CFD Modelling of Flow Assurance Challenges

Technology for a better societyANSYS NordicOilGas Seminar Oct. 15 & 16
Oslo & Stavanger
1
Stein Tore Johansen
SINTEF
The flow assurance challenges and
possibilities for CFD to contribute.

• Exploration in colder and deeper waters:
• Drilling, construction, maintenance and operation is more expensive.
• Transportation of oil, condensate and gas in long pipelines may be very cost-effective
if multiphase transportation is reliable.
• Main challenges for long-distance pipeline transportation:
• Handling of precipitation of solid materials as flow cools down (wax, hydrates,
asphalthenes)
• Effects of pressure reduction (scale precipitation and resulting deposition)
• Cost effective sizing of the pipeline (reliable and stable operation – control with
liquid surges and slugs)
2
The Challenges

Technology for a better societyANSYS NordicOilGas Seminar Oct. 15 & 16 3
Shut down and restart
Shut down:
• Many solids form as the well flow cools down. The solids may deposit on
the pipe wall or become dispersed particles in the liquid.
• Mature fields produce more and more water 
• After shut-down the pipe may clog if the water in the pipeline is
converted into solid hydrates.
Restart:
• Alternatively the pipeline may be open as operation restarts but becomes
plugged during start-up.
• Cold Flow Challenge: Can we restart a shut down and cold pipeline
without adding chemicals and without costly hydrate prevention
measures ?

Example of compact hydrate plug:
Ref. Kværner report on cold spots in Kristin X-mas tree and choke module

Example of wax ’slug’ in pig trap at Statfjord B
Ref: H.P. Rønningsen, Statoil

Ref: H.P. Rønningsen, Statoil

Low liquid loading: The Snow White field pipelines
Flow with small liquid contents may still result in significant liquid
accumulation !!
In very long lines: Extreme challenges  Uncontrollable flow instabilities
160 km long !

Aker Solutions Subsea Field Layout for Aasgard
Emerging technologies:
Separation moves closer to the wells
Seabed processing
Downhole separation

More challenges:
Icing on structures
Wave impact on structures

Even more challenges:
Blow outs
- Scenario evaluation
- Capping stacks
- Explosion risk assessments
Oil spills – prevention and clean up
- Better oil boom technology
- Dispersion and breakdown in the
environment

• Oil exploration in the Arctic and near Arctic regions has many significant technology
challenges.
• Operations in these areas need technologies which can give fast and accurate enough
answers
• The complexity of the physics and chemistry involved is extreme !
• Length scales varies from sub-millimeter to hundreds of kilometers
• Time scales varied from seconds to years !
• Good flow assurance models needed which can predict system performance. Speed
requirements are at least to simulate 10 times faster than real time!
• These models will be the workhorses for driving process simulators, operator training,
optimization and troubleshooting
• CFD does not fit directly into this picture (detailed, too slow, too complex, tuning not
possible if data is scarce )
• At the end, multi-billion USD decisions will in a foreseeable future be based on this
type of models, and not on CFD
11
The CFD Challenge

• Still, CFD has the capability to explain the complex interactions of physics and
chemistry, together with experiments, in order to build simplified models with
acceptable confidence.
• In addition, CFD has the capability to improve and design unit operations (separators,
well inflow devices, oil-booms) in order to improve their performance.
• Computational Fluid Dynamics is a tool which relies heavily on the physical models
and modeling concepts  solving flow assurance problems related to precipitation of
solids, or emulsion rich flows, cannot be done before appropriate chemistry and flow
models are developed.
• A need for better models !
• The well completion systems become more and more complex 3D devices, which can
only be analysed by 3D CFD.
• CFD is crucial in providing sub-models for more simplified and operational models
• CFD will have a large number of niche applications where there is no alternative to
CFD !
12
The CFD Challenge – Really a need for CFD ?

LedaFlow Q3D: Beyond the limits of full 3D –
but restricted applicability to system assessment ( domain of 1D models)
However, we have still many successful application of 3D ANSYS Fluent !!

 Capping stacks are deployed to stop
oil/gas-release
 They are lowered onto leaking BOP
 The hydrodynamic pressure from the
release can prevent successful landing
of capping stacks
Hydrodynamics loads on capping stacks

Pressure distribution
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 Feasibility of landing can be assessed by CFD, using ANSYS Fluent.
 Weight of capping stack needs to exceed hydrodynamic forces
 Potential hydrodynamic force varies between wells
 We have analysed situations were hydrodynamic force exceeded gravity
Hydrodynamics loads on capping stacks

Subsea bubble plumes & oil spill barriers
Bubble source
Sea current Sea current
Bubble source
Oil slick accumulation
VOF applied to oil spill barriers
PhD: Qingqing Pan

