Added facies fractions to VolumetricAnalysis

webviz_subsurface/_figures/px_figure.py

@@ -6,6 +6,8 @@
 import plotly.graph_objects as go
 from pandas.api.types import is_numeric_dtype
 
+VALID_BOXMODES = ["group", "overlay"]
+
 
 def create_figure(plot_type: str, **kwargs: Any) -> go.Figure:
     """Create subplots for selected parameters"""
@@ -33,6 +35,9 @@ def set_default_args(**plotargs: Any) -> dict:
     plotargs["barmode"] = plotargs.get("barmode", "group")
     plotargs["opacity"] = plotargs.get("opacity", 0.7)
 
+    if "boxmode" in plotargs and plotargs["boxmode"] not in VALID_BOXMODES:
+        plotargs["boxmode"] = VALID_BOXMODES[0]
+
     if plotargs.get("facet_col") is not None:
         facet_cols = plotargs["data_frame"][plotargs["facet_col"]].nunique()
         plotargs.update(

webviz_subsurface/_models/inplace_volumes_model.py

@@ -59,9 +59,7 @@ def __init__(
         if volume_type != "dynamic":
             # compute water zone volumes if total volumes are present
             if any(col.endswith("_TOTAL") for col in volumes_table.columns):
-                volumes_table = self._compute_water_zone_volumes(
-                    volumes_table, selectors
-                )
+                volumes_table = self._compute_water_zone_volumes(volumes_table)
 
             # stack dataframe on fluid zone and add fluid as column instead of a column suffix
             dfs = []
@@ -201,15 +199,20 @@ def parameters(self) -> List[str]:
         return self.pmodel.parameters
 
     @staticmethod
-    def _compute_water_zone_volumes(
-        voldf: pd.DataFrame, selectors: list
-    ) -> pd.DataFrame:
+    def _compute_water_zone_volumes(voldf: pd.DataFrame) -> pd.DataFrame:
         """Compute water zone volumes by subtracting HC-zone volumes from
         TOTAL volumes"""
         supported_columns = ["BULK_TOTAL", "NET_TOTAL", "PORE_TOTAL", "PORV_TOTAL"]
+        supported_responses_in_df = [
+            col.replace("_TOTAL", "") for col in supported_columns if col in voldf
+        ]
         # Format check
         for src, df in voldf.groupby("SOURCE"):
-            volcols = [col for col in df if col not in selectors]
+            volcols = [
+                col
+                for col in df
+                if any(col.startswith(resp) for resp in supported_responses_in_df)
+            ]
             if not any(col in volcols for col in supported_columns):
                 continue
             if df[volcols].isnull().values.any():
@@ -221,7 +224,7 @@ def _compute_water_zone_volumes(
                 )
                 return voldf
 
-        for col in [x.replace("_TOTAL", "") for x in voldf if x in supported_columns]:
+        for col in supported_responses_in_df:
             voldf[f"{col}_WATER"] = (
                 voldf[f"{col}_TOTAL"]
                 - voldf.get(f"{col}_OIL", 0)
@@ -247,6 +250,9 @@ def _set_initial_property_columns(self) -> None:
         if all(col in self._dataframe for col in ["HCPV", "PORV"]):
             self._property_columns.append("SW")
 
+        if "FACIES" in self.selectors and "BULK" in self._dataframe:
+            self._property_columns.append("FACIES_FRACTION")
+
         for vol_column in ["STOIIP", "GIIP"]:
             if all(col in self._dataframe for col in ["HCPV", vol_column]):
                 pvt = "BO" if vol_column == "STOIIP" else "BG"
@@ -276,11 +282,11 @@ def compute_property_columns(
         dframe.replace(np.inf, np.nan, inplace=True)
         return dframe
 
-    def get_df(
+    def _get_dataframe_with_volumetrics_and_properties(
         self,
-        filters: Optional[Dict[str, list]] = None,
-        groups: Optional[list] = None,
-        parameters: Optional[list] = None,
+        filters: Dict[str, list],
+        groups: list,
+        parameters: list,
         properties: Optional[list] = None,
     ) -> pd.DataFrame:
         """Function to retrieve a dataframe with volumetrics and properties. Parameters
@@ -290,10 +296,6 @@ def get_df(
         """
         dframe = self.dataframe.copy()
 
-        groups = groups if groups is not None else []
-        filters = filters if filters is not None else {}
-        parameters = parameters if parameters is not None else []
-
         if parameters and self.parameters:
             columns = parameters + ["REAL", "ENSEMBLE"]
             dframe = pd.merge(
@@ -319,8 +321,47 @@ def get_df(
                 dframe["BO"] = np.nan
             if not filters.get("FLUID_ZONE") == ["gas"]:
                 dframe["BG"] = np.nan
+        if "FACIES" not in groups:
+            dframe["FACIES_FRACTION"] = np.nan
+
         return dframe
 
+    def get_df(
+        self,
+        filters: Optional[Dict[str, list]] = None,
+        groups: Optional[list] = None,
+        parameters: Optional[list] = None,
+        properties: Optional[list] = None,
+    ) -> pd.DataFrame:
+        """
+        Function to retrieve a dataframe with volumetrics and properties, using the
+        "_get_dataframe_with_volumetrics_and_properties" method. If FACIES is used as
+        a group selector, the returning dataframe will include facies fractions.
+        Note if FACIES has been included as filter this filter is applied after
+        calculating facies fractions.
+        """
+
+        groups = groups if groups is not None else []
+        filters = filters if filters is not None else {}
+        parameters = parameters if parameters is not None else []
+
+        if "FACIES" not in groups:
+            return self._get_dataframe_with_volumetrics_and_properties(
+                filters, groups, parameters, properties
+            )
+
+        if filters:
+            facies_filter = filters.pop("FACIES")
+
+        dframe = self._get_dataframe_with_volumetrics_and_properties(
+            filters, groups, parameters, properties
+        )
+        groups = [x for x in groups if x != "FACIES"]
+        df = dframe.groupby(groups) if groups else dframe
+        dframe["FACIES_FRACTION"] = df["BULK"].transform(lambda x: x / x.sum())
+
+        return dframe[dframe["FACIES"].isin(facies_filter)] if filters else dframe
+
 
 def filter_df(dframe: pd.DataFrame, filters: dict) -> pd.DataFrame:
     """

webviz_subsurface/plugins/_volumetric_analysis/controllers/comparison_controllers.py

@@ -109,6 +109,9 @@ def comparison_callback(
     ):
         groupby.append("FLUID_ZONE")
 
+    if selections["Response"] == "FACIES_FRACTION" and "FACIES" not in groupby:
+        groupby.append("FACIES")
+
     if display_option == "multi-response table":
         # select max one hc_response for a cleaner table
         responses = [selections["Response"]] + [
@@ -287,7 +290,6 @@ def create_comparison_df(
         df[col, "diff (%)"] = ((df[col][value2] / df[col][value1]) - 1) * 100
         df.loc[df[col]["diff"] == 0, (col, "diff (%)")] = 0
     df = df[responses].replace([np.inf, -np.inf], np.nan).reset_index()
-
     # remove rows where the selected response is nan
     # can happen for properties where the volume columns are 0
     df = df.loc[~((df[resp][value1].isna()) & (df[resp][value2].isna()))]

webviz_subsurface/plugins/_volumetric_analysis/controllers/distribution_controllers.py

@@ -15,9 +15,11 @@
 from webviz_subsurface._models import InplaceVolumesModel
 
 from ..utils.table_and_figure_utils import (
+    FLUID_COLORS,
     create_data_table,
     create_table_columns,
     fluid_annotation,
+    get_text_format_bar_plot,
 )
 from ..utils.utils import move_to_end_of_list, to_ranges
 from ..views.distribution_main_layout import (
@@ -67,6 +69,12 @@ def _update_page_custom(selections: dict, page_selected: str) -> tuple:
                 "oil" if "BO" in selected_data else "gas"
             ]
 
