def test_chemicaltransport_step(num_regression):
nx, ny, nz = 5, 5, 5 # number of cells along x, y, and z
nsteps = 10 # number of time steps
velocity = fire.Constant([1.0e-2, 0.0,
0.0]) # the velocity (in units of m/s)
diffusion = fire.Constant(
1.0e-4) # the diffusion coefficient (in units of m2/s)
dt = 1.0 # the time step (in units of s)
T = 60.0 + 273.15 # the temperature (in units of K)
P = 100 * 1e5 # the pressure (in units of Pa)
mesh = fire.UnitCubeMesh(nx, ny, nz)
V = fire.FunctionSpace(mesh, "CG", 1)
# Initialise the database
database = rkt.Database("supcrt98.xml")
# Initialise the chemical editor
editor = rkt.ChemicalEditor(database)
editor.addAqueousPhase(
"H2O(l) H+ OH- Na+ Cl- Ca++ Mg++ HCO3- CO2(aq) CO3--")
editor.addMineralPhase("Quartz")
editor.addMineralPhase("Calcite")
editor.addMineralPhase("Dolomite")
# Initialise the chemical system
system = rkt.ChemicalSystem(editor)
# Define the initial condition of the reactive transport modeling problem
problem_ic = rkt.EquilibriumProblem(system)
problem_ic.setTemperature(T)
problem_ic.setPressure(P)
problem_ic.add("H2O", 1.0, "kg")
problem_ic.add("NaCl", 0.7, "mol")
problem_ic.add("CaCO3", 10, "mol")
problem_ic.add("SiO2", 10, "mol")
# Define the boundary condition of the reactive transport modeling problem
problem_bc = rkt.EquilibriumProblem(system)
problem_bc.setTemperature(T)
problem_bc.setPressure(P)
problem_bc.add("H2O", 1.0, "kg")
problem_bc.add("NaCl", 0.90, "mol")
problem_bc.add("MgCl2", 0.05, "mol")
problem_bc.add("CaCl2", 0.01, "mol")
problem_bc.add("CO2", 0.75, "mol")
# Calculate the equilibrium states for the initial and boundary conditions
state_ic = rkt.equilibrate(problem_ic)
state_bc = rkt.equilibrate(problem_bc)
# Scale the volumes of the phases in the initial condition such that their sum is 1 m3
state_ic.scalePhaseVolume("Aqueous", 0.1, "m3")
state_ic.scalePhaseVolume("Quartz", 0.882, "m3")
state_ic.scalePhaseVolume("Calcite", 0.018, "m3")
# Scale the volume of the boundary equilibrium state to 1 m3
state_bc.scaleVolume(1.0)
# Initialise the chemical field
field = rok.ChemicalField(system, V)
field.fill(state_ic)
# Initialize the chemical transport solver
transport = rok.ChemicalTransportSolver(field)
transport.addBoundaryCondition(state_bc, 1) # 1 means left side
transport.setVelocity([velocity])
transport.setDiffusion([diffusion])
species_names_for_output = [
"Ca++",
"Mg++",
"Calcite",
"Dolomite",
"CO2(aq)",
"HCO3-",
"Cl-",
"H2O(l)",
]
element_names_for_output = ["H", "O", "C", "Ca", "Mg", "Na", "Cl"]
species_amount_functions = [
fire.Function(V, name=name) for name in species_names_for_output
]
element_amount_functions = [
fire.Function(V, name=name) for name in element_names_for_output
]
step = 0
species_data = []
element_data = []
while step <= nsteps:
transport.step(field, dt)
# For each selected species, output its molar amounts
for f in species_amount_functions:
f.assign(field.speciesAmount(f.name()))
species_data.append(f.dat.data)
# For each selected species, output its molar amounts
for f in element_amount_functions:
f.assign(field.elementAmountInPhase(f.name(), "Aqueous"))
element_data.append(f.dat.data)
step += 1
species_data = {
"n({})(step={})".format(name, i): u
for i, (name,
u) in enumerate(zip(species_names_for_output, species_data))
}
element_data = {
"b({})(step={})".format(name, i): u
for i, (name,
u) in enumerate(zip(element_names_for_output, element_data))
}
data = {**species_data, **element_data}
num_regression.check(data)
def test_ternary_c1_c4_c10_bips_setup():
"""
This is a ternary example from Whitson monograph. Retrieved from Problem 18 in
Appendix B. This test compares the results defining BIPs as 'zero' matrix with
the result without BIPs setup. Such results should be the same.
