Simulation metadata

webviz_subsurface/_abbreviations/abbreviation_data/reservoir_simulation_unit_terminology.json

@@ -1,17 +1,32 @@
 {
-    "METRIC": 
-    {
-        "SM3": "Sm³",
+    "METRIC": {
+        "M": "m",
         "M3": "m³",
-        "RM3": "m³",
+        "SECONDS": "seconds",
+        "DAYS": "days",
+        "YEARS": "years",
+        "KG/M3": "kg/m³",
+        "BARSA": "bara",
+        "bars": "bar",
+        "K": "K",
+        "C": "\u00B0C",
+        "CP": "cP",
+        "MD": "mD",
+        "SM3": "Sm³",
+        "RM3": "Rm³",
         "SM3/DAY": "Sm³/day",
-        "RM3/DAY": "m³/day",
+        "RM3/DAY": "Rm³/day",
+        "CPR3/DAY/BARS": "Rm³\u00D7cP/day/bar",
+        "MDM": "mD\u00D7m",
+        "KG": "kg",
+        "KG/DAY": "kg/day",
         "SM3/SM3": "Sm³/Sm³",
-        "RM3/SM3": "m³/Sm³",
-        "BARSA": "bara",
-        "BARS": "barg",
+        "RM3/SM3": "Rm³/Sm³",
+        "SM3/RM3": "Sm³/Rm³",
+        "SM3/DAY/BARS": "Sm³/day/bar",
         "SM3/D/B": "Sm³/day/bar",
-        "SECONDS": "s",
-        "DAYS": "days"
-    } 
+        "KJ": "kJ",
+        "KJ/DAY": "kJ/day",
+        "SEC/D": "seconds/day"
+    }
 }

webviz_subsurface/_abbreviations/abbreviation_data/volume_terminology.json

@@ -24,3 +24,4 @@
   "RECOVERABLE_GAS": {"label": "Recoverable volume (gas zone)", "unit": "Sm³"},
   "RECOVERABLE_TOTAL": {"label": "Recoverable volume (total)", "unit": "Sm³"}
 }
+

webviz_subsurface/_abbreviations/number_formatting.py

@@ -2,23 +2,33 @@
 import json
 import pathlib
 import warnings
-from typing import Optional, Union
+from typing import Optional, Union, List
 
 
 _DATA_PATH = pathlib.Path(__file__).parent.absolute() / "abbreviation_data"
 
 SI_PREFIXES = json.loads((_DATA_PATH / "si_prefixes.json").read_text())
 
-TABLE_STATISTICS_BASE = [
-    (
-        i,
-        {
-            "type": "numeric",
-            "format": {"locale": {"symbol": ["", "unit_insert"]}, "specifier": "$.4s",},
-        },
-    )
-    for i in ["Mean", "Stddev", "Minimum", "P90", "P10", "Maximum"]
-]
+
+def table_statistics_base() -> List[tuple]:
+    return [
+        (
+            i,
+            {
+                "type": "numeric",
+                "format": {"locale": {"symbol": ["", ""]}, "specifier": "$.4s",},
+            },
+        )
+        if i != "Stddev"
+        else (
+            i,
+            {
+                "type": "numeric",
+                "format": {"locale": {"symbol": ["", ""]}, "specifier": "$.3s",},
+            },
+        )
+        for i in ["Mean", "Stddev", "Minimum", "P90", "P10", "Maximum"]
+    ]
 
 
 def si_prefixed(

webviz_subsurface/_abbreviations/reservoir_simulation.py

@@ -1,6 +1,9 @@
 import json
 import pathlib
 import warnings
+from typing import Optional
+
+import pandas as pd
 
 
 _DATA_PATH = pathlib.Path(__file__).parent.absolute() / "abbreviation_data"
@@ -14,7 +17,7 @@
 )
 
 
-def simulation_unit_reformat(ecl_unit: str, unit_set: str = "METRIC"):
+def simulation_unit_reformat(ecl_unit: str, unit_set: str = "METRIC") -> str:
     """Returns the simulation unit in a different, more human friendly, format if possible,
     otherwise returns the simulation unit.
     * `ecl_unit`: Reservoir simulation vector unit to reformat
@@ -23,15 +26,14 @@ def simulation_unit_reformat(ecl_unit: str, unit_set: str = "METRIC"):
     return RESERVOIR_SIMULATION_UNIT_TERMINOLOGY[unit_set].get(ecl_unit, ecl_unit)
 
 
-def simulation_vector_base(vector: str):
+def simulation_vector_base(vector: str) -> str:
     """Returns base name of simulation vector
     E.g. WOPR for WOPR:OP_1 and ROIP for ROIP_REG:1
     """
-
     return vector.split(":", 1)[0].split("_", 1)[0]
 
