Option to remove precomputed values in COMPDAT

docs/_sources/introduction.rst.txt

@@ -41,8 +41,9 @@ where
 -z    Vector of z-coarsening, see the description for -x ('' by default).
 -a    Use `min`, `max`, or `mode` to scale the actnum, e.g., min makes the new coarser cell inactive if at least one cell is inactive, while max makes it active it at least one cell is active (`mode` by default).
 -n    Use `min`, `max`, or `mode` to scale endnum, eqlnum, fipnum, fluxnum, imbnum, miscnum, multnum, pvtnum, rocknum, and satnum (`mode` by default).
--s    Use `min`, `max`, or `mean` to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz ('' by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, and the mean for the rest).
+-s    Use `min`, `max`, or `mean` to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz ('' by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, mean for mult(-)xyz, and the pore volume weighted mean for the rest).
 -p    Add the removed pore volume to the closest coarser cells (`0` by default, `1` to enable).
+-r    Remove CONFACT and KH from COMPDAT (`1`) and also remove PEQVR (`2`) (ITEM 13, the last entry) to compute the well transmisibility connections internally in OPM Flow using the grid properties (`2` by default; `0` to not remove).
 -j    Tuning parameter to avoid creation of neighbouring connections in the coarser model where there are discontinuities between cells along the z direction, e.g., around faults ('' by default, i.e., nothing corrected; if need it, try with values of the order of 1).
 -m    Execute a dry run on the input deck to generate the static properties ('prep'), generate only the coarse files ('deck'), only exectute a dry run on the generated coarse model ('dry'), 'prep_deck', 'deck_dry', or do all ('all') (`prep_deck` by default).
 -w    Name of the generated deck ('' by default, i.e., the name of the input deck plus _PYCOPM.DATA).

docs/introduction.html

@@ -139,11 +139,14 @@ <h2>Roadmap<a class="headerlink" href="#roadmap" title="Link to this heading">
 <dd><p>Use <cite>min</cite>, <cite>max</cite>, or <cite>mode</cite> to scale endnum, eqlnum, fipnum, fluxnum, imbnum, miscnum, multnum, pvtnum, rocknum, and satnum (<cite>mode</cite> by default).</p>
 </dd>
 <dt><kbd><span class="option">-s</span></kbd></dt>
-<dd><p>Use <cite>min</cite>, <cite>max</cite>, or <cite>mean</cite> to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz (’’ by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, and the mean for the rest).</p>
+<dd><p>Use <cite>min</cite>, <cite>max</cite>, or <cite>mean</cite> to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz (’’ by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, mean for mult(-)xyz, and the pore volume weighted mean for the rest).</p>
 </dd>
 <dt><kbd><span class="option">-p</span></kbd></dt>
 <dd><p>Add the removed pore volume to the closest coarser cells (<cite>0</cite> by default, <cite>1</cite> to enable).</p>
 </dd>
+<dt><kbd><span class="option">-r</span></kbd></dt>
+<dd><p>Remove CONFACT and KH from COMPDAT (<cite>1</cite>) and also remove PEQVR (<cite>2</cite>) (ITEM 13, the last entry) to compute the well transmisibility connections internally in OPM Flow using the grid properties (<cite>2</cite> by default; <cite>0</cite> to not remove).</p>
+</dd>
 <dt><kbd><span class="option">-j</span></kbd></dt>
 <dd><p>Tuning parameter to avoid creation of neighbouring connections in the coarser model where there are discontinuities between cells along the z direction, e.g., around faults (’’ by default, i.e., nothing corrected; if need it, try with values of the order of 1).</p>
 </dd>

docs/text/introduction.rst

@@ -41,8 +41,9 @@ where
 -z    Vector of z-coarsening, see the description for -x ('' by default).
 -a    Use `min`, `max`, or `mode` to scale the actnum, e.g., min makes the new coarser cell inactive if at least one cell is inactive, while max makes it active it at least one cell is active (`mode` by default).
 -n    Use `min`, `max`, or `mode` to scale endnum, eqlnum, fipnum, fluxnum, imbnum, miscnum, multnum, pvtnum, rocknum, and satnum (`mode` by default).
--s    Use `min`, `max`, or `mean` to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz ('' by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, and the mean for the rest).
+-s    Use `min`, `max`, or `mean` to scale permx, permy, permz, poro, swatinit, and all mult(-)xyz ('' by default, i.e., using the arithmetic average for permx/permy, harmonic average for permz, mean for mult(-)xyz, and the pore volume weighted mean for the rest).
 -p    Add the removed pore volume to the closest coarser cells (`0` by default, `1` to enable).
+-r    Remove CONFACT and KH from COMPDAT (`1`) and also remove PEQVR (`2`) (ITEM 13, the last entry) to compute the well transmisibility connections internally in OPM Flow using the grid properties (`2` by default; `0` to not remove).
 -j    Tuning parameter to avoid creation of neighbouring connections in the coarser model where there are discontinuities between cells along the z direction, e.g., around faults ('' by default, i.e., nothing corrected; if need it, try with values of the order of 1).
 -m    Execute a dry run on the input deck to generate the static properties ('prep'), generate only the coarse files ('deck'), only exectute a dry run on the generated coarse model ('dry'), 'prep_deck', 'deck_dry', or do all ('all') (`prep_deck` by default).
 -w    Name of the generated deck ('' by default, i.e., the name of the input deck plus _PYCOPM.DATA).