.. reference:
Whitson, C. H., & Brulé, M. R. (2000). Phase behavior (Vol. 20).
Richardson, TX: Henry L. Doherty Memorial Fund of AIME, Society of Petroleum Engineers.
"""
temperature = 280 # degF
pressure = 500 # psi
composition = np.array([0.5, 0.42, 0.08]) # molar fractions
db = reaktoro.Database(str(get_test_data_dir() / 'hydrocarbons.xml'))
editor = reaktoro.ChemicalEditor(db)
editor_bips = reaktoro.ChemicalEditor(db)
gaseous_species = ["C1(g)", "C4(g)", "C10(g)"]
oil_species = ["C1(liq)", "C4(liq)", "C10(liq)"]
eos_params = reaktoro.CubicEOSParams(
model=reaktoro.CubicEOSModel.PengRobinson,
phase_identification_method=reaktoro.PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod,
)
editor.addGaseousPhase(gaseous_species).setChemicalModelCubicEOS(
eos_params)
editor.addLiquidPhase(oil_species).setChemicalModelCubicEOS(eos_params)
def calculate_bips(T):
zero = 0.0
k = [[zero, zero, zero], [zero, zero, zero], [zero, zero, zero]]
bips = reaktoro.BinaryInteractionParams(k)
return bips
eos_params_bips = reaktoro.CubicEOSParams(
model=reaktoro.CubicEOSModel.PengRobinson,
phase_identification_method=reaktoro.PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod,
binary_interaction_values=calculate_bips)
editor_bips.addGaseousPhase(gaseous_species).setChemicalModelCubicEOS(
eos_params_bips)
editor_bips.addLiquidPhase(oil_species).setChemicalModelCubicEOS(
eos_params_bips)
system = reaktoro.ChemicalSystem(editor)
system_bips = reaktoro.ChemicalSystem(editor_bips)
problem = reaktoro.EquilibriumProblem(system)
problem_bips = reaktoro.EquilibriumProblem(system_bips)
problem.setTemperature(temperature, 'degF')
problem.setPressure(pressure, 'psi')
problem.setElementAmount('C1', composition[0])
problem.setElementAmount('C4', composition[1])
problem.setElementAmount('C10', composition[2])
problem_bips.setTemperature(temperature, 'degF')
problem_bips.setPressure(pressure, 'psi')
problem_bips.setElementAmount('C1', composition[0])
problem_bips.setElementAmount('C4', composition[1])
problem_bips.setElementAmount('C10', composition[2])
# Custom initial guess below. This is necessary for hydrocarbon mixtures.
state = reaktoro.ChemicalState(system)
state.setSpeciesAmounts(0.001) # start will all having 0.001 moles
state.setSpeciesAmount(
"C1(g)", composition[0]) # overwrite amount of C1(g) (same below)
state.setSpeciesAmount("C4(g)", composition[1])
state.setSpeciesAmount("C10(g)", composition[2])
state_bips = reaktoro.ChemicalState(system_bips)
state_bips.setSpeciesAmounts(0.001)
state_bips.setSpeciesAmount("C1(g)", composition[0])
state_bips.setSpeciesAmount("C4(g)", composition[1])
state_bips.setSpeciesAmount("C10(g)", composition[2])
options = reaktoro.EquilibriumOptions()
options.hessian = reaktoro.GibbsHessian.Exact
solver = reaktoro.EquilibriumSolver(system)
solver.setOptions(options)
result = solver.solve(state, problem)
solver_bips = reaktoro.EquilibriumSolver(system_bips)
solver_bips.setOptions(options)
result_bips = solver_bips.solve(state_bips, problem_bips)
assert result.optimum.succeeded
assert result_bips.optimum.succeeded
# Compare results with and without setting BIPs
molar_base = state.phaseAmount('Gaseous') + state.phaseAmount('Liquid')
gas_phase_molar_fraction = state.phaseAmount('Gaseous') / molar_base
liquid_phase_molar_fraction = state.phaseAmount('Liquid') / molar_base
phase_fractions = np.array(
[gas_phase_molar_fraction, liquid_phase_molar_fraction])
molar_base_bips = state_bips.phaseAmount(
'Gaseous') + state_bips.phaseAmount('Liquid')
gas_phase_molar_fraction_bips = state_bips.phaseAmount(
'Gaseous') / molar_base_bips
liquid_phase_molar_fraction_bips = state_bips.phaseAmount(
'Liquid') / molar_base_bips
phase_fractions_bips = np.array(
[gas_phase_molar_fraction_bips, liquid_phase_molar_fraction_bips])
assert phase_fractions == pytest.approx(phase_fractions_bips)
def test_equilibrium_CH4_CO2_pedersen():
"""
This case is gathered from Pedersen book [1]. It is a C1-CO2 mixture using
SRK as Cubic EOS. In P = 20 bar and T = -42 degC, it results in a LV equilibrium.
