def test_minimal_branched_well():
r"""
| segidx 1
/ \ segidx 2 and 3
"""
two_branch = pd.DataFrame({
"SEGIDX": [1, 2, 3],
"SEGNXT": [None, 1, 1],
"SEGBRNO": [1, 1, 2]
})
con_data = pd.DataFrame({
"CONSEGNO": [2, 3],
"PRESSURE": [301, 302],
"CONPRES": [291, 292]
})
m_two_branch = rft.process_seg_topology(two_branch)
assert len(m_two_branch) == 4 # One extra row for the junction segment
assert sum(m_two_branch["LEAF"]) == 2
assert rft.count_wellbranches(m_two_branch) == 2
assert rft.split_seg_icd(two_branch)[1].empty
con_seg = rft.merge_icd_seg_conseg(con_data, m_two_branch)
# Junction segment has no reservoir connection and is not included
# in the merge.
assert len(con_seg) == 2
assert rft.seg2dicttree(m_two_branch) == {1: {2: {}, 3: {}}}
# Junction segment points to two upstream segments:
assert set(m_two_branch[m_two_branch["SEGIDX"] == 1]
["SEGIDX_upstream"].astype(int)) == {2, 3}
assert int(m_two_branch.loc[0, "SEGIDX_upstream"]) == 2
assert int(m_two_branch.loc[1, "SEGIDX_upstream"]) == 3
def test_branched_icd_well():
r"""Simplest possible branched well with ICD segments
| segidx 1
* - / \ - * segidx 2 and 3
"""
wellseg = pd.DataFrame({
"SEGIDX": [1, 2, 3, 4, 5],
"SEGNXT": [None, 1, 1, 2, 3],
"SEGBRNO": [1, 1, 2, 3, 4],
})
con_data = pd.DataFrame({
"CONSEGNO": [4, 5],
"PRESSURE": [301, 302],
"CONPRES": [291, 292]
})
(seg_data, icd_data) = rft.split_seg_icd(wellseg)
print(rft.seg2dicttree(wellseg))
print(rft.pretty_print_well(wellseg))
assert len(icd_data) == 2
assert all(icd_data.columns.str.startswith("ICD"))
assert all(icd_data["ICD_SEGIDX"].values == [4, 5])
assert all(icd_data["ICD_SEGBRNO"].values == [3, 4])
assert all(icd_data["ICD_SEGBRNO_upstream"].values == [0, 0])
print(seg_data)
assert rft.count_wellbranches(seg_data) == 2
con_seg = rft.merge_icd_seg_conseg(con_data, seg_data, icd_data)
print(con_seg)
assert len(con_seg) == 2
con_seg = rft.add_extras(con_seg)
assert all(con_seg["DRAWDOWN"].values == [10, 10])
def test_minimal_well():
"""Test a dummy well dataset
| segidx 1
"""
one_seg = pd.DataFrame({
"SEGIDX": [1],
"SEGNXT": [None],
"SEGBRNO": [1],
"SEGPRES": [195.8]
})
m_one_seg = rft.process_seg_topology(one_seg)
assert m_one_seg["LEAF"][0]
assert len(m_one_seg) == 1
assert rft.count_wellbranches(one_seg) == 1
assert rft.split_seg_icd(one_seg)[1].empty
con_data = pd.DataFrame({
"CONSEGNO": [1],
"PRESSURE": [200.1],
"CONPRES": [196.0]
})
con_seg = rft.merge_icd_seg_conseg(con_data, m_one_seg)
assert len(con_seg) == 1
assert "CONSEGNO" in con_seg
assert "SEGIDX" in con_seg
con_seg = rft.add_extras(con_seg)
assert "COMPLETION_DP" in con_seg
assert con_seg["COMPLETION_DP"].values[0] == 196.0 - 195.8
assert con_seg["DRAWDOWN"].values[0] == 200.1 - 196.0
assert rft.seg2dicttree(m_one_seg) == {1: {}}
print(rft.pretty_print_well(m_one_seg))
def test_seg2dicttree():
assert rft.seg2dicttree(pd.DataFrame()) == {}
with pytest.raises(ValueError):
rft.seg2dicttree(pd.DataFrame({"SEGIDX": [1]}))
