numerical simulation of ior and eor processes in a carbonate reservoir outcrop analogue
DESCRIPTION
Numerical Simulation of IOR and EOR Processes in a Carbonate Reservoir Outcrop AnalogueTRANSCRIPT
CARBONATE RESERVOIRS…..
Simeon Agada, Fuzhen Chen, Sebastian Geiger
Institute of Petroleum Engineering, Heriot-Watt University, U.K. Email: [email protected]
Numerical simulation of IOR AND EOR processes in a carbonate reservoir outcrop analogue
DYNAMIC MODELLING USING 3D HIGH-RESOLUTION DIGITAL OUTCROP MODELS
PURPOSE
ANALYSING THE IMPACT OF HETEROGENEITY ON DIFFERENT RECOVERY MECHANISMS
CONCLUSIONS: 1. Outcrop analogues are used as an economic means to decipher fundamental flow attributes during IOR and EOR in carbonates. This is achieved by relating transient pressure response to visible geological heterogeneity.
2. Secondary recovery (waterflood and gasflood) and tertiary recovery (miscible flooding) simulations show that fluid properties and engineering parameters can be varied to optimise recovery during IOR and EOR.
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Pre
ss
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(p
si)
Time (hr)
Zero Trans (P) Zero Trans (dp/dt)
0.25 Trans (P) 0.25 Trans (dp/dt)
1.0 Trans (P) 1.0 Trans (dp/dt)
5.0 Trans (P) 5.0 Trans (dp/dt)
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0.1 1 10 100
Pre
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(p
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Time (hr)
WT1 (Press) WT5 (Press) WT7 (Press)
WT1 (dp/dt) WT5 (dp/dt) WT7 (dp/dt)
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Pre
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(p
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Time (hr)
WT1 (Press) WT2 (Press) WT6 (Press)
WT1 (dp/dt) WT2 (dp/dt) WT6 (dp/dt)
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0.1 1 10 100
Pre
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(p
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Time (hr)
Base_WT1 (Press) Base_WT1 (dp/dt)
Bioherms_WT1 (Press) Bioherms_WT1 (dp/dt)
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0.1 1 10 100
Pre
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(p
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Time (hr)
Base_WT4 (Press) Base_WT4 (dp/dt)
Bioherms_WT4 (Press) Bioherms_WT4 (dp/dt)
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Pre
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(p
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Time (hr)
Base (Press) Base (dp/dt)
Base + Fractures (Press) Base + Fractures (dp/dt)
(a)
(f)(e)
(d)(c)
(b)
Flow simulation and
pressure transient
analysis workflow
Upscaling
Flow Simulation
Fracture Modelling
Outcrop Analogue
Geological Model
Numerical Well Testing
A systematic process is used to adequately capture
geological heterogeneities and represent them in
high-resolution geological and flow simulation
models. The workflow we employ enables us to
identify unique signatures of geological features by
numerical well testing and to optimise hydrocarbon
recovery in carbonates by secondary (water and gas
injection) and tertiary (miscible flooding) methods.
(a) Oil recovery factor and (b) oil production rate for secondary and
tertiary oil recovery simulations. Impact of (c) petrophysical rock types and
(d) hysteresis on ultimate recovery from WAG.
f f
Upscaling is required for quick turn around time in numerous
optimisation simulations. It is achieved by a vertical layer
optimisation procedure and validated against the fine scale
geological model using streamline simulations (full field) and
finite difference simulations (sector).
- 350
- 0
- 200
- 100
- 300
Dip azimuth (deg)(a) (b) (c)
CAD Rhino Representation of Outcrop Window
ANSYS Mesh of Outcrop Window after Extrusion to 3D
The influence of faults is seen (below) by the slope of the
pressure transient at late time and always dominates transients
(a & e). The symmetry/asymmetry of a well’s drainage area is
discernible from the pressure transient derivative “hump” (b).
High permeability oyster bioherms in varied reservoir locations
are also identifiable from transients (c & d). The classical
textbook transients for a fractured reservoir are not visible
possibly due to severe heterogeneities (f).