This test compare the results from the book with Reaktoro's outcomes. The main
goal is to check if BIPs setup is working properly. The case is given in Table 6.3
in the Chapter 6 of [1]. The BIP value is given in the Chapter 4, Table 4.2.
.. reference:
[1] Pedersen, K. S., Christensen, P. L., & Shaikh, J. A. (2014). Phase behavior
of petroleum reservoir fluids. CRC press.
"""
db = reaktoro.Database("supcrt98.xml")
editor = reaktoro.ChemicalEditor(db)
def calculate_bips(T):
k_00 = k_11 = 0.0
k_01 = k_10 = 0.12
k = [
[k_00, k_01],
[k_10, k_11],
]
bips = reaktoro.BinaryInteractionParams(k)
return bips
eos_params = reaktoro.CubicEOSParams(
model=reaktoro.CubicEOSModel.SoaveRedlichKwong,
phase_identification_method=reaktoro.PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod,
binary_interaction_values=calculate_bips)
editor.addGaseousPhase(["CH4(g)",
"CO2(g)"]).setChemicalModelCubicEOS(eos_params)
editor.addLiquidPhase(["CH4(liq)",
"CO2(liq)"]).setChemicalModelCubicEOS(eos_params)
system = reaktoro.ChemicalSystem(editor)
problem = reaktoro.EquilibriumProblem(system)
temperature = -42.0 # degC
pressure = 20.0 # bar
problem.setTemperature(temperature, "degC")
problem.setPressure(pressure, "bar")
problem.add("CH4(g)", 0.4, "mol")
problem.add("CO2(g)", 0.6, "mol")
state = reaktoro.ChemicalState(system)
state.setSpeciesAmounts(0.001) # start will all having 0.001 moles
state.setSpeciesAmount("CH4(g)",
0.4) # overwrite amount of C1(g) (same below)
state.setSpeciesAmount("CO2(g)", 0.6)
solver = reaktoro.EquilibriumSolver(problem.system())
options = reaktoro.EquilibriumOptions()
options.hessian = reaktoro.GibbsHessian.Exact
solver.setOptions(options)
result = solver.solve(state, problem)
assert result.optimum.succeeded
# Compare phases molar fractions
molar_base = state.phaseAmount('Gaseous') + state.phaseAmount('Liquid')
gas_phase_molar_fraction = state.phaseAmount('Gaseous') / molar_base
liquid_phase_molar_fraction = state.phaseAmount('Liquid') / molar_base
phase_fractions = np.array(
[liquid_phase_molar_fraction, gas_phase_molar_fraction])
F_expected = np.array([0.197, 0.803])
assert phase_fractions == pytest.approx(F_expected, rel=2e-2)
ch4_gas_fraction = state.speciesAmount('CH4(g)') / phase_fractions[1]
co2_gas_fraction = state.speciesAmount('CO2(g)') / phase_fractions[1]
equilibrium_gas_composition = np.array(
[ch4_gas_fraction, co2_gas_fraction])
expected_gas_composition = np.array([0.488, 0.512])
assert equilibrium_gas_composition == pytest.approx(
expected_gas_composition,
rel=1e-2 # 1% rel error
)
ch4_liq_fraction = state.speciesAmount('CH4(liq)') / phase_fractions[0]
co2_liq_fraction = state.speciesAmount('CO2(liq)') / phase_fractions[0]
equilibrium_liq_composition = np.array(
[ch4_liq_fraction, co2_liq_fraction])
expected_liq_composition = np.array([0.042, 0.958])
assert equilibrium_liq_composition == pytest.approx(
expected_liq_composition,
rel=1e-2 # 1% rel error
)
def test_ternary_c1_c4_c10_mixture(P, T, F_expected, x_expected, y_expected):
"""
This is a ternary example from Whitson monograph. Retrieved from Problem 18 in
Appendix B.
.. reference:
Whitson, C. H., & Brulé, M. R. (2000). Phase behavior (Vol. 20).
Richardson, TX: Henry L. Doherty Memorial Fund of AIME, Society of Petroleum Engineers.
"""
temperature = T # degF
pressure = P # psi
composition = np.array([0.5, 0.42, 0.08]) # molar fractions
db = reaktoro.Database('supcrt07.xml')
_add_hydrocarbons_to_database(db)
editor = reaktoro.ChemicalEditor(db)
gaseous_species = ["C1(g)", "C4(g)", "C10(g)"]
oil_species = ["C1(liq)", "C4(liq)", "C10(liq)"]
eos_params = reaktoro.CubicEOSParams(
model=reaktoro.CubicEOSModel.PengRobinson,
phase_identification_method=reaktoro.PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod,
)
editor.addGaseousPhase(gaseous_species).setChemicalModelCubicEOS(
eos_params)
editor.addLiquidPhase(oil_species).setChemicalModelCubicEOS(eos_params)
system = reaktoro.ChemicalSystem(editor)
problem = reaktoro.EquilibriumProblem(system)
problem.setTemperature(temperature, 'degF')
problem.setPressure(pressure, 'psi')
problem.setElementAmount('C1', composition[0])
problem.setElementAmount('C4', composition[1])
problem.setElementAmount('C10', composition[2])
# Custom initial guess below. This is necessary for hydrocarbon mixtures.
state = reaktoro.ChemicalState(system)
state.setSpeciesAmounts(0.001) # start will all having 0.001 moles
state.setSpeciesAmount(
"C1(g)", composition[0]) # overwrite amount of C1(g) (same below)
state.setSpeciesAmount("C4(g)", composition[1])
state.setSpeciesAmount("C10(g)", composition[2])
options = reaktoro.EquilibriumOptions()
options.hessian = reaktoro.GibbsHessian.Exact
solver = reaktoro.EquilibriumSolver(system)
solver.setOptions(options)
result = solver.solve(state, problem)
assert result.optimum.succeeded
molar_base = state.phaseAmount('Gaseous') + state.phaseAmount('Liquid')
gas_phase_molar_fraction = state.phaseAmount('Gaseous') / molar_base
liquid_molar_fraction = state.phaseAmount('Liquid') / molar_base
phase_fractions = np.array(
[gas_phase_molar_fraction, liquid_molar_fraction])
assert phase_fractions == pytest.approx(F_expected, rel=5e-3)
c1_gas_fraction = state.speciesAmount('C1(g)') / phase_fractions[0]
c4_gas_fraction = state.speciesAmount('C4(g)') / phase_fractions[0]
c10_gas_fraction = state.speciesAmount('C10(g)') / phase_fractions[0]
equilibrium_gas_composition = np.array(
[c1_gas_fraction, c4_gas_fraction, c10_gas_fraction])
assert equilibrium_gas_composition == pytest.approx(y_expected, rel=2e-2)
c1_liq_fraction = state.speciesAmount('C1(liq)') / phase_fractions[1]
c4_liq_fraction = state.speciesAmount('C4(liq)') / phase_fractions[1]
c10_liq_fraction = state.speciesAmount('C10(liq)') / phase_fractions[1]
equilibrium_liq_composition = np.array(
[c1_liq_fraction, c4_liq_fraction, c10_liq_fraction])
assert equilibrium_liq_composition == pytest.approx(x_expected, rel=2e-2)
mesh = fire.UnitSquareMesh(nx, ny, quadrilateral=True)
V = fire.FunctionSpace(mesh, "CG", 1)
# Initialise the database
database = rkt.Database("supcrt98.xml")
# Initialise the chemical editor
editor = rkt.ChemicalEditor(database)
editor.addAqueousPhase("H2O(l) H+ OH- Na+ Cl- Ca++ Mg++ HCO3- CO2(aq) CO3--")
editor.addMineralPhase("Quartz")
editor.addMineralPhase("Calcite")
editor.addMineralPhase("Dolomite")