 
-def simulation_vector_description(vector: str):
+def simulation_vector_description(vector: str) -> str:
     """Returns a more human friendly description of the simulation vector if possible,
      otherwise returns the input as is.
     """
@@ -71,3 +73,47 @@ def simulation_vector_description(vector: str):
         )
 
     return description
+
+
+def historical_vector(
+    vector: str,
+    smry_meta: Optional[pd.DataFrame] = None,
+    return_historical: Optional[bool] = True,
+):
+    """This function is trying to make a best guess on converting between historical and
+    non-historical vector names.
+
+    `vector`: An Eclipse-format vector string
+    `smry_meta`: Note: Not activate avaiting https://github.com/equinor/libecl/issues/708
+                 A pandas DataFrame with vector metadata on the format returned by
+                 `load_smry_meta` in `../_datainput/fmu_input.py`. Here the field is_historical is
+                 used to check if a vector is a historical vector.
+    `return_historical`: If return_historical is `True`, the corresponding guessed historical
+                         vector name is returned if the guessed vector is thought to be a
+                         historical vector, else None is returned. If `False` the corresponding
+                         non-historical vector name is returned, if the input vector is thought to
+                         be a historical vector, else None is returned.
+    """
+    smry_meta = None  # Temp deactivation waiting on https://github.com/equinor/libecl/issues/708
+    parts = vector.split(":", 1)
+    if return_historical:
+        parts[0] += "H"
+        hist_vec = ":".join(parts)
+        return (
+            None
+            if historical_vector(hist_vec, smry_meta=smry_meta, return_historical=False)
+            is None
+            else hist_vec
+        )
+
+    if smry_meta is None:
+        if parts[0].endswith("H") and parts[0].startswith(("F", "G", "W")):
+            parts[0] = parts[0][:-1]
+            return ":".join(parts)
+        return None
+
+    try:
+        is_hist = smry_meta.is_historical[vector]
+    except KeyError:
+        is_hist = False
+    return parts[0][:-1] if is_hist else None

webviz_subsurface/_datainput/fmu_input.py

@@ -63,6 +63,24 @@ def load_smry(
     )
 
 
+@CACHE.memoize(timeout=CACHE.TIMEOUT)
+@webvizstore
+def load_smry_meta(
+    ensemble_paths: dict,
+    ensemble_set_name: str = "EnsembleSet",
+    column_keys: Optional[list] = None,
+) -> pd.DataFrame:
+    """Finds metadata for the summary vectors in the ensemble set.
+    Note that we assume the same units for all ensembles.
+    (meaning that we update/overwrite when checking the next ensemble)
+    """
+    ensemble_set = load_ensemble_set(ensemble_paths, ensemble_set_name)
+    smry_meta = {}
+    for ensname in ensemble_set.ensemblenames:
+        smry_meta.update(ensemble_set[ensname].get_smry_meta(column_keys=column_keys))
+    return pd.DataFrame(smry_meta).transpose()
+
+
 @CACHE.memoize(timeout=CACHE.TIMEOUT)
 @webvizstore
 def get_realizations(

webviz_subsurface/_utils/simulation_timeseries.py

@@ -0,0 +1,38 @@
+import warnings
+from typing import Optional
+
+import pandas as pd
+
+
+def set_simulation_line_shape_fallback(line_shape_fallback: str) -> str:
+    """
+    Defines a Plotly line_shape to use if a vector is not thought to be a rate or a total.
+    """
+    line_shape_fallback = line_shape_fallback.lower()
+    if line_shape_fallback in ("backfilled", "backfill"):
+        return "vh"
+    if line_shape_fallback in ["hv", "vh", "hvh", "vhv", "spline", "linear"]:
+        return line_shape_fallback
+    warnings.warn(
+        f"{line_shape_fallback}, is not a valid line_shape option, will use linear."
+    )
+    return "linear"
+
+
+def get_simulation_line_shape(
+    line_shape_fallback: str, vector: str, smry_meta: Optional[pd.DataFrame] = None
+) -> str:
+    """Get simulation time series line shape, smry_meta is a pd.DataFrame on the format given
+    by `load_smry_meta` in `../_datainput/fmu_input.py`.
+    """
+
+    if smry_meta is None:
+        return line_shape_fallback
+    try:
+        if smry_meta.is_rate[vector]:
+            return "vh"
+        if smry_meta.is_total[vector]:
+            return "linear"
+    except (AttributeError, KeyError):
+        pass
+    return line_shape_fallback