def test_deprecated_kroend():
"""Testing that the deprecated scalrecommendation can take
both kroend and krogend/krowend"""
low_krowend = dict(LOW_SAMPLE_LET)
low_krowend["krowend"] = low_krowend["kroend"]
del low_krowend["kroend"]
base_krowend = dict(BASE_SAMPLE_LET)
base_krowend["krowend"] = base_krowend["kroend"]
del base_krowend["kroend"]
high_krowend = dict(HIGH_SAMPLE_LET)
high_krowend["krowend"] = high_krowend["kroend"]
del high_krowend["kroend"]
rec = SCALrecommendation(low_krowend,
base_krowend,
high_krowend,
"foo",
h=0.1)
rec.add_simple_J() # Add default pc curve
interpolant = rec.interpolate(0.1, 0, h=0.1)
check_table(interpolant.wateroil.table)
print(interpolant.SWOF())
def test_make_scalrecommendation():
"""Test that we can make scal recommendation objects
from three WaterOilGas objects"""
low = PyscalFactory.create_water_oil_gas(LOW_SAMPLE_LET)
base = PyscalFactory.create_water_oil_gas(BASE_SAMPLE_LET)
high = PyscalFactory.create_water_oil_gas(HIGH_SAMPLE_LET)
rec = SCALrecommendation(low, base, high)
interpolant = rec.interpolate(-0.5, h=0.2)
check_table(interpolant.wateroil.table)
check_table(interpolant.gasoil.table)
# Check preservation of tags.
swof = interpolant.SWOF()
assert "SCAL recommendation interpolation to -0.5" in swof
assert "SCAL recommendation interpolation to -0.5" in interpolant.SGOF()
assert "SCAL recommendation interpolation to -0.5" in interpolant.SWFN()
assert "SCAL recommendation interpolation to -0.5" in interpolant.SOF3()
assert "SCAL recommendation interpolation to -0.5" in interpolant.SGFN()
assert swof.count("SATNUM X") == 1
assert interpolant.SOF3().count("SATNUM X") == 1
# Check different comment when different interpolation parameter:
interpolant = rec.interpolate(-0.777, 0.888, h=0.2)
assert "SCAL recommendation interpolation to -0.777" in interpolant.SWOF()
assert "SCAL recommendation interpolation to 0.888" in interpolant.SGOF()
def test_interpolation_deprecated(param_wo, param_go):
"""Testing deprecated functionality. Remove
this test function when SCALrecommendation class is updated"""
rec = SCALrecommendation(
LOW_SAMPLE_LET, BASE_SAMPLE_LET, HIGH_SAMPLE_LET, "foo", h=0.1
)
rec.add_simple_J() # Add default pc curve
assert rec.type == WaterOilGas
try:
interpolant = rec.interpolate(param_wo, param_go, h=0.1)
except AssertionError:
return
check_table(interpolant.wateroil.table)
check_table(interpolant.gasoil.table)
assert len(interpolant.gasoil.SGOF()) > 100
assert len(interpolant.gasoil.SGFN()) > 100
assert len(interpolant.wateroil.SWFN()) > 100
assert len(interpolant.SOF3()) > 100
assert len(interpolant.wateroil.SWOF()) > 100
if not interpolant.threephaseconsistency():
print(interpolant.wateroil.SWOF())
print(interpolant.gasoil.SGOF())
assert interpolant.threephaseconsistency()
def interpolatetest():
rec = SCALrecommendation(lowsample(), basesample(), highsample(), "foo", h=0.05)
rec.add_simple_J() # Add default pc curve
# print rec.low.wateroil.table
interpolant = rec.interpolate(0.3, parameter2=-0.9, h=0.05)
print(interpolant.wateroil.SWOF())
print(interpolant.gasoil.SGOF())
print("Consistency check: ", end=" ")
print(interpolant.threephaseconsistency())
def create_scal_recommendation(params, tag="", h=None):
"""
Set up a SCAL recommendation curve set from input as a
dictionary of dictionary.
The keys in in the dictionary *must* be "low", "base" and "high".
The value for "low" must be a new dictionary with saturation
endpoints and LET/Corey parameters, as you would feed it to
the create_water_oil_gas() factory function, and then similarly
for base and high.
For oil-water only, you may omit the parameters for gas-oil.