(e)
a) Regular 5-spot waterflood (favourable mobility)
b) Inverted 5-spot waterflood (favourable mobility)
c) Direct line drive d) Staggered line drive
e) Regular 5-spot gasflood (favourable mobility)
f) Regular 5-spot waterflood (unfavourable mobility)
g) Tornado chart showing impact of key engineering
parameters
(a)
(f)
(c)
(d)
(b) (g)
Digital outcrop model showing positions
of synthetic numerical test wells
Digital outcrop model showing high
permeability mollusc banks
Drawdown pressure transients enhance
identification of geological features
Oyster
Bioherms
Base Geological Realisation
Model with oyster bioherms
Outcrop Analogue
The matrix model is coupled with fractures using a Discrete Fracture Network (DFN) model or Discrete
Fracture and Matrix (DFM) model that incorporates input from RHINO & ANSYS. DFNs are generated
for 0.1, 0.5 & 0.9 fracture intensity to investigate fracture impact on flow dynamics. The DFNs are then
combined with dual porosity-dual permeability models in IMEX/GEM for fracture flow simulations.
In the numerical well test analysis, synthetic wells are placed at different locations in the
outcrop model to test the impact of small- and large scale heterogeneities including mud
mounds, oyster bioherms and fractures. The theoretical pressure responses (e.g. linear
flow and recharge) that are derived for idealised geological structures can be validated by
comparing them to pressure responses obtained for realistic geological structures. This
procedure can also be employed to improve the calibration of static and dynamic reservoir
models with production. The secondary recovery simulations show the potential of varied
fluid and engineering parameters to mitigate flow challenges due to heterogeneity.
Final flow simulation model
• Intermediate oil-wet reservoir
• Single and multiple Pc & Kr curve
• Secondary recovery simulations with IMEX
• Miscible Flood simulations with GEM
DFN with 0.1 fracture intensity (P32) DFN with 0.5 fracture intensity (P32) DFN with 0.9 fracture intensity (P32)
Injector
Producer
979,000 980,000 981,000
979,000 980,000 981,000
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File: CO2_CGI_Miscible_B1.irfUser: simeon agadaDate: 31/05/2013
Scale: 1:5754Y/X: 1.00:1Axis Units: ft
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Oil Saturation 2011-05-01 K layer: 1
InjectorInjector-CO2
Producer
979,000 980,000 981,000
979,000 980,000 981,000
-11,6
22,0
00
-11,6
22,0
00
-11,6
21,0
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0.00 370.00 740.00 feet
0.00 115.00 230.00 meters
File: co2_wag_miscible_b1.irfUser: simeon agadaDate: 31/05/2013
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Oil Saturation 2011-05-01 K layer: 1
InjectorInjector-CO2
Producer
979,000 980,000 981,000
979,000 980,000 981,000
-11,6
22,0
00
-11,6
22,0
00
-11,6
21,0
00
0.00 370.00 740.00 feet
0.00 115.00 230.00 meters
File: co2_wag_miscible_b1.irfUser: simeon agadaDate: 31/05/2013
Scale: 1:5754Y/X: 1.00:1Axis Units: ft
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Oil Saturation 2011-05-01 K layer: 1
Injector
Producer
979,000 980,000 981,000
979,000 980,000 981,000
-11,6
22,0
00
-11,6
21,0
00
-11,6
22,0
00
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File: water injection_b1.irfUser: simeon agadaDate: 31/05/2013
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Oil Saturation 2011-05-01 K layer: 1
(b) (a)
So
Water Injection Continuous Gas Injection
(Miscible)
Water Alternating Gas Injection
(Miscible)
• Carbonate reservoirs are highly heterogeneous across all
length scales, rendering it difficult to predict flow behavior in
the subsurface.
• The multi-scale heterogeneities result from complex
depositional, reactive and diagenetic processes.
• An accurate characterization of carbonate reservoir
architecture is therefore critical for successful modelling and
multiphase fluid flow prediction.
• The detailed reservoir architecture is commonly studied
using outcrop analogues, but these are rarely used for flow
modelling.
We use a high-resolution 3D outcrop model of a Jurassic
Carbonate ramp in order to perform a series of detailed and
systematic flow simulations. The aim is to test the impact of
small- and large-scale geological features on reservoir
performance and oil recovery during IOR and EOR. We also
investigate the effect of dynamic matrix-fracture interaction and
phase miscibility on the flow simulations.
(a) (b)
(c) (d)
Research kindly supported by the ExxonMobil (FC)2 Alliance