Bubble plumes
Lagrangian modeling of
the plume
New models for:
• Bubble induced
turbulence
• Free surface effects
• Buoyancy modified
turbulence
0 0.1 0.2 0.3 0.4 0.5 0.6
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
r [m]
Ur[m/s]
Ur-standard
Ur-enhanced
Ur-exp.
0 0.1 0.2 0.3 0.4 0.5 0.6
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
r [m]
Uz[m/s]
Uz-standard
Uz-enhanced
Uz-exp.
-0.4 -0.2 0 0.2 0.4 0.6
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
r [m]
alpha
alpha-no-wake
alpha-with-wake
alpha-exp.
Radial flow, close to surface
Axial flow, close to surface
Radial gas distribution. Half
way up.
PhD: Qingqing Pan

Position- (and time-) dependent
Gas-flux density through sea surface
↓
Mass Source at Wall
Radial sea-surface velocity
↓
Moving Wall BC
Inhouse Subsea Plume Model, DeepBlow (Ø. Johansen),
provides input to ANSYS Fluent model
Atmospheric Gas Dispersion Following
Sub-Sea Oil/Gas-Release

Vertical Symmetry-Plane
(Time-dependent Contours of Gas content)
Transient CFD simulations (LES) of gas-cloud development in ANSYS Fluent.
Focus on explosion/fire hazard.
Sensitivity-studies on e.g.:
• Release-rates, depths and directions
• Wind conditions
Videos:
Symmetry plane gas-content contours
3D gas-content isosurface

Introduction/Motivation
Connectors
Gate Valves
Ball Valve
Actuator
Insert Choke
and actuator
Xmas tree
Manifold including
pig loop
Well jumperFlow loop
Hub
Connectors
Gate Valves
Ball Valve
Actuator
Insert Choke
and actuator
Connectors
Gate Valves
Ball Valve
Actuator
Insert Choke
and actuator
Xmas tree
Manifold including
pig loop
Well jumperFlow loop
Hub
Typical subsea production system
Assessing thermal problems due to cold spots
(hydrate risk assessment)

x
y
Outflow, cooling water
x
y
Outflow, cooling water
Experimental setup
Partially insulated pipe with cold spot
Pipe dimensions:
L = 2000 mm
ID = 70 mm
Sections: = 3/8 L and 5/8L
Near horizontal inclination: θ = 2°
PhD: Uduak Mme

-500 0 500 1000 1500 2000
20
25
30
35
40
45
50
55
Time (s)
Temperature(C)
2degExP
2degke-fine grid
88degExp
88degke-fine grid
-500 0 500 1000 1500 2000
20
25
30
35
40
45
50
55
Time (s)
Temperature(C)
2degExP
2degke-fine grid
88degExp
88degke-fine grid
Far field temperatures: k-epsilon model
Close field temperatures: k-epsilon model
PhD: Uduak Mme

-500 0 500 1000 1500 2000
20
25
30
35
40
45
50
55
Time (s)
Temperature(C)
2degExP
2degLES-fine grid
88degExp
88degLES-fine grid
-500 0 500 1000 1500 2000
20
25
30
35
40
45
50
55
Time (s)
Temperature(C)
2degExP
2degLES-fine grid
88degExp
88degLES-fine grid
Far field temperatures: Large Eddy model
Close field temperatures: Large Eddy model
PhD: Uduak Mme

CFD framework for separation
 Overall goal is to develop
simulation framework for
separation processes.
 Phenomena of relevance:
 Relative motion of phases.
 Droplet behaviour in free settling
zone.
 Droplet behaviour in dense packed
layer.
 Droplet-droplet interactions.
 Influence of surfactants on the
above.
 Framework has been realized in
ANSYS FLUENT.
Model now ported to Star CCM+ , who is FACE Partner.

CFD framework for separation
 Basis for model is the n-phase Eulerian model.
 Dispersed phases (e.g. water droplets) are treated by means of
population balance modelling.
 Additional functionality, such as adsorption/desorption kinetics is
implemented as user defined functions and scalar fields.
Phase distribution
(oil and water)
Surfactant distribution
(soluble only in organic phase)

Singing Risers: Motivation
Corrugated pipes have experienced
high levels of vibration (singing/
whistling)

Potential fatigue failure
Explosion risk
The movie is from the courtesy of Statoil, Norway
The picture is from the courtesy of Statoil, Norway

Singing related to vortex shedding on corrugations
Vortices, in the axial plane of the pipe
Flow domain with 128 corrugations:
The predicted vortices along the pipe corrugations indicate the source of the sound

Singing Risers:
Profile of the static pressure in the pipe
• The profile of the static pressure in the pipe indicates and "approximately
standing wave"
Axial Pressure
Contour pressure

• Large classes of flow assurance issues must be handled by 1D models to be
industrially interesting
• Better models of the physics and chemistry is crucial in order to expand the
application of CFD models in flow assurance
• However, many successful CFD applications can be demonstrated:
• Capping stack installation
• Bubble plumes and oil slick accumulation
• Explosion risk – atmospheric gas dispersion
• Thermal dynamics due to cold spots and risk reduction
• Chemistry controlled droplet coalescence and separation
• Aero-acoustical simulations of the singing riser phenomena
• The possibility of developing new models using UDFs has been a major success factor
for ANSYS Fluent
• If good models are provided, CFD will become a very important element in the
toolbox needed for modern flow assurance work
Summary

CFD Modelling of Flow Assurance Challenges

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