+        if "FACIES_FRACTION" in selected_data and "FACIES" not in groups:
+            return html.Div(
+                "To plot FACIES_FRACTIONS, select 'FACIES' as response, subplot or color",
+                style={"margin-top": "40px"},
+            )
+
         dframe = volumemodel.get_df(
             filters=selections["filters"], groups=groups, parameters=parameters
         )
@@ -98,8 +106,16 @@ def _update_page_custom(selections: dict, page_selected: str) -> tuple:
                 color=selections["Color by"],
                 color_discrete_sequence=selections["Colorscale"],
                 color_continuous_scale=selections["Colorscale"],
+                color_discrete_map=FLUID_COLORS
+                if selections["Color by"] == "FLUID_ZONE"
+                else None,
                 barmode=selections["barmode"],
                 boxmode=selections["barmode"],
+                text_auto=get_text_format_bar_plot(
+                    selected_data, selections, volumemodel
+                )
+                if selections["Plot type"] == "bar"
+                else False,
                 layout=dict(
                     title=dict(
                         text=(
@@ -231,16 +247,16 @@ def _update_page_per_zr(selections: dict, page_selected: str) -> list:
                 layout={"bargap": 0.05},
                 color_discrete_sequence=selections["Colorscale"],
                 color=selections["Color by"],
-                text=selections["X Response"],
                 xaxis=dict(type="category", tickangle=45, tickfont_size=17, title=None),
-            ).update_traces(
-                texttemplate=(
-                    "%{text:.3s}"
-                    if selections["X Response"] in volumemodel.volume_columns
-                    else "%{text:.3g}"
+                text_auto=get_text_format_bar_plot(
+                    responses=[selections["X Response"]],
+                    selections=selections,
+                    volumemodel=volumemodel,
                 ),
-                textposition="auto",
-            )
+                color_discrete_map=FLUID_COLORS
+                if selections["Color by"] == "FLUID_ZONE"
+                else None,
+            ).update_layout(margin_t=35)
 
             if selections["X Response"] not in volumemodel.hc_responses:
                 barfig.add_annotation(fluid_annotation(selections))

webviz_subsurface/plugins/_volumetric_analysis/controllers/selections_controllers.py

@@ -127,6 +127,10 @@ def _store_initial_load_info(
             {"id": get_uuid("selections"), "tab": "voldist", "selector": "Color by"},
             "value",
         ),
+        Input(
+            {"id": get_uuid("selections"), "tab": "voldist", "selector": "X Response"},
+            "value",
+        ),
         State(
             {"id": get_uuid("selections"), "tab": "voldist", "selector": "bottom_viz"},
             "options",
@@ -143,17 +147,20 @@ def _plot_options(
         plot_type: str,
         selected_page: str,
         selected_color_by: list,
+        selected_x_response: str,
         visualization_options: list,
         selector_values: list,
         selector_ids: list,
         previous_selection: Optional[dict],
         selected_tab: str,
     ) -> tuple:
         ctx = callback_context.triggered[0]
-        if (
-            selected_tab != "voldist"
-            or ("Color by" in ctx["prop_id"] and plot_type not in ["box", "bar"])
-            or previous_selection is None
+
+        if selected_tab != "voldist" or previous_selection is None:
+            raise PreventUpdate
+
+        if ("Color by" in ctx["prop_id"] and plot_type not in ["box", "bar"]) or (
+            "X Response" in ctx["prop_id"] and selected_x_response != "FACIES_FRACTION"
         ):
             raise PreventUpdate
 
@@ -184,6 +191,10 @@ def _plot_options(
 
             settings[selector] = {"disable": disable, "value": value}
 
+        # Need to ensure a plot type is selected if page is custopm
+        if settings["Plot type"]["value"] is None and selected_page == "custom":
+            settings["Plot type"]["value"] = "histogram"
+
         # update dropdown options based on plot type
         if settings["Plot type"]["value"] == "scatter":
             y_elm = x_elm = (
@@ -217,6 +228,11 @@ def _plot_options(
         settings["Color by"]["options"] = [
             {"label": elm, "value": elm} for elm in colorby_elm
         ]
+        if settings["X Response"]["value"] == "FACIES_FRACTION":
+            if selected_page == "per_zr":
+                settings["Color by"]["value"] = "FACIES"
+            elif selected_page == "conv":
+                settings["Subplots"]["value"] = "FACIES"
 
         # disable vizualisation radioitem for some pages
         for x in visualization_options:

webviz_subsurface/plugins/_volumetric_analysis/controllers/tornado_controllers.py

@@ -22,7 +22,7 @@
 from ..views.tornado_view import tornado_error_layout, tornado_plots_layout
 
 
-# pylint: disable=too-many-locals, too-many-statements
+# pylint: disable=too-many-locals, too-many-statements, too-many-branches
 def tornado_controllers(
     get_uuid: Callable, volumemodel: InplaceVolumesModel, theme: WebvizConfigTheme
 ) -> None:
@@ -49,6 +49,23 @@ def _update_tornado_pages(
 
         filters = selections["filters"].copy()
 
+        if selections["Response"] == "FACIES_FRACTION" and "FACIES" not in groups:
+            if len(filters.get("FACIES", [])) == 1:
+                groups.append("FACIES")
+            else:
+                return update_relevant_components(
+                    id_list=id_list,
+                    update_info=[
+                        {
+                            "new_value": tornado_error_layout(
+                                "To see tornado for FACIES_FRACTION. Either select "
+                                "'FACIES' as subplot value or filter to only one facies"
+                            ),
+                            "conditions": {"page": page_selected},
+                        }
+                    ],
+                )
+
         figures = []
         tables = []
         responses = (
@@ -340,10 +357,4 @@ def create_tornado_table(
 
     columns = create_table_columns(columns=[subplots]) if subplots is not None else []
     columns.extend(tornado_table.columns)
-    columns.extend(
-        create_table_columns(
-            columns=["Reference"],
-            use_si_format=["Reference"] if use_si_format else [],
-        )
-    )
     return table_data, columns

webviz_subsurface/plugins/_volumetric_analysis/utils/table_and_figure_utils.py

@@ -5,6 +5,14 @@
 import webviz_core_components as wcc
 from dash import dash_table
 
+from webviz_subsurface._models import InplaceVolumesModel
+
+FLUID_COLORS = {
+    "oil": "#007079",
+    "gas": "#FF1243",
+    "water": "#ADD8E6",
+}
+
 
 def create_table_columns(
     columns: list,
@@ -85,11 +93,6 @@ def create_data_table(
 
 
 def fluid_table_style() -> list:
-    fluid_colors = {
-        "oil": "#007079",
-        "gas": "#FF1243",
-        "water": "#ADD8E6",
-    }
     return [
         {
             "if": {
@@ -99,7 +102,7 @@ def fluid_table_style() -> list:
             "color": color,
             "fontWeight": "bold",
         }
-        for fluid, color in fluid_colors.items()
+        for fluid, color in FLUID_COLORS.items()
     ]
 
 
@@ -153,3 +156,19 @@ def update_tornado_figures_xaxis(figures: List[go.Figure]) -> None:
     x_absmax = max([max(abs(trace.x)) for fig in figures for trace in fig.data])
     for fig in figures:
         fig.update_layout(xaxis_range=[-x_absmax, x_absmax])
+
+
+def get_text_format_bar_plot(
+    responses: list, selections: dict, volumemodel: InplaceVolumesModel
+) -> Union[bool, str]:
+    """Get number format for bar plot labels"""
+    if not selections["textformat"]:
+        return False
+
+    if selections["textformat"] == "default":
+        if any(x in responses for x in volumemodel.volume_columns):
+            return f".{selections['decimals']}s"
+        if any(x in responses for x in volumemodel.property_columns):
+            return f".{selections['decimals']}f"
+
+    return f".{selections['decimals']}{selections['textformat']}"