with pytest.raises(KeyError, match="SEGBRNO"):
rft.seg2dicttree(pd.DataFrame({"SEGIDX": [1], "SEGNXT": [None]}))
# Simplest well:
assert rft.seg2dicttree(
pd.DataFrame({
"SEGIDX": [1],
"SEGNXT": [None],
"SEGBRNO": [1]
})) == {
1: {}
}
# Two branches:
assert rft.seg2dicttree(
pd.DataFrame({
"SEGIDX": [1, 2, 3],
"SEGNXT": [None, 1, 1],
"SEGBRNO": [1, 1, 2]
})) == {
1: {
2: {},
3: {}
}
}
def test_single_branch_partly_icd():
r"""
Test that we are able to untangle segment dataframes with ICDs
modelled as individual branches, but not on all reservoir connections
Single branch well, one mother segment, two connections,
one icd to one connection:
| segidx 1
| - * segidx 2 and 4 (icd), and reservoir
| * segidx 3, and reservoir
legend: | = tubing
- = icd
* = reservoir connection
This is the same layout as
| segidx 1
| segidx 2
/ \ segidx 3 and 4
* *
which is a two-branch well. It is not possible to
separate these two based on topology. Current code interprets
the topology as the latter case.
The ambiguity arises due to the assumption that ICD segments
are on their on branches with only one segment. In real modelled
wells, this assumption will be valid, as the tubing segments will
consist of more segments than 1 (except corner cases)
(check the LONELYSEG segment toplogy metadata column which
is used in determining whether a segment is ICD or not)
"""
wellseg = pd.DataFrame({
"SEGIDX": [1, 2, 3, 4],
"SEGNXT": [None, 1, 2, 2],
"SEGBRNO": [1, 1, 1, 2]
})
con_data = pd.DataFrame({
"CONSEGNO": [4, 3],
"PRESSURE": [301, 302],
"CONPRES": [291, 292]
})
(seg_data, icd_data) = rft.split_seg_icd(wellseg)
print(rft.seg2dicttree(wellseg))
print(rft.pretty_print_well(wellseg))
assert rft.count_wellbranches(seg_data) == 2
assert len(icd_data) == 0
con_seg = rft.merge_icd_seg_conseg(con_data, seg_data, icd_data)
assert len(con_seg) == 2
con_seg = rft.add_extras(con_seg)
assert all(con_seg["DRAWDOWN"].values == [10, 10])
def test_longer_branched_icd_well():
r"""Test a well with two connections on each of two laterals,
with an ICD segment for each connection
| segidx 1
* - / \ - * segidx 4 and 2 (lateral1) and 6 and 8
* - | | - * segidx 5 and 3 (lateral1) and 7 and 9
"""
wellseg = {
"SEGIDX": [1] + [2, 3, 4, 5] + [6, 7, 8, 9],
"SEGNXT": [None] + [1, 2, 2, 3] + [1, 6, 6, 7],
"SEGBRNO": [1] + [1, 1, 3, 4] + [2, 2, 5, 6],
}
# Shuffle the segment list randomly, that should not matter:
shuffled = list(range(9))
random.shuffle(shuffled)
print(shuffled)
wellseg = pd.DataFrame(
{segname: [wellseg[segname][idx] for idx in shuffled] for segname in wellseg}
)
con_data = pd.DataFrame(
{
"CONSEGNO": [4, 5, 8, 9],
"PRESSURE": [301, 302, 401, 402],
"CONPRES": [291, 292, 392, 393],
}
)
seg_data = rft.process_seg_topology(wellseg)
assert sum(seg_data["LONELYSEG"]) == 4
assert sum(seg_data["LEAF"]) == 4
assert sum(seg_data["JUNCTION"]) == 6 # 1, 2 and 6 counted twice
assert sum(seg_data["LEAF"]) == 4
(seg_data, icd_data) = rft.split_seg_icd(wellseg)
print(rft.seg2dicttree(wellseg))
