pycopm.utils.mapping_methods module

Methods to create modified (coarser, finner, submodels, transformations) OPM files.

pycopm.utils.mapping_methods.add_pv_bc(dic)

Add the pore volume from outside the submodel on the xy directions

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.chop_grid(dic)

Extract the corresponding subgrid

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.coarsening_dir(dic)

Get the coarsening directions

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.find_neighbors(dic, ind, i_d, n, s)

Find the neighbouring cells to distribute the removed pore volume

Args:

dic (dict): Global dictionary

ind (list): Indices os cells to distribute the pore volume

i_d (int): Index of the removed cell to distribute its pore volume

n (int): Current increased index for the neighbours search

s (int): Shift to neighbours cells

Returns:

ind (list): Indices os cells to distribute the pore volume

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.get_ijk(dic, i_d)

Return the i,j, and k index from the global index

Args:

dic (dict): Global dictionary

i_d (int): Index of the removed cell to distribute its pore volume

Returns:

i,j,k (int): i,j, and k cell indices

pycopm.utils.mapping_methods.handle_clusters(dic)

Create the coarser clusters

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.handle_cp_grid(dic)

Handle the pillars and zcord for the coarser grid

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.handle_pv(dic, clusmin, clusmax, rmv)

Make sure the pore volume is not created nor destroyed, only distributed

Args:

dic (dict): Global dictionary

clusmin (pandas dataFrame): Mask with all active cells in cluster

clusmax (pandas dataFrame): Mask with at least one active cell in cluster

rmv (pandas dataFrame): Mask to remove cells by the argument flag jump

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.handle_refinement(dic)

Create the refinement objects

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.handle_vicinity(dic)

Create the vicinity objects

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.handle_zcorn(dic, ir)

Process the zcorn

Args:

dic (dict): Global dictionary

ir (list): Z coordinates from the corners

Returns:

ir (list): Modified z coordinates

pycopm.utils.mapping_methods.map_ijk(dic)

Create the mappings to the new i,j,k indices

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.map_properties(dic, actnum, z_t, z_b, z_b_t, v_c)

Mapping to the coarsened properties

Args:

dic (dict): Global dictionary

actnum (array): Integers with the active cells

z_t (array): Floats with the top cell z-center position

z_b (array): Floats with the bottom cell z-center position

z_b_t (array): Floats with the maximum cell z difference

v_c (array): Floats with the cell volumes

Returns:

dic (dict): Modified global dictionary

clusmin (array): True for clusters with at least one inactive cell

clusmax (array): True for clusters with at least one active cell

rmv (array): Indices for the cells to remove

pycopm.utils.mapping_methods.map_vicinity(dic)

Properties to the vicinity

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.refine_grid(dic)

Refine the reservoir grid

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary

pycopm.utils.mapping_methods.transform_grid(dic)

Transform the reservoir grid

Args:

dic (dict): Global dictionary

Returns:

dic (dict): Modified global dictionary