def test_interpolate_go(
swl,
sgcr,
dsgcr,
dswlhigh,
sorg,
dsorg,
ng_l,
ng_h,
nog_l,
nog_h,
krgend_l,
krgend_h,
kroend_l,
kroend_h,
):
"""Test many possible combinations of interpolation between two
Corey gasoil curves, looking for numerical corner cases"""
go_low = GasOil(swl=swl, sgcr=sgcr, sorg=sorg)
go_high = GasOil(swl=swl + dswlhigh,
sgcr=sgcr + dsgcr,
sorg=max(sorg - dsorg, 0))
go_low.add_corey_gas(ng=ng_l, krgend=krgend_l)
go_high.add_corey_gas(ng=ng_h, krgend=krgend_h)
go_low.add_corey_oil(nog=nog_l, kroend=kroend_l)
go_high.add_corey_oil(nog=nog_h, kroend=kroend_h)
ips = []
ip_dist = 0.05
for t in np.arange(0, 1 + ip_dist, ip_dist):
go_ip = utils.interpolate_go(go_low, go_high, t)
check_table(go_ip.table)
ips.append(go_ip)
assert 0 < go_ip.crosspoint() < 1
# Distances between low and interpolants:
dists = [(go_low.table - interp.table)[["krg", "krog"]].sum().sum()
for interp in ips]
print("Interpolation, mean: {}, min: {}, max: {}, std: {} ip-par-dist: {}".
format(np.mean(dists), min(dists), max(dists),
np.std(np.diff(dists[1:])), ip_dist))
assert np.isclose(dists[0], 0) # Reproducing go_low
# All curves that are close in parameter t, should be close in sum().sum().
# That means that diff of the distances should be similar,
# that is the std.dev of the distances is low:
ip_dist_std = np.std(np.diff(
dists[1:])) # This number depends on 'h' and 't' range, and
# by how different the low and high is.
# (avoiding the first which reproduces go_low
if ip_dist_std > 1.0: # number found from trial and error.
print("ip_dist_std: {}".format(ip_dist_std))
print(dists)
from matplotlib import pyplot as plt
_, mpl_ax = plt.subplots()
go_low.plotkrgkrog(mpl_ax=mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax=mpl_ax, color="blue")
for interp in ips:
interp.plotkrgkrog(mpl_ax=mpl_ax, color="green")
plt.show()
assert False
def testgascurves():
"""test of gas-oil curves"""
sgof = GasOil(tag="Testcurve", h=0.02, swirr=0.18, swl=0.31, sorg=0.09, sgcr=0.04)
sgof.add_corey_gas(ng=1.5, krgend=0.7)
sgof.add_corey_oil(nog=2, kroend=0.4)
sgof.add_LET_gas(l=2, e=1, t=1.4, krgend=0.9)
sgof.add_LET_oil(l=2, e=3, t=1.4, kroend=0.7)
print(sgof.table)
_, mpl_ax = plt.subplots()
sgof.plotkrgkrog(mpl_ax)
# mpl_ax.set_yscale('log')
print(sgof.SGOF())
plt.show()
def test_interpolate_go(
swl,
sgcr,
dsgcr,
dswlhigh,
sorg,
dsorg,
ng_l,
ng_h,
nog_l,
nog_h,
krgend_l,
krgend_h,
kroend_l,
kroend_h,
):
# pylint: disable=too-many-arguments,too-many-locals
"""Test many possible combinations of interpolation between two
Corey gasoil curves, looking for numerical corner cases"""
h = 0.01
go_low = GasOil(swl=swl, sgcr=sgcr, sorg=sorg, h=h)
go_high = GasOil(
swl=swl + dswlhigh, sgcr=sgcr + dsgcr, sorg=max(sorg - dsorg, 0), h=h
)
go_low.add_corey_gas(ng=ng_l, krgend=krgend_l)
go_high.add_corey_gas(ng=ng_h, krgend=krgend_h)
go_low.add_corey_oil(nog=nog_l, kroend=kroend_l)
go_high.add_corey_oil(nog=nog_h, kroend=kroend_h)
ips = []
ip_dist = 0.05
for t in np.arange(0, 1 + ip_dist, ip_dist):
go_ip = interpolate_go(go_low, go_high, t)
check_table(go_ip.table)
ips.append(go_ip)
assert 0 < go_ip.crosspoint() < 1
# sgcr is non-trivial, if exponents are high, an effective sgcr might
# be larger than the value used to initialize the curve. Try to be
# permissive enough here. This can even cause the interpolant to be
# outside the low-high envelope, but it is the way it is supposed to
# be when sgcr is interpolated separately.
sgcr_low = min(
go_low.sgcr, go_low.estimate_sgcr(), go_high.sgcr, go_high.estimate_sgcr()
)
sgcr_high = max(
go_low.sgcr, go_low.estimate_sgcr(), go_high.sgcr, go_high.estimate_sgcr()
)
sgcr_ip = go_ip.estimate_sgcr()
sgcr_lower_bound_ok = sgcr_low - h - epsilon < sgcr_ip
sgcr_upper_bound_ok = sgcr_ip < sgcr_high + h + epsilon
assert sgcr_lower_bound_ok
assert sgcr_upper_bound_ok
# Distances between low and interpolants:
dists = [
(go_low.table - interp.table)[["krg", "krog"]].sum().sum() for interp in ips
]
print(
"Interpolation, mean: {}, min: {}, max: {}, std: {} ip-par-dist: {}".format(
np.mean(dists), min(dists), max(dists), np.std(np.diff(dists[1:])), ip_dist
)
)
assert np.isclose(dists[0], 0) # Reproducing go_low
# All curves that are close in parameter t, should be close in sum().sum().
# That means that diff of the distances should be similar,
# that is the std.dev of the distances is low:
ip_dist_std = np.std(
np.diff(dists[1:])
) # This number depends on 'h' and 't' range, and
# by how different the low and high is.
# (avoiding the first which reproduces go_low
if ip_dist_std > 1.0: # number found from trial and error.
print("ip_dist_std: {}".format(ip_dist_std))
print(dists)
_, mpl_ax = plt.subplots()
go_low.plotkrgkrog(mpl_ax=mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax=mpl_ax, color="blue")
for interp in ips:
interp.plotkrgkrog(mpl_ax=mpl_ax, color="green")
plt.show()
assert False
def test_interpolate_go():
"""Interactive tests for gasoil"""
swl_l = random.uniform(0, 0.1)
sgcr_l = random.uniform(0, 0.1)
swl_h = random.uniform(0, 0.1)
sgcr_h = random.uniform(0, 0.1)
sorg_l = random.uniform(0, 0.2)
sorg_h = random.uniform(0, 0.2)
if bool(random.getrandbits(1)):
# Interpolation is not possible if only
# one of the curves has nonzero sgro
sgro_l = sgcr_l
sgro_h = sgcr_h
else:
sgro_l = 0
sgro_h = 0
krgend_l = random.uniform(0.5, 1)
krgend_h = random.uniform(0.5, 1)
kromax_l = random.uniform(0.5, 1)
kromax_h = random.uniform(0.5, 1)
kroend_l = min(random.uniform(0.5, 1), kromax_l)
kroend_h = min(random.uniform(0.5, 1), kromax_h)
if random.uniform(0, 1) > 0.5:
krgendanchor_l = "sorg"
else:
krgendanchor_l = ""
if random.uniform(0, 1) > 0.5:
krgendanchor_h = "sorg"
else:
krgendanchor_h = ""
go_low = GasOil(
swl=swl_l,
sgcr=sgcr_l,
sorg=sorg_l,
sgro=sgro_l,
krgendanchor=krgendanchor_l,
h=0.001,
)
go_high = GasOil(
swl=swl_h,
sgcr=sgcr_h,
sorg=sorg_h,
sgro=sgro_h,
krgendanchor=krgendanchor_h,
h=0.001,
)
go_low.add_corey_gas(ng=random.uniform(1, 3), krgend=krgend_l)
go_high.add_corey_gas(ng=random.uniform(1, 3), krgend=krgend_h)
go_low.add_corey_oil(nog=random.uniform(1, 3),
kroend=kroend_l,
kromax=kromax_l)
go_high.add_corey_oil(nog=random.uniform(1, 3),
kroend=kroend_h,
kromax=kromax_h)
print(" ** Low curve GasOil (red):\n" + go_low.sgcomment +
go_low.krgcomment + go_low.krogcomment)
print(" ** High curve GasOil (blue):\n" + go_high.sgcomment +
go_high.krgcomment + go_high.krogcomment)
_, mpl_ax = pyplot.subplots()
go_low.plotkrgkrog(mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax, color="blue")
for tparam in np.arange(0, 1, 0.1):
go_ip = utils.interpolation.interpolate_go(go_low, go_high, tparam)
go_ip.plotkrgkrog(mpl_ax, color="green")
mpl_ax.set_title("GasOil, random Corey, linear y-scale")
_pyplot_show_with_user_message()
_, mpl_ax = pyplot.subplots()
go_low.plotkrgkrog(mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax, color="blue")
# Plot again with log yscale:
for tparam in np.arange(0, 1, 0.1):
go_ip = utils.interpolation.interpolate_go(go_low, go_high, tparam)
go_ip.plotkrgkrog(mpl_ax, color="green", logyscale=True)
mpl_ax.set_title("GasOil, random Corey, log y-scale")
_pyplot_show_with_user_message()
def test_interpolate_go():
"""Interactive tests for gasoil"""
swl_l = random.uniform(0, 0.1)
sgcr_l = random.uniform(0, 0.1)
swl_h = random.uniform(0, 0.1)
sgcr_h = random.uniform(0, 0.1)
sorg_l = random.uniform(0, 0.2)
sorg_h = random.uniform(0, 0.2)
if random.uniform(0, 1) > 0.5:
krgendanchor_l = "sorg"
else:
krgendanchor_l = ""
if random.uniform(0, 1) > 0.5:
krgendanchor_h = "sorg"
else:
krgendanchor_h = ""
go_low = GasOil(swl=swl_l,
sgcr=sgcr_l,
sorg=sorg_l,
krgendanchor=krgendanchor_l,
h=0.001)
go_high = GasOil(swl=swl_h,
sgcr=sgcr_h,
sorg=sorg_h,
krgendanchor=krgendanchor_h,
h=0.001)
go_low.add_corey_gas(ng=random.uniform(1, 3),
krgend=random.uniform(0.5, 1))
go_high.add_corey_gas(ng=random.uniform(1, 3),
krgend=random.uniform(0.5, 1))
go_low.add_corey_oil(nog=random.uniform(1, 3),
kroend=random.uniform(0.5, 1))
go_high.add_corey_oil(nog=random.uniform(1, 3),
kroend=random.uniform(0.5, 1))
print(" ** Low curve GasOil (red):\n" + go_low.sgcomment +
go_low.krgcomment + go_low.krogcomment)
print(" ** High curve GasOil (blue):\n" + go_high.sgcomment +
go_high.krgcomment + go_high.krogcomment)
_, mpl_ax = plt.subplots()
go_low.plotkrgkrog(mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax, color="blue")
for tparam in np.arange(0, 1, 0.1):
go_ip = utils.interpolation.interpolate_go(go_low, go_high, tparam)
go_ip.plotkrgkrog(mpl_ax, color="green")
mpl_ax.set_title("GasOil, random Corey, linear y-scale")
plt.show()
_, mpl_ax = plt.subplots()
go_low.plotkrgkrog(mpl_ax, color="red")
go_high.plotkrgkrog(mpl_ax, color="blue")
# Plot again with log yscale:
for tparam in np.arange(0, 1, 0.1):
go_ip = utils.interpolation.interpolate_go(go_low, go_high, tparam)
go_ip.plotkrgkrog(mpl_ax, color="green", logyscale=True)
mpl_ax.set_title("GasOil, random Corey, log y-scale")
plt.show()
# Capillary pressure - This is barely supported for gasoil
# so the plotpc() function is missing. Include calculations
# here so we ensure we don't crash on the all zeros.
# _, mpl_ax = plt.subplots()
# go_low.plotpc(mpl_ax, color="red", logyscale=True)
# go_high.plotpc(mpl_ax, color="blue", logyscale=True)
for tparam in np.arange(0, 1, 0.1):
go_ip = utils.interpolation.interpolate_go(go_low,
go_high,
tparam,
h=0.001)
def test_plotting():
"""Test that plotting code pass through (nothing displayed)"""
gasoil = GasOil(swl=0.1, h=0.1)
gasoil.add_corey_gas()
gasoil.add_corey_oil()
gasoil.plotkrgkrog(mpl_ax=matplotlib.pyplot.subplots()[1])
