Obtaining relative permeability curves from CT scan images and running drainage simulations

[EnochMayor]

Hi everyone,

I am currently working on a project that involves obtaining relative permeability curves from CT scan images during drainage simulations. I am seeking assistance from the community to help me with the following tasks:

1. Extracting relevant data from CT scan images.
2. Running drainage simulations and converting the extracted data into relative permeability curves.

To provide some context, my project aims to analyze the fluid flow behavior in porous media using CT scan images. I have access to a dataset of CT scan images of a porous material, and I want to extract the relevant information from these images to obtain the relative permeability curves.

My challenge is currently implementing the workflow I found going through the documentation where. Specifically specifying which pores have boundary conditions. I am currently stuck and keep getting Keyword Error: pore.left

`im = ps.io.openpnm_to_im(pore_net, max_dim=200)
im.shape
fig, ax = plt.subplots(figsize=(5, 5))
plt.imshow(im)
pore_net['pore.diameter'] = pore_net['pore.inscribed_diameter']
pore_net['throat.diameter'] = pore_net['throat.inscribed_diameter']
pore_net['throat.spacing'] = pore_net['throat.total_length']
pore_net.add_model(propname='throat.hydraulic_size_factors',
model=op.models.geometry.hydraulic_size_factors.spheres_and_cylinders, regen_mode='deferred')
pore_net.add_model(propname='throat.diameter',
model=op.models.geometry.throat_size.from_neighbor_pores, mode = 'min',)
pore_net.add_model(propname='pore.diameter',
model=op.models.geometry.pore_size.largest_sphere)
pore_net.regenerate_models()
h = op.utils.check_network_health(pore_net)
print(h)
op.topotools.trim(network=pore_net, pores=h['trim_pores'])
h = op.utils.check_network_health(pore_net)
print(h)

#Define phase objects
H2 = op.phase.Phase(network=pore_net)
#gas['pore.diffusivity'] = 1.0
H2['pore.viscosity'] = 0.000009
H2['pore.surface_tension'] = 0.072
H2['pore.contact_angle'] = 150.0
H2['pore.density'] = 0.08375 # Kg/m^3
H2['pore.molar_density'] = 41.875 #mol/m^3
H2['pore.thermal_conductivity'] = 0.03
H2['pore.vapor_pressure'] = 9868.42

f = op.models.physics.capillary_pressure.washburn
H2.add_model(propname='throat.entry_pressure',
model=f,
surface_tension='throat.surface_tension',
contact_angle='throat.contact_angle',
diameter='throat.diameter',)

#Checks
pore_net.labels()
pore_net.BC()

pore_net['throat.hydraulic_size_factors']

#H2.add_model_collection(op.models.collections.phase.air)
H2.add_model_collection(op.models.collections.physics.basic)
H2.regenerate_models()

water = op.phase.Water(network=pore_net, name='water')
H2['pore.vapor_pressure']
water.add_model_collection(op.models.collections.phase.water)
water.add_model_collection(op.models.collections.physics.basic)
water.regenerate_models()

#Pore Scale Drainage

ip = op.algorithms.InvasionPercolation(network=pore_net, phase=H2)
print (ip)

ip.set_inlet_BC(pores=pore_net.pores('left'))
ip.run(pressures = 20)
Finlets=([Finlets_init[x] for x in range(0, len(Finlets_init), 2)])
#ip.set_inlet_BC(pores=Finlets)
#ip.run()
`

[jgostick]

That error means that you don't have any pore labeled 'pore.left'. You can do print(pore_net) to see which labels are defined. We switched to using 'xmin' and 'xmax' to represent 'pore.left' and 'pore.right' since it's more clear what they mean.

[EnochMayor]

Thank you for the swift reply professor, print(pore_net) shows that my network (extracted using the snow2 function) does not contain xmin or xmax.

as compared to openpnm simple cubic network model