Make FlowNet work with pyscal 0.6.x, and add possibility of using pyscal's SCALrecommendation

CHANGELOG.md

@@ -5,11 +5,14 @@ This project adheres to [Semantic Versioning](https://semver.org/).
 ## [Unreleased]
 
 ### Added
+- [#199](https://github.com/equinor/flownet/pull/199) Added the possibility of defining a 'base' value for all parameters related to relative permeability. This provides the opportunity to interpolate between three relative permeability models. All the 'min' values will be used to construct a pessimistic or low model, the 'base' values are used for a 'base' model, and the 'high' values are used for an optimistic or high model value. The history matching can then be done with only one (two for three phase models - oil/water and gas/oil interpolated independently) relative permeability parameter(s) per SATNUM region.
 - [#188](https://github.com/equinor/flownet/pull/188) The possibility to extract regions from an input simulation model extended to also include SATNUM regions. For relative permeability, the scheme keyword can be set to 'regions_from_sim' in the configuration file.
 - [#189](https://github.com/equinor/flownet/pull/189) User can now provide both a _base_ configuration file, and an optional extra configuration file which will be used to override the base settings.
 
-## [0.3.0] - 2020-09-14
+### Changed
+- [#199](https://github.com/equinor/flownet/pull/199) Removed deprecated parameters in pyscal ('krowend', 'krogend') from config file. Added 'kroend' to config file. 
 
+## [0.3.0] - 2020-09-14
 ### Added
 - [#160](https://github.com/equinor/flownet/pull/160) Adds the possibility to extract regions from an existing model when the data source is a simulation model. For equil, the scheme key can be set to 'regions_from_sim'
 - [#157](https://github.com/equinor/flownet/pull/157) Adds a new 'time-weighted average open perforation location' perforation strategy called `time_avg_open_location`. 

setup.py

@@ -14,7 +14,7 @@
     "opm>=2020.10",
     "pandas~=1.0",
     "pyarrow>=0.14",
-    "pyscal~=0.5.1",
+    "pyscal~=0.6.1",
     "pyvista>=0.23",
     "pyyaml>=5.2",
     "scikit-learn>=0.22",

src/flownet/ahm/_run_ahm.py

@@ -45,7 +45,7 @@ def _from_regions_to_flow_tubes(
         network: FlowNet network instance
         field_data: FlowData class with information from simulation model data source
         ti2ci: A dataframe with index equal to tube model index, and one column which equals cell indices.
-        name: The name of the region parameter
+        region_name: The name of the region parameter
 
     Returns:
         A list with values for 'name' region for each tube in the FlowNet model
@@ -61,7 +61,7 @@ def _from_regions_to_flow_tubes(
             ijk = field_data.grid.find_cell(xyz_mid[0][j], xyz_mid[1][j], xyz_mid[2][j])
             if ijk is not None and field_data.grid.active(ijk=ijk):
                 tube_regions.append(field_data.init(region_name)[ijk])
-        if tube_regions != []:
+        if tube_regions:
             df_regions.append(mode(tube_regions).mode.tolist()[0])
         else:
             df_regions.append(None)
@@ -399,6 +399,12 @@ def run_flownet_history_matching(
 
     relperm_parameters = {key: relperm_dict[key] for key in relperm_dict}
 
+    relperm_interp_values: Optional[pd.DataFrame] = (
+        pd.DataFrame(columns=list(relperm_parameters.keys()) + ["CASE", "SATNUM"])
+        if config.model_parameters.relative_permeability.interpolate
+        else None
+    )
+
     defined_satnum_regions = []
     if config.model_parameters.relative_permeability.scheme == "regions_from_sim":
         relp_config_satnum = config.model_parameters.relative_permeability.regions
@@ -413,13 +419,56 @@ def run_flownet_history_matching(
             idx = defined_satnum_regions.index(i)
         else:
             idx = defined_satnum_regions.index(None)
-        info = [
-            relperm_parameters.keys(),
-            [getattr(relp_config_satnum[idx], key).min for key in relperm_parameters],
-            [getattr(relp_config_satnum[idx], key).max for key in relperm_parameters],
-            [False] * len(relperm_parameters),
-            [i] * len(relperm_parameters),
-        ]
+        if config.model_parameters.relative_permeability.interpolate:
+            interp_info = [
+                [
+                    getattr(relp_config_satnum[idx], key).min
+                    for key in relperm_parameters
+                ]
+                + ["low"]
+                + [i],
+                [
+                    getattr(relp_config_satnum[idx], key).base
+                    for key in relperm_parameters
+                ]
+                + ["base"]
+                + [i],
+                [
+                    getattr(relp_config_satnum[idx], key).max
+                    for key in relperm_parameters
+                ]
+                + ["high"]
+                + [i],
+            ]
+            info: List = [["interpolate"], [-1], [1], [False], [i]]
+            if {"oil", "gas", "water"}.issubset(config.flownet.phases):
+                add_info = ["interpolate gas", -1, 1, False, i]
+                for j, val in enumerate(add_info):
+                    info[j].append(val)
+
+        else:
+            info = [
+                relperm_parameters.keys(),
+                [
+                    getattr(relp_config_satnum[idx], key).min
+                    for key in relperm_parameters
+                ],
+                [
+                    getattr(relp_config_satnum[idx], key).max
+                    for key in relperm_parameters
+                ],
+                [False] * len(relperm_parameters),
+                [i] * len(relperm_parameters),
+            ]
+
+        if isinstance(relperm_interp_values, pd.DataFrame):
+            relperm_interp_values = relperm_interp_values.append(
+                pd.DataFrame(
+                    list(map(list, interp_info)),
+                    columns=list(relperm_parameters.keys()) + ["CASE", "SATNUM"],
+                ),
+                ignore_index=True,
+            )
 
         relperm_dist_values = relperm_dist_values.append(
             pd.DataFrame(
@@ -585,6 +634,7 @@ def run_flownet_history_matching(
             ti2ci,
             df_satnum,
             config.flownet.phases,
+            interpolation_values=relperm_interp_values,
             fast_pyscal=fast_pyscal,
         ),
         Equilibration(