# Initialise the chemical system
system = rkt.ChemicalSystem(editor)
# Define the initial condition of the reactive transport modeling problem
problem_ic = rkt.EquilibriumProblem(system)
problem_ic.setTemperature(T)
problem_ic.setPressure(P)
problem_ic.add("H2O", 1.0, "kg")
problem_ic.add("NaCl", 0.7, "mol")
problem_ic.add("CaCO3", 10, "mol")
problem_ic.add("SiO2", 10, "mol")
# Define the boundary condition of the reactive transport modeling problem
problem_bc = rkt.EquilibriumProblem(system)
problem_bc.setTemperature(T)
problem_bc.setPressure(P)
problem_bc.add("H2O", 1.0, "kg")
def test_convergence_with_liquid_phase(num_regression):
temperature = 343.15
pressure = 1323.9767e5
db = reaktoro.Database('supcrt07.xml')
_add_lumped_oil_to_database(db)
editor = reaktoro.ChemicalEditor(db)
aqueous_species = [
"H2O(l)",
"CO2(aq)",
"HCO3-",
"CO3--",
"H2S(aq)",
"HS-",
"SO4--",
"Ca++",
"Na+",
"Cl-",
"Fe++",
"Ba++",
"Sr++",
]
gaseous_species = ["CO2(g)", "H2S(g)", "CH4(g)"]
oil_species = ["H2S(liq)", "CO2(liq)", "LumpedOil(liq)"]
minerals = [
"Anhydrite", "Barite", "Calcite", "Celestite", "Siderite", "Pyrrhotite"
]
editor.addAqueousPhase(aqueous_species)
editor.addGaseousPhase(gaseous_species)
editor.addLiquidPhase(oil_species)
for mineral in minerals:
editor.addMineralPhase(mineral)
system = reaktoro.ChemicalSystem(editor)
problem = reaktoro.EquilibriumProblem(system)
problem.setTemperature(temperature)
problem.setPressure(pressure)
state = reaktoro.ChemicalState(system)
state.setTemperature(temperature)
state.setPressure(pressure)
# AQUEOUS
state.setSpeciesAmount("H2O(l)", 1047530951.9776191)
state.setSpeciesAmount("CO2(aq)", 20774.560623553392)
state.setSpeciesAmount("HCO3-", 282912.10935910186)
state.setSpeciesAmount("CO3--", 1483.0702563458142)
state.setSpeciesAmount("H2S(aq)", 12166.740676127629)
state.setSpeciesAmount("HS-", 41503.521359359736)
state.setSpeciesAmount("SO4--", 0.00000000000000000)
state.setSpeciesAmount("Ca++", 182556.98986975398)
state.setSpeciesAmount("Na+", 8919454.7940101717)
state.setSpeciesAmount("Cl-", 8955756.8340308685)
state.setSpeciesAmount("Fe++", 0.00000000000000000)
state.setSpeciesAmount("Ba++", 13319.520269138628)
state.setSpeciesAmount("Sr++", 20875.710568363389)
# MINERAL
state.setSpeciesAmount("Calcite", 999131754.50533485)
state.setSpeciesAmount("Anhydrite", 0.00000000000000000)
state.setSpeciesAmount("Barite", 0.00000000000000000)
state.setSpeciesAmount("Celestite", 0.00000000000000000)
state.setSpeciesAmount("Siderite", 6732617546.7550077)
state.setSpeciesAmount("Pyrrhotite", 0.00000000000000000)
# GASEOUS
state.setSpeciesAmount("CO2(g)", 574511.37111462699)
state.setSpeciesAmount("H2S(g)", 13303.310614909715)
state.setSpeciesAmount("CH4(g)", 700402204.48213911)
# LIQUID
state.setSpeciesAmount("CO2(liq)", 821887.77968393208)
state.setSpeciesAmount("H2S(liq)", 240596.16100715694)
state.setSpeciesAmount("LumpedOil(liq)", 12676647027.415014)
problem.addState(state)
solver = reaktoro.EquilibriumSolver(system)
state = reaktoro.ChemicalState(system)
converged = solver.solve(state, problem).optimum.succeeded
n = state.speciesAmounts()
b = state.elementAmounts()
output = {}
output["Element amounts [mol]"] = np.asarray(b)
output["Species amounts [mol]"] = n
num_regression.check(output)
assert converged