Loading in 5 sec....

Simulation of single phase reactive transport on pore-scale imagesPowerPoint Presentation

Simulation of single phase reactive transport on pore-scale images

Download Presentation

Simulation of single phase reactive transport on pore-scale images

Loading in 2 Seconds...

- 128 Views
- Uploaded on
- Presentation posted in: General

Simulation of single phase reactive transport on pore-scale images

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Simulation of single phase reactive transport on pore-scale images

Zaki Al Nahari, Branko Bijeljic, Martin Blunt

- Motivation
- Modelling reactive transport
- Geometry & flow field
- Transport
- Reaction rate
- Validation against analytical solutions
- Results
- Future work

- Contaminant transport:
- Industrial waste
- Biodegradation of landfills…etc

- Carbon capture and storage:
- Acidic brine.
- Over time, potential dissolution and/or mineral trapping.

- However….
- Uncertainty in reaction rates
- The field <<in the lab.

- No fundamental basis to integrate flow, transport and reaction in porous media.

- Uncertainty in reaction rates

- Micro-CT scanner uses X-rays to produce a sequence of cross-sectional tomography images of rocks in high resolution (µm)
- To obtain the pressure and velocity field at the pore-scale, the Navier-Stokes equations are fundamental approach for the flow simulation.
- Momentum balance
- Mass balance

- For incompressible laminar flow, Stokes equations can be used:

Pore space

Velocity field

Pressure field

- Track the motion of particles for every time step by:
- Advection along streamlines using a novel formulation accounting for zero flow at solid boundaries. It is based on a semi-analytical approach: no further numerical errors once the flow is computed at cell faces.
- Diffusion using random walk. It is a series of spatial random displacements that define the particle transitions by diffusion.

- Bimolecular reaction
- A + B → C
- The reaction occurs if two conditions are met:
- Distance between reactant is less than or equal the diffusive step ( )
- If there is more than one possible reactant, the reaction will be with nearest reactant..

- The probability of reaction (P) as a function of reaction rate constant (k):

- Distance between reactant is less than or equal the diffusive step ( )

- Reaction in a bulk system against the analytical solution:
- no porous medium
- no flow

- Analytical solution for concentration in bulk with no flow.

- Number of Voxels:
- Case 1: 10×10×10
- Case 2: 20×20×20
- Case 3: 50×50×50

- Number of particles:
- A= 100,000 density= 0.8 Np/voxel
- B= 50,000 density= 0.4 Np/voxel

- Parameters:
- Dm= 7.02x10-11 m2/s
- k= 2.3x109 M-1.s-1
- Time step sizes:
- Δt= 10-3 s P= 3.335×10-3
- Δt= 10-4 s P= 1.055×10-2
- Δt= 10-5 s P= 3.335×10-2

Δt= 10-3 s

Δt= 10-4 s

Δt= 10-5 s

Δt= 10-3 s

Δt= 10-4 s

Δt= 10-5 s

Δt= 10-3 s

Δt= 10-4 s

- Berea Sandstone
- Number of Voxels: 300×300×300
- Number of particles:
- A= 400,000 density= 1.481×10-2 Np/voxel
- B= 200,000 density= 7.407×10-3 Np/voxel

- Pe= 200

- Case 1: Parallel injection
- Both reactants (A and B) injected at the top and bottom half of the inlet.

- Case 2: Injection
- Reactant, A, is resident in the pore space, while reactant B is injected at the inlet face.

2-D

3-D

y (μm)

x (μm)

y (μm)

z (μm)

x (μm)

2-D

3-D

y (μm)

x (μm)

C= 1087

y (μm)

z (μm)

x (μm)

2-D

3-D

y (μm)

x (μm)

y (μm)

z (μm)

x (μm)

2-D

3-D

y (μm)

x (μm)

C= 713

y (μm)

z (μm)

x (μm)

- Fluid-Fluid interactions
- Predict experimental data; Gramling et al. (2002)

- Fluid-solid interactions
- Dissolution and/or precipitation
- Change the pore space geometry and hence the flow field over time

Gramling et al. (2002)

Acknowledgements:

Dr. Branko Bijeljic and Prof. Martin Blunt

Emirates Foundation for funding this project

(0, y, z)

(0, y, z)

Image

Mirror

(x, y, z)

(x, y, z)

(x, y, 0)

(0, y, 0)

(0, y, 0)

(x, y, 0)

Image + Mirror

(x, 0, z)

(0, 0, z)

(0, 0, z)

(x, 0, z)

(0, 0, 0)

(x, 0, 0)

(0, 0, 0)

(x, 0, 0)

(0, y, z)

(0, y, z)

(0, y, z)

(x, y, z)

(x, y, z)

(x, y, z)

(0, y, 0)

(0, y, 0)

(0, y, 0)

(2x, y, 0)

(2x, y, 0)

(2x, y, 0)

Number

Images

Image 1

Image 2

(0, 0, z)

(0, 0, z)

(0, 0, z)

(2x, 0, z)

(2x, 0, z)

(2x, 0, z)

(0, 0, 0)

(0, 0, 0)

(0, 0, 0)

(2x, 0, 0)

(2x, 0, 0)

(2x, 0, 0)

- Couple transport with reactions

- General Pollock’s algorithm with no solid boundaries:
- To obtain the velocity at position inside a voxel
- To estimate the minimum time for a particle to exit a voxel:
- To determine the exit position of a particle in the neighbouring voxel

Mostaghimi et al. (2010)

6 algorithms

3 algorithms

8 algorithms

12 algorithms

3 algorithms

12 algorithms

12 algorithms

Mostaghimi et al. (2010)

- Particles Motion:
- Advection
- Diffusion.

- To measure the spreading of particles in porous media
- Peclet number

Bijeljic and Blunt (2006)

- Assumption:
- Temperature is constant
- CO2 is dissolved in brine.
- No vaporisation process.
- No biogeological reactions

- Carbonate dissolution and precipitation kinetic constant rate are taken from Chou et al. (1989).

- Activity Coefficients are estimated using Harvie-Moller-Weare (HMV) methods (Bethke, 1996).

- Nigrini (1970) approach are used to estimate diffusion coefficient