline
simulator. To correct for this, the simulated result is reduced
by an amount representing historically produced attic oil. A
more realistic option would be to take historical dry gas into
account in the E300 truth models. Should the projected work
with the compositional full field model mentioned above be
successful, that would also enable this to be taken into account
in an even more rational way.
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Strønen, L.K., "Identification and Modeling of Remaining
Reserves in the Gullfaks Field", paper SPE 65412 poster
presentation at the EUROPEC 2000 Conference held in Paris,
France, October 24-25 2000.
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4. Haajizadeh, M., Fayers, F., Cockin A., “Effects of Phase
Behavior, Dispersion and Gridding on Sweep Patterns for Nearly
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October 2000
5. Giordano, R.M., Redman, R.S., and Bratvedt, F.: “A New
Approach to Forecasting Miscible WAG Performance at the Field
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”Forties CO2 IOR Evaluation Integrating Finite Difference and
Streamline Simulation Techniques”, SPE 78298, presentation at
the SPE 13th European Petroleum Conference held in Aberdeen,
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