print(rft.pretty_print_well(wellseg))
assert len(icd_data) == 4
assert all(icd_data.columns.str.startswith("ICD"))
assert set(icd_data["ICD_SEGIDX"].values) == {4, 5, 8, 9}
assert set(icd_data["ICD_SEGBRNO"].values) == {3, 4, 5, 6}
assert all(icd_data["ICD_SEGBRNO_upstream"].values == [0, 0, 0, 0])
print(seg_data)
assert rft.count_wellbranches(seg_data) == 2
con_seg = rft.merge_icd_seg_conseg(con_data, seg_data, icd_data)
print(con_seg)
assert len(con_seg) == 4
con_seg = rft.add_extras(con_seg)
assert all(con_seg["DRAWDOWN"].values == [10, 10, 9, 9])
def test_longer_branched_partly_icd_well():
r"""Test a well with two connections on each of two laterals,
with an ICD segment for each connection only on the first lateral
| segidx 1
* - / \ * segidx 4 and 2 (lateral1) and 6 and
* - | | * segidx 5 and 3 (lateral1) and 7 and
"""
wellseg = pd.DataFrame(
{
# [wellhead] + [lateral 1, tubing, then icd layer] + [lateral 2]
"SEGIDX": [1] + [2, 3, 4, 5] + [6, 7],
"SEGNXT": [None] + [1, 2, 2, 3] + [1, 6],
"SEGBRNO": [1] + [1, 1, 3, 4] + [2, 2],
}
)
con_data = pd.DataFrame(
{
"CONSEGNO": [4, 5, 6, 7],
"PRESSURE": [301, 302, 401, 402],
"CONPRES": [291, 292, 392, 393],
}
)
(seg_data, icd_data) = rft.split_seg_icd(wellseg)
print()
print(seg_data)
print(rft.seg2dicttree(wellseg))
print(rft.pretty_print_well(wellseg))
assert len(icd_data) == 2
assert all(icd_data.columns.str.startswith("ICD"))
assert set(icd_data["ICD_SEGIDX"].values) == {4, 5}
assert set(icd_data["ICD_SEGBRNO"].values) == {3, 4}
assert all(icd_data["ICD_SEGBRNO_upstream"].values == [0, 0])
print(seg_data)
assert rft.count_wellbranches(seg_data) == 2
con_seg = rft.merge_icd_seg_conseg(con_data, seg_data, icd_data)
print(con_seg)
assert len(con_seg) == 4
con_seg = rft.add_extras(con_seg)
assert all(con_seg["DRAWDOWN"].values == [10, 10, 9, 9])
def test_single_branch_icd():
"""
Test that we are able to untangle segment dataframes with ICDs
modelled as individual brances.
"""
# Single branch well, one mother segment, two connections,
# one icd to each connection:
# | segidx 1
# | - * segidx 2 and 4, and reservoir
# | - * segidx 3 and 5, and reservoir
# legend: | = tubing
# - = icd
# * = reservoir connection
wellseg = pd.DataFrame({
"SEGIDX": [1, 2, 3, 4, 5],
"SEGNXT": [None, 1, 2, 2, 3],
"SEGBRNO": [1, 1, 1, 2, 3],
})
con_data = pd.DataFrame({
"CONSEGNO": [4, 5],
"PRESSURE": [301, 302],
"CONPRES": [291, 292]
})
(seg_data, icd_data) = rft.split_seg_icd(wellseg)
print(rft.seg2dicttree(wellseg))
print(rft.pretty_print_well(wellseg))
assert rft.count_wellbranches(seg_data) == 1
assert len(icd_data) == 2
assert all(icd_data.columns.str.startswith("ICD"))
assert all(icd_data["ICD_SEGIDX"].values == [4, 5])
assert all(icd_data["ICD_SEGBRNO"].values == [2, 3])
assert all(icd_data["ICD_SEGBRNO_upstream"].values == [0, 0])
con_seg = rft.merge_icd_seg_conseg(con_data, seg_data, icd_data)
assert len(con_seg) == 2
con_seg = rft.add_extras(con_seg)
assert all(con_seg["DRAWDOWN"].values == [10, 10])
