Nested Hybrid Grids

Overview

The nestedhybridgrid module creates nested hybrid grids where a selected region of a coarse grid is replaced by a refined (subdivided) sub-grid. The two grids are merged into a single grid and connected through Non-Neighbour Connections (NNCs).

The typical workflow is:

1. Define a coarse grid and a region property that marks which cells to refine.

2. Call create_nested_hybrid_grid() to produce the merged grid and an NNC table. You may need to export the NNC file to csv at this stage.

3. Do rescaling from the original gridmodel (e.g. a finer geogrid) to the merged grid, e.g. by using software like RMS.

4. Make another script, that computes transmissibilities with xtgeo.Grid.get_transmissibilities() passing the NNC table.

5. Export the NNC transmissibilities for the flow simulator.

Quick-start example

The example here runs within RMS, but similar workflows can be created for file i/o.

import xtgeo
from fmu.tools.nestedhybridgrid import (
    create_nested_hybrid_grid,
)

# Load grid and region property
grid = xtgeo.grid_from_roxar(project, "Simgrid")
region = xtgeo.gridproperty_from_roxar(project, "Simgrid", "REGION")

# Create nested hybrid grid (e.g. refine region 2 by 2×2×1)
merged, nnc_table = create_nested_hybrid_grid(
    grid, region, target_region_id=2, refinement=(2, 2, 1)
)

# store merged grid in RMS (or file)
merged.to_roxar(project, "NestedHybrid")

merged.get_prop_by_name("NEST_ID")
nest_id.to_roxar(project, "NestedHybrid", nest_id.name)

# write the NNC pandas to disk; this will be applied for computing NNC's in the next script
nnc_table.write_csv("path_to_some_csv_file.csv", index=False)

The next step is to do a rescaling from the original geogrid to the merged grid using e.g. the RMS tool.

Further, we need to create NNC transmissibilities and generate file for flow simulator:

import xtgeo
from fmu.tools.nestedhybridgrid import (
    nnc_to_flowsimulator_input,
    nnc_to_gridproperty,
)

GNAME = "NestedHybrid"

# Load grid and region property which may be stored in RMS
nested = xtgeo.grid_from_roxar(project, GNAME)
region = nested.get_prop_by_name("NEST_ID")  # if needed for QC

# load the NNC table
nnc_table = pd.read_csv("path_to_some_nnc_file.csv")


# Load rescaled property input for transmissibilities and compute
permx = xtgeo.gridproperty_from_roxar(project, GNAME,"PERMX")
permy = xtgeo.gridproperty_from_roxar(project, GNAME,"PERMY")
permz = xtgeo.gridproperty_from_roxar(project, GNAME,"PERMZ")
ntg   = xtgeo.gridproperty_from_roxar(project, GNAME,"NTG")  # defaults to 1 if no NTG

# compute transmissibilities. Note that flow simulators do this for the normal cells/faults
# so strictly speaking, only nnc_hybrid is needed here.
tranx, trany, tranz, nnc_fault, nnc_hybrid, rbnd = merged.get_transmissibilities(
    permx, permy, permz, ntg, nnc_