"""
if not isinstance(params, dict):
raise ValueError("Input must be a dictionary (of dictionaries)")
# For case insensitiveness, all keys are converted to lower case:
params = {key.lower(): value for (key, value) in params.items()}
if "low" not in params:
raise ValueError('"low" case not supplied')
if "base" not in params:
raise ValueError('"base" case not supplied')
if "high" not in params:
raise ValueError('"high" case not supplied')
if not all([isinstance(x, dict) for x in params.values()]):
raise ValueError(
"All values in parameter dict must be dictionaries")
check_deprecated(params["low"])
check_deprecated(params["base"])
check_deprecated(params["high"])
errored = False
if h is not None:
params["low"]["h"] = h
params["base"]["h"] = h
params["high"]["h"] = h
wog_low = PyscalFactory.create_water_oil_gas(params["low"])
if not wog_low.selfcheck():
logger.error("Incomplete parameter set for low case")
errored = True
wog_base = PyscalFactory.create_water_oil_gas(params["base"])
if not wog_base.selfcheck():
logger.error("Incomplete parameter set for base case")
errored = True
wog_high = PyscalFactory.create_water_oil_gas(params["high"])
if not wog_high.selfcheck():
logger.error("Incomplete parameter set for high case")
errored = True
if errored:
raise ValueError("Incomplete SCAL recommendation")
scal = SCALrecommendation(wog_low, wog_base, wog_high, tag)
return scal
def test_interpolation(param_wo, param_go):
rec = SCALrecommendation(low_sample_let,
base_sample_let,
high_sample_let,
"foo",
h=0.1)
rec.add_simple_J() # Add default pc curve
try:
interpolant = rec.interpolate(param_wo, param_go, h=0.1)
except AssertionError:
return
check_table_wo(interpolant.wateroil.table)
check_table_go(interpolant.gasoil.table)
assert len(interpolant.gasoil.SGOF()) > 100
assert len(interpolant.gasoil.SGFN()) > 100
assert len(interpolant.wateroil.SWFN()) > 100
assert len(interpolant.SOF3()) > 100
assert len(interpolant.wateroil.SWOF()) > 100
assert interpolant.threephaseconsistency() == ""
def test_make_scalrecommendation_go():
"""Test that we can make scal recommendation objects
from three WaterOilGas objects, but only with GasOil
objects"""
go_param_names = [
"swirr",
"sorg",
"krgend",
"krgmax",
"swl",
"sgcr",
"Lg",
"Eg",
"Tg",
"Log",
"Eog",
"Tog",
"kroend",
]
low_let_go = slicedict(LOW_SAMPLE_LET, go_param_names)
low = PyscalFactory.create_water_oil_gas(low_let_go)
base_let_go = slicedict(BASE_SAMPLE_LET, go_param_names)
base = PyscalFactory.create_water_oil_gas(base_let_go)
high_let_go = slicedict(HIGH_SAMPLE_LET, go_param_names)
assert "Lw" not in high_let_go
high = PyscalFactory.create_water_oil_gas(high_let_go)
rec = SCALrecommendation(low, base, high)
assert rec.type == WaterOilGas
interpolant = rec.interpolate(-0.5)
check_table(interpolant.gasoil.table)
assert interpolant.wateroil is None
sat_table_str_ok(interpolant.SGOF())
sat_table_str_ok(interpolant.SGFN())
# This should return empty string
assert not interpolant.SWOF()
def test_make_scalrecommendation_wo():
"""Test that we can make scal recommendation objects
from three WaterOilGas objects, but only with WaterOil
objects"""
wo_param_names = [
"swirr",
"sorw",
"krwend",
"krwmax",
"swl",
"swcr",
"Lw",
"Ew",
"Tw",
"Lo",
"Eo",
"To",
"krowend",
]
low_let_wo = slicedict(LOW_SAMPLE_LET, wo_param_names)
low = PyscalFactory.create_water_oil_gas(low_let_wo)
base_let_wo = slicedict(BASE_SAMPLE_LET, wo_param_names)
base = PyscalFactory.create_water_oil_gas(base_let_wo)
high_let_wo = slicedict(HIGH_SAMPLE_LET, wo_param_names)
assert "Lg" not in high_let_wo
high = PyscalFactory.create_water_oil_gas(high_let_wo)
rec = SCALrecommendation(low, base, high)
interpolant = rec.interpolate(-0.5)
check_table(interpolant.wateroil.table)
assert interpolant.gasoil is None
assert sat_table_str_ok(interpolant.SWOF())
assert sat_table_str_ok(interpolant.SWFN())
# This should return empty string
assert not interpolant.SGOF()
def test_fast():
"""Test the fast option"""
low_fast = PyscalFactory.create_water_oil_gas(LOW_SAMPLE_LET, fast=True)
base_fast = PyscalFactory.create_water_oil_gas(BASE_SAMPLE_LET, fast=True)
high_fast = PyscalFactory.create_water_oil_gas(HIGH_SAMPLE_LET, fast=True)
rec = SCALrecommendation(low_fast, base_fast, high_fast)
interp = rec.interpolate(-0.5)
assert rec.fast
assert interp.fast
# test that one or more inputs not being set to fast does not trigger fast mode
low = PyscalFactory.create_water_oil_gas(LOW_SAMPLE_LET)
base = PyscalFactory.create_water_oil_gas(BASE_SAMPLE_LET)
high = PyscalFactory.create_water_oil_gas(HIGH_SAMPLE_LET)
rec = SCALrecommendation(low_fast, base_fast, high)
interp = rec.interpolate(-0.5)
assert not rec.fast
assert not interp.fast
rec = SCALrecommendation(low, base_fast, high)
interp = rec.interpolate(-0.5)
assert not rec.fast
assert not interp.fast
rec = SCALrecommendation(low, base, high)
interp = rec.interpolate(-0.5)
assert not rec.fast
assert not interp.fast
def interpolateplottest():
"""Demonstration of interpolation pointwise between LET curves"""
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use("ggplot")
rec = SCALrecommendation(lowsample(), basesample(), highsample(), "foo", h=0.001)
_, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
# Choosing logarithmic spaced interpolation parameters
# is not the same as interpolating in log(kr)-space
# check the effect by setting
# for t in -2 + np.logspace(1e-5,1e-1,15):
# and
# for t in -1 + np.logspace(1e-5,1e-1,15)
# in the loops below. Curves get clustered to the bottom
# in both linear and log(kr) spaces, but there
# still might be some other distribution for the interpolants
# that yields something that spans nicely both the linear and the
# logarithmic kr space (?)
for t in np.arange(-1, 0, 0.2):
interp = rec.interpolate(t, h=0.001)
interp.wateroil.plotkrwkrow(ax1, "r")
interp.wateroil.plotkrwkrow(ax2, "r")
for t in np.arange(0, 1, 0.2):
interp = rec.interpolate(t, h=0.001)
interp.wateroil.plotkrwkrow(ax1, "g")
interp.wateroil.plotkrwkrow(ax2, "g")
rec.low.wateroil.plotkrwkrow(ax1, linewidth=2, linestyle=":")
rec.base.wateroil.plotkrwkrow(ax1, linewidth=2)
rec.high.wateroil.plotkrwkrow(ax1, linewidth=2, linestyle="--")
rec.low.wateroil.plotkrwkrow(ax2, linewidth=2, linestyle=":")
rec.base.wateroil.plotkrwkrow(ax2, linewidth=2)
rec.high.wateroil.plotkrwkrow(ax2, linewidth=2, linestyle="--")
ax2.set_yscale("log")
ax2.set_ylim([1e-10, 1])
ax1.set_title("Water-oil, low, base, high and interpolants")
ax2.set_title("Water-oil, low, base, high and interpolants")
for t in np.arange(-1, 0, 0.2):
interp = rec.interpolate(t, h=0.001)
interp.gasoil.plotkrgkrog(ax3, "r")
interp.gasoil.plotkrgkrog(ax4, "r")
for t in np.arange(0, 1, 0.2):
interp = rec.interpolate(t, h=0.001)
interp.gasoil.plotkrgkrog(ax3, "g")
interp.gasoil.plotkrgkrog(ax4, "g")
rec.low.gasoil.plotkrgkrog(ax3, linewidth=2, linestyle=":")
rec.base.gasoil.plotkrgkrog(ax3, linewidth=2)
rec.high.gasoil.plotkrgkrog(ax3, linewidth=2, linestyle="--")
rec.low.gasoil.plotkrgkrog(ax4, linewidth=2, linestyle=":")
rec.base.gasoil.plotkrgkrog(ax4, linewidth=2)
rec.high.gasoil.plotkrgkrog(ax4, linewidth=2, linestyle="--")
ax3.set_title("Gas-oil, low, base, high and interpolants")
ax4.set_title("Gas-oil, low, base, high and interpolants")
ax4.set_yscale("log")
ax4.set_ylim([1e-05, 1])
plt.subplots_adjust(hspace=0.3)
plt.show()
def test_boundary_cases():
rec = SCALrecommendation(low_sample_let,
base_sample_let,
high_sample_let,
"foo",
h=0.1)
# Object reference equivalence is a little bit strict,
# because it would be perfectly fine if interpolate()
# retured copied objects. But we don't have an equivalence operator
# implemented.
assert rec.interpolate(0).wateroil == rec.base.wateroil
assert rec.interpolate(-1).wateroil == rec.low.wateroil
assert rec.interpolate(1).wateroil == rec.high.wateroil
assert rec.interpolate(0).gasoil == rec.base.gasoil
assert rec.interpolate(-1).gasoil == rec.low.gasoil
assert rec.interpolate(1).gasoil == rec.high.gasoil
assert rec.interpolate(0, 1).wateroil == rec.base.wateroil
assert rec.interpolate(-1, 1).wateroil == rec.low.wateroil
assert rec.interpolate(1, 1).wateroil == rec.high.wateroil
assert rec.interpolate(0, 1).gasoil == rec.high.gasoil
assert rec.interpolate(-1, 1).gasoil == rec.high.gasoil
assert rec.interpolate(1, 1).gasoil == rec.high.gasoil
assert rec.interpolate(0, 0).gasoil == rec.base.gasoil
assert rec.interpolate(-1, 0).gasoil == rec.base.gasoil
assert rec.interpolate(1, 0).gasoil == rec.base.gasoil
assert rec.interpolate(0, -1).gasoil == rec.low.gasoil
assert rec.interpolate(-1, -1).gasoil == rec.low.gasoil
assert rec.interpolate(1, -1).gasoil == rec.low.gasoil