def test_pillars():
"""Test that we can build a dataframe of pillar statistics"""
eclfiles = EclFiles(DATAFILE)
pillars_df = pillars.df(eclfiles)
assert "PILLAR" in pillars_df
assert "VOLUME" in pillars_df
assert "PORV" in pillars_df
assert "PERMX" in pillars_df
assert "X" in pillars_df
assert "Y" in pillars_df
assert "PORO" in pillars_df
assert "OILVOL" not in pillars_df
assert "FIPNUM" not in pillars_df
assert "EQLNUM" not in pillars_df
assert "OWC" not in pillars_df
assert "GOC" not in pillars_df
assert len(pillars_df) == 2560
pillars_df = pillars.df(eclfiles, region="FIPNUM")
assert "FIPNUM" in pillars_df
assert len(pillars_df["FIPNUM"].unique()) == 6
assert "OILVOL" not in pillars_df
pillars_df = pillars.df(eclfiles, rstdates="first")
firstdate = str(grid.dates2rstindices(eclfiles, "first")[1][0])
assert "OILVOL@" + firstdate in pillars_df
assert "GASVOL@" + firstdate in pillars_df
assert "WATVOL@" + firstdate in pillars_df
pillars_df = pillars.df(eclfiles, rstdates="last", soilcutoff=0.2, sgascutoff=0.2)
lastdate = str(grid.dates2rstindices(eclfiles, "last")[1][0])
assert "OWC@" + lastdate in pillars_df
assert "GOC@" + lastdate not in pillars_df # Because the dataset has no GAS...
def test_rstdates():
eclfiles = EclFiles(DATAFILE)
# rstfile = eclfiles.get_rstfile()
alldates = grid.rstdates(eclfiles)
assert len(alldates) == 4
didx = grid.dates2rstindices(eclfiles, "all")
assert len(didx[0]) == len(alldates)
assert len(didx[1]) == len(alldates)
assert isinstance(didx[0][0], int)
assert isinstance(didx[1][0], datetime.date)
assert didx[1][0] == alldates[0]
assert didx[1][-1] == alldates[-1]
first = grid.dates2rstindices(eclfiles, "first")
assert first[1][0] == alldates[0]
last = grid.dates2rstindices(eclfiles, "last")
assert last[1][0] == alldates[-1]
dates = grid.rstdates(eclfiles)
assert isinstance(dates, list)
# Test with missing RST file:
eclfiles = EclFiles("BOGUS.DATA")
with pytest.raises(IOError):
eclfiles.get_rstfile()
def test_get_available_rst_dates():
"""Test the support of dates in restart files"""
eclfiles = EclFiles(REEK)
# rstfile = eclfiles.get_rstfile()
alldates = grid.get_available_rst_dates(eclfiles)
assert len(alldates) == 4
didx = grid.dates2rstindices(eclfiles, "all")
assert len(didx[0]) == len(alldates)
assert len(didx[1]) == len(alldates)
assert isinstance(didx[0][0], int)
assert isinstance(didx[1][0], datetime.date)
assert didx[1][0] == alldates[0]
assert didx[1][-1] == alldates[-1]
somedate = grid.dates2rstindices(eclfiles, "2000-07-01")
assert somedate[1] == [alldates[1]]
with pytest.raises(ValueError, match="date 1999-09-09 not found in UNRST file"):
grid.dates2rstindices(eclfiles, "1999-09-09")
with pytest.raises(ValueError, match="date 1999-0909 not understood"):
grid.dates2rstindices(eclfiles, "1999-0909")
expl_date = grid.dates2rstindices(eclfiles, datetime.date(2000, 7, 1))
assert expl_date[1] == [alldates[1]]
expl_datetime = grid.dates2rstindices(
eclfiles, datetime.datetime(2000, 7, 1, 0, 0, 0)
)
assert expl_datetime[1] == [alldates[1]]
expl_list_datetime = grid.dates2rstindices(eclfiles, [datetime.date(2000, 7, 1)])
assert expl_list_datetime[1] == [alldates[1]]
# For list input, only datetime.date objects are allowed:
expl_list2_date = grid.dates2rstindices(
eclfiles, [datetime.date(2000, 7, 1), datetime.date(2001, 2, 1)]
)
assert expl_list2_date[1] == [alldates[1], alldates[2]]
with pytest.raises(ValueError, match="None of the requested dates were found"):
grid.dates2rstindices(eclfiles, ["2000-07-01", "2001-02-01"])
with pytest.raises(ValueError, match="None of the requested dates were found"):
grid.dates2rstindices(
eclfiles,
[
datetime.datetime(2000, 7, 1, 0, 0, 0),
datetime.datetime(2001, 2, 1, 0, 0, 0),
],
)
with pytest.raises(ValueError, match="not understood"):
grid.dates2rstindices(eclfiles, {"2000-07-01": "2001-02-01"})
first = grid.dates2rstindices(eclfiles, "first")
assert first[1][0] == alldates[0]
last = grid.dates2rstindices(eclfiles, "last")
assert last[1][0] == alldates[-1]
dates = grid.get_available_rst_dates(eclfiles)
assert isinstance(dates, list)
# Test with missing RST file:
eclfiles = EclFiles("BOGUS.DATA")
with pytest.raises(IOError):
eclfiles.get_rstfile()
def df(
eclfiles: EclFiles,
region: str = None,
rstdates: Optional[Union[str, datetime.date, List[datetime.date]]] = None,
soilcutoff: float = 0.2,
sgascutoff: float = 0.7,
swatcutoff: float = 0.7,
stackdates: bool = False,
) -> pd.DataFrame:
"""Produce a dataframe with pillar information
This is the "main" function for Python API users
Produces a dataframe with data for each I-J combination
(in the column PILLAR), and if a region parameter is
supplied, also pr. region.
