def equil_fromdeck(deck: Union[str, "opm.libopmcommon_python.Deck"],
ntequl: Optional[int] = None) -> pd.DataFrame:
"""Extract EQUIL data from a deck
If the deck is supplied as a string object, the number
of EQLNUM regions will be inferred if needed.
Args:
deck
ntequl: Number of EQLNUM regions in deck.
"""
if "EQLDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("EQLDIMS", "NTEQUL", deck,
ntequl)
phases = phases_from_deck(deck)
if not phases or phases not in RENAMERS:
raise ValueError(
f"Could not determine phase configuration, got '{phases}'")
columnrenamer = RENAMERS[phases_from_deck(deck)]
dataframe = common.ecl_keyworddata_to_df(deck,
"EQUIL",
renamer=columnrenamer,
recordcountername="EQLNUM")
# The column handling can be made prettier..
for col in dataframe.columns:
if "IGNORE" in col:
del dataframe[col]
return dataframe
def equil_fromdeck(deck, ntequl=None):
"""Extract EQUIL data from a deck
Args:
deck (str or opm.common Deck)
ntequl (int): Number of EQLNUM regions in deck. Will
be inferred if not present in deck
"""
if "EQLDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("EQLDIMS", "NTEQUL", deck,
ntequl)
phasecount = sum(["OIL" in deck, "GAS" in deck, "WATER" in deck])
phases = phases_from_deck(deck)
if not phases or phases not in RENAMERS:
raise ValueError(
"Could not determine phase configuration, got '{}'".format(phases))
columnrenamer = RENAMERS[phases_from_deck(deck)]
if phasecount == 1:
columnrenamer = {"DATUM_DEPTH": "DATUM", "DATUM_PRESSURE": "PRESSURE"}
if not columnrenamer:
raise ValueError("Unsupported phase configuration")
dataframe = common.ecl_keyworddata_to_df(deck,
"EQUIL",
renamer=columnrenamer,
recordcountername="EQLNUM")
# The column handling can be made prettier..
for col in dataframe.columns:
if "IGNORE" in col:
del dataframe[col]
return dataframe
def rock_fromdeck(deck, ntpvt=None):
"""Extract ROCK from a deck
Args:
deck (str or opm.common Deck)
ntpvt (int): Number of PVT regions in deck. Will
be inferred if not present in deck.
"""
if "TABDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("TABDIMS", "NTPVT", deck, ntpvt)
return common.ecl_keyworddata_to_df(
deck, "ROCK", renamer=RENAMERS["ROCK"], recordcountername="PVTNUM"
)
def pdvd_fromdeck(deck, ntequl=None):
"""Extract PDVD data from a deck
Args:
deck (str or opm.common Deck)
ntequl (int): Number of EQLNUM regions in deck. Will
be inferred if not present in deck
"""
if "EQLDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("EQLDIMS", "NTEQUL", deck, ntequl)
return common.ecl_keyworddata_to_df(
deck, "PDVD", renamer=RENAMERS["PDVD"], recordcountername="EQLNUM"
)
def slgof_fromdeck(deck, ntsfun=None):
"""Extract SLGOF data from a deck
Args:
deck (str or opm.common Deck)
ntsfun (int): Number of SATNUM regions in deck. Will
be inferred if not present in deck
"""
if "TABDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("TABDIMS", "NTSFUN", deck, ntsfun)
return common.ecl_keyworddata_to_df(
deck, "SLGOF", renamer=RENAMERS["SLGOF"], recordcountername="SATNUM"
)
def density_fromdeck(deck: Union[str, "opm.libopmcommon_python.Deck"],
ntpvt: Optional[int] = None) -> pd.DataFrame:
"""Extract DENSITY from a deck
Args:
deck
ntpvt: Number of PVT regions in deck. Will
be inferred if not present in deck.
"""
if "TABDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("TABDIMS", "NTPVT", deck, ntpvt)
return common.ecl_keyworddata_to_df(deck,
"DENSITY",
renamer=RENAMERS["DENSITY"],
recordcountername="PVTNUM")
def slgof_fromdeck(deck: Union[str, "opm.libopmcommon_python.Deck"],
ntsfun: Optional[int] = None) -> pd.DataFrame:
"""Extract SLGOF data from a deck
Args:
deck
ntsfun: Number of SATNUM regions in deck. Will
be inferred if not present in deck
"""
if "TABDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("TABDIMS", "NTSFUN", deck,
ntsfun)
return common.ecl_keyworddata_to_df(deck,
"SLGOF",
renamer=RENAMERS["SLGOF"],
recordcountername="SATNUM")
def pdvd_fromdeck(deck: Union[str, "opm.libopmcommon_python.Deck"],
ntequl: Optional[int] = None) -> pd.DataFrame:
"""Extract PDVD data from a deck
Args:
deck
ntequl: Number of EQLNUM regions in deck. Will
be inferred if not present in deck
"""
if "EQLDIMS" not in deck:
deck = inferdims.inject_xxxdims_ntxxx("EQLDIMS", "NTEQUL", deck,
ntequl)
return common.ecl_keyworddata_to_df(deck,
"PDVD",
renamer=RENAMERS["PDVD"],
recordcountername="EQLNUM")
def df(
deck: Union[str, "opm.libopmcommon_python.Deck"],
keywords: Optional[List[str]] = None,
ntsfun: Optional[int] = None,
) -> pd.DataFrame:
"""Extract the data in the saturation function keywords as a Pandas
DataFrames.
Data for all saturation functions are merged into one dataframe.
The two first columns in the dataframe are 'KEYWORD' (which can be
SWOF, SGOF, etc.), and then SATNUM which is an index counter from 1 and
onwards. Then follows the data for each individual keyword that
is found in the deck.
SATNUM data can only be parsed correctly if TABDIMS is present
and stating how many saturation functions there should be.
If you have a string with TABDIMS missing, you must supply
this as a string to this function, and not a parsed deck, as
the default parser in EclFiles is very permissive (and only
returning the first function by default).
Arguments:
deck: Incoming data deck. Always
supply as a string if you don't know TABDIMS-NTSFUN.
keywords: Requested keywords for which to
to extract data.
ntsfun: Number of SATNUMs defined in the deck, only
needed if TABDIMS with NTSFUN is not found in the deck.
If not supplied (or None) and NTSFUN is not defined,
it will be attempted inferred.
Return:
pd.DataFrame, columns 'KEYWORD', 'SW', 'KRW', 'KROW', 'PC', ..
"""
if isinstance(deck, EclFiles):
# NB: If this is done on include files and not on DATA files
# we can loose data for SATNUM > 1
deck = deck.get_ecldeck()
deck = inferdims.inject_xxxdims_ntxxx("TABDIMS", "NTSFUN", deck, ntsfun)
assert "TABDIMS" in deck
wanted_keywords = common.handle_wanted_keywords(keywords, deck, SUPPORTED_KEYWORDS)
frames = []
for keyword in wanted_keywords:
frames.append(
interpolate_defaults(
common.ecl_keyworddata_to_df(
deck, keyword, renamer=RENAMERS[keyword], recordcountername="SATNUM"
).assign(KEYWORD=keyword)
)
)
nonempty_frames = [frame for frame in frames if not frame.empty]
if nonempty_frames:
dframe = pd.concat(nonempty_frames, axis=0, sort=False, ignore_index=True)
# We want to sort the keywords by the order they appear in
# SUPPORTED_KEYWORDS (mainly to get WaterOil before GasOil)
# We do that by converting to a Categorical series:
dframe["KEYWORD"] = pd.Categorical(dframe["KEYWORD"], SUPPORTED_KEYWORDS)
dframe.sort_values(["SATNUM", "KEYWORD"], inplace=True)
dframe["KEYWORD"] = dframe["KEYWORD"].astype(str)
return dframe
return pd.DataFrame()
