Erosion Modeling and Sand Management with ANSYS CFD · PDF fileErosion Modeling and Sand...
Transcript of Erosion Modeling and Sand Management with ANSYS CFD · PDF fileErosion Modeling and Sand...
2011 ANSYS, Inc. June 21, 2012 1
Erosion Modeling and Sand Management with ANSYS CFD
Madhusuden Agrawal
ANSYS Houston
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Particulate modeling in ANSYS CFD
Sand Control and Sand Management
Sand Filtration Sand Transport in pipelines Proppant Placement
Erosion Modeling
Challenges in Erosion Modeling Key components of erosion modeling ANSYS solution for erosion modeling Erosion Module Examples
OUTLINE
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Recap: Particulate Modeling
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Spans wide range of
Length scales Time scales
Physics
Particulate physics Fluid particle interaction Particle size distribution Homogenous and
heterogeneous reaction
Particle structure interaction
Challenges in Particulate Modeling
From: Fundamental of Multiphase Flow, C. E. Brennen
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Particulate Flows Regimes Diluted vs. Dense Flow
es
t12/tcol
10-3 10-1 10-5 10-7
104
102
100
10-2
dilute dense
101 102 100 (x1-x2)/dp
4-way coupling
2-way coupling
1-way coupling
Particles reduce
turbulence
Particles enhance
turbulence negligible effect on
turbulence
102
100
10-2
t12/teddy
Dilute Dense Relative motion between particles Large Small
Particle-particle interaction Weak Strong
Apparent viscosity of the solid phase
Particle-fluid
interactions
Particle-particle
interaction
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Modeling Particulate Flow
Particle Phase
Particle size
P-P Interaction
Fluid-P Interaction
Eulerian
Lagrangian
Sub grid scale
Super grid scale
Hybrid
Resolved
Modeled
Resolved
Modeled
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Platform for Simulating Particulate Systems
ANSYS CFD provides a platform which can adapt to the multi-physics, multi-components and multi-scale configurations of particulate flows and their industrial applications
Eulerian Granular
MPM DDPM-DEM DPM
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Models for Particulate Flows Model Numerical
approach Particle fluid interaction
Particle-Particle interaction
Particle size distribution
DPM Fluid Eulerian Particles Lagrangian
Empirical models for sub-grid particles
Particles are treated as points
Easy to include PSD because of Lagrangian description
DDPM - KTGF Fluid Eulerian Particles Lagrangian
Empirical; sub-grid particles
Approximate P-P interactions determined by granular models
Easy to include PSD because of Lagrangian description
DDPM - DEM Fluid Eulerian Particles Lagrangian
Empirical; sub-grid particles
Accurate determination of P-P interactions.
Can account for all PSD physics accurately including geometric effects
Euler Granular model
Fluid Eulerian Particles Eulerian
Empirical; sub-grid particles
P-P interactions modeled by fluid properties, such as granular pressure, viscosity, drag etc.
Different phases to account for a PSD; when size change operations happen use population balance models
Macroscopic Particle Model
Fluid Eulerian Particles Lagrangian
Interactions determined as part of solution; particles span many fluid cells
Accurate determination of P-P interactions.
Easy to include PSD; if particles become smaller than the mesh, uses an empiricial model
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Sand Control
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Sand is often produced in both onshore and offshore production systems Sand production may be continuous, or sudden
The sediment consists mud, sand and scale picked up during the transport of the oil
Sand Management is important in oil production to ensure system integrity and efficiency
Excessive sand leads to Partial or complete blockage of flowlines Enhanced pipe bottom corrosion and erosion Trapping of pigs Reduced production time and increased maintenance and operating costs
Sedimentation in Oil & Gas
Internal flow of natural gas containing sand particles. particle trajectories are colored in grey. The erosive wear hotspots on the piping is colored out in red.
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Sand control strategies
Preventing formation failure Sand exclusion techniques Sand management
Sand Control
Key areas to understand fundamental nature of sand in the reservoir and the wellbore
Hydraulic fracturing (Proppant transport)
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Sand Exclusion Techniques
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Sand control screen systems
Screens Gravel and frac packing
Example: Sand Filtering Systems in O&G
Bulk process Surface process
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Euler Granular Model
Porous media model with physical velocity formulation Low permeability for the particulate phase May not be able to simulate particle size dependent filtering
Particulate Models
DDPM model with DEM closure for particle-particle interaction Particles can be stopped by reflect or trap boundary conditions Can model particle size effects. Macro Particle Model will physically filter particles through
pores
Modeling Filtration with ANSYS
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Euler Granular Model for Filtration
t = 16 sec.
t = 100 sec.
t = 135 sec.
t = 60 sec.
Solid Phase Volume Faction Contours Velocity Vectors of Solid Phase
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Filter Cake Formation in Vertical Wells Journal of Petroleum and Gas Engineering Vol. 2(7), pp. 146-164, November 2011 Mohd. A. Kabir and Isaac K. Gamwo
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Filtration Modeling Using DDPM/DEM
Filter: Allows particles below a threshold to pass through, Filter represented by a internal boundary condition.
Inlet Outlet
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Particle separation through a filter element at three instances in time. The flow is from left to right. The small particles flow through the holes in the perforated plate and exit the pipe on the right. The plate blocks the bigger particles.
Filtration Modeling using MPM
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Particulate Migration in Gravel Pack
Micro scale Simulation for fine particles transport through pores in gravel pack
Study Permeability alterations in the gravel pack due to fine particles entrainments, transport and deposition
Filtration of fine particles
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Sand Transport
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Example: Sand Transport in Pipelines
Sand-Water slurry flow in horizontal pipe Pipe diameter D = 0.0505m Pipe length L = 4m
30% volume loading Four Different Slurry Flow Rates DDPM with DEM Collision
Particle staggering for surface injection
Low value of Spring Constant as buoyancy force is important.
Almost 3 millions parcels
Gravity
Slurry Velocity (m/s)
dp/dx (Pa/m)
SRC: Saskatchewan Research Council
Expected Results
To be published in collaboration with Shell
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Mean Static Pressure is plotted on the line coinciding with the axis of the pipe.
dp/dx is calculated between z=3m to z=4m as it varies linearly in this range for all the cases.
Results: Pressure Gradient
Slurry Velocity (m/s)
dp/dx (Pa/m)
dp/dx pipe length dp/dx slurry velocity
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Reduced particle time step size to more accurately model collisions.
Little difference in predicted pressure gradient.
Considerable increase in simulation time.
Effect of particle time step size Mixture Velocity (m/s) Baseline Particle Time
Step Size (s) Smaller Particle Time Step Size (s)
0.7 2.50E-04 1.0E-04
1.42 1.00E-04 4.00E-05
3 5.00E-05 2.50E-05
Slurry Velocity (m/s)
dp/dx (Pa/m)
dp/dx slurry velocity
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It is important to keep particles suspended Critical flow velocity which keeps sand particles moving along
the pipe depends on Liquid holdup and flow rates, Pipe diameter, Fluids properties, Sand
properties, Pipe inclination angle
Many correlations exists for solids transportation in multiphase flow
Based on experiments for single phase flow on small pipes
Lot of variability in measurements
Sand Transport in Pipelines
Hjulstrom Diagram
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Transport paths Traction or full contact
sand rolling or sliding across bottom
Saltation sand hop/ bounce along bottom
Bedload combined traction and saltation
Suspended load sand carried without settling
upward forces > downwarde
Sand Transport in Pipelines
All these paths for sand transport can be addressed by Particulate modeling in ANSYS CFD.