PORV is the summed porevolume of the pillar (in the region),
VOLUME is bulk volume, and PORO is porevolume weighted porosity
PERM columns contain unweighted value averages, use with caution.
If a restart date is picked, then SWAT and SGAS will
be used to compute volumes pr. phase, WATVOL, OILVOL and GASVOL. The
columns with dynamic data will include the date in the column headers
like SWAT@2009-01-01
Args:
region: A parameter the pillars will be split
on. Typically EQLNUM or FIPNUM. Set to empty string
or None to avoid any region grouping.
rstdates: Dates for which restart data
is to be extracted. The string can
be in ISO-format, or one of the mnenomics
'first', 'last' or 'all'. It can also be a list
of datetime.date.
soilcutoff: If not None, an oil-water contact will
be estimated pr. pillar, based on the deepest cell with
SOIL above the given cutoff. Value is put in column OWC.
sgascuttof: If not None, a gas contact will be
estimated pr pillar, based on the deepest cell with
SGAS above the given cutoff. Value is put in column GOC.
swatcutoff: OWC or GWC is only computed for pillars
where at least one cell is above this value.
stackdates: If true, a column
called DATE will be added and data for all restart
dates will be added in a stacked manner.
"""
# List of vectors we want, conservative in order to save memory and cputime:
vectors = []
if region:
vectors.append(region)
vectors.extend(["POR*", "PERM*", "SWAT", "SGAS", "1OVERBO", "1OVERBG"])
grid_df = grid.df(eclfiles,
rstdates=rstdates,
vectors=vectors,
dateinheaders=True)
rstdates_iso = grid.dates2rstindices(eclfiles, rstdates)[2]
grid_df["PILLAR"] = grid_df["I"].astype(str) + "-" + grid_df["J"].astype(
str)
logger.info("Computing pillar statistics")
groupbies = ["PILLAR"]
if region:
if region not in grid_df:
logger.warning("Region parameter %s not found, ignored", region)
else:
groupbies.append(region)
grid_df[region] = grid_df[region].astype(int)
for datestr in rstdates_iso:
logger.info("Dynamic volumes for %s", datestr)
volumes = compute_volumes(grid_df, datestr=datestr)
grid_df = pd.concat([grid_df, volumes], axis="columns", sort=False)
aggregators = {
key: AGGREGATORS[key.split("@")[0]]
for key in grid_df if key.split("@")[0] in AGGREGATORS
}
# Group over PILLAR and possibly regions:
grouped = (grid_df.groupby(groupbies).agg(aggregators)).reset_index()
# Compute correct pillar averaged porosity (from bulk)
if "PORV" in grouped and "VOLUME" in grouped:
grouped["PORO"] = grouped["PORV"] / grouped["VOLUME"]
# Compute contacts:
for datestr in rstdates_iso:
if "SWAT@" + datestr in grid_df and ("SOIL@" + datestr in grid_df
or "SGAS@" + datestr in grid_df):
contacts = compute_pillar_contacts(
grid_df,
region=region,
soilcutoff=soilcutoff,
sgascutoff=sgascutoff,
swatcutoff=swatcutoff,
datestr=datestr,
)
if not contacts.empty:
grouped = pd.merge(grouped, contacts, how="left")
if stackdates:
return common.stack_on_colnames(grouped,
sep="@",
stackcolname="DATE",
inplace=True)
return grouped