src/pycopm/core/pycopm.py

@@ -33,6 +33,7 @@ def pycopm():
     dic["mode"] = cmdargs["mode"].strip()  # What to run
     dic["label"] = cmdargs["label"].strip()  # Prefix to the generted inc files
     dic["ijk"] = cmdargs["ijk"].strip()  # ijk indices to map to the coarse model
+    dic["remove"] = int(cmdargs["remove"].strip())  # Remove CONFACT and KH
     dic["encoding"] = cmdargs["encoding"].strip()
     dic["pvcorr"] = int(cmdargs["pvcorr"])
     dic["cijk"] = "yes"
@@ -177,14 +178,23 @@ def load_parser():
         default="",
         help="Use 'min', 'max', or 'mean' to scale permx, permy, permz, poro, swatinit, and all "
         "mult(-)xyz ('' by default, i.e., using the arithmetic average for permx/permy, harmonic"
-        " average for permz, and the mean for the rest).",
+        " average for permz, mean for mult(-)xyz, and the pore volume weighted mean for the "
+        "rest).",
     )
     parser.add_argument(
         "-p",
         "--pvcorr",
         default=0,
         help="Add the removed pore volume to the closest coarser cells ('0' by default).",
     )
+    parser.add_argument(
+        "-r",
+        "--remove",
+        default="2",
+        help="Remove CONFACT and KH from COMPDAT (1) and also remove PEQVR (2) (ITEM 13, the "
+        "last entry) to compute the well transmisibility connections internally in OPM Flow "
+        "using the grid properties ('2' by default; '0' to not remove).",
+    )
     parser.add_argument(
         "-j",
         "--jump",

src/pycopm/utils/generate_coarser_files.py

@@ -72,7 +72,7 @@ def create_deck(dic):
                 )
                 sys.exit()
         dic["field"] = "generic"
-        dic["props"] = ["poro", "permx", "permy", "permz"]
+        dic["props"] = ["permx", "permy", "permz", "poro"]
         dic["base"] = dic["props"] + ["grid"]
         dic["regions"] = []
         dic["grids"] = []
@@ -137,16 +137,17 @@ def create_deck(dic):
                         n
                     ]
                 if not dic["show"]:
-                    dic["permx"][cell.global_index] = (
-                        dic["ini"].iget_kw("PERMX")[0][n] * d_z[cell.global_index]
-                    )
-                    dic["permy"][cell.global_index] = (
-                        dic["ini"].iget_kw("PERMY")[0][n] * d_z[cell.global_index]
-                    )
-                    if dic["ini"].iget_kw("PERMZ")[0][n] != 0:
+                    dic["permx"][cell.global_index] *= d_z[cell.global_index]
+                    dic["permy"][cell.global_index] *= d_z[cell.global_index]
+                    if dic["permz"][cell.global_index] != 0:
                         dic["permz"][cell.global_index] = (
-                            d_z[cell.global_index] / dic["ini"].iget_kw("PERMZ")[0][n]
+                            d_z[cell.global_index] / dic["permz"][cell.global_index]
                         )
+                    dic["poro"][cell.global_index] *= dic["porv"][cell.global_index]
+                    if "swatinit" in dic["props"]:
+                        dic["swatinit"][cell.global_index] *= dic["porv"][
+                            cell.global_index
+                        ]
                 n += 1
 
         # Coarsening
@@ -229,24 +230,26 @@ def map_properties(dic, actnum, d_z, z_t, z_b, z_b_t):
     else:
         rmv = 0 * dz_c + 1
         dic["actnum_c"] = [int(val) for val in clust]
-    c_c = pd.Series(dic["porv"]).groupby(dic["con"]).sum()
-    dic["porv_c"] = [f"{val}" for val in c_c]
+    p_vs = pd.Series(dic["porv"]).groupby(dic["con"]).sum()
+    dic["porv_c"] = [f"{val}" for val in p_vs]
     for name in dic["props"]:
         if not dic["show"]:
+            c_c = pd.Series(dic[name]).groupby(dic["con"]).sum()
             if name in ["permx", "permy"]:
-                c_c = pd.Series(dic[name]).groupby(dic["con"]).sum()
                 dic[f"{name}_c"] = [
                     f"{val/h_t}" if h_t * val > 0 else "0"
                     for val, h_t in zip(c_c, h_tot)
                 ]
             elif name == "permz":
-                c_c = pd.Series(dic[name]).groupby(dic["con"]).sum()
                 dic["permz_c"] = [
                     f"{h_t/val}" if h_t * val > 0 else "0"
                     for val, h_t in zip(c_c, h_tot)
                 ]
+            elif name in ["poro", "swatinit"]:
+                dic[f"{name}_c"] = [
+                    f"{val/p_v}" if p_v > 0 else "0" for val, p_v in zip(c_c, p_vs)
+                ]
             else:
-                c_c = pd.Series(dic[name]).groupby(dic["con"]).sum()
                 dic[f"{name}_c"] = [
                     f"{val/fre}" if fre > 0 else "0" for val, fre in zip(c_c, freq)
                 ]
@@ -877,6 +880,12 @@ def handle_segmented_wells(dic, nrwo):
                 edit[2] = str(dic["jc"][int(edit[2])])
                 edit[3] = str(dic["kc"][int(edit[3])])
                 edit[4] = str(dic["kc"][int(edit[4])])
+                if dic["remove"] > 0 and len(edit) > 7:
+                    edit[7] = "1*"
+                if dic["remove"] > 0 and len(edit) > 9:
+                    edit[9] = "1*"
+                if dic["remove"] > 1 and len(edit) > 12:
+                    edit[-2] = ""
                 dic["lol"].append(" ".join(edit))
                 return True
     if dic["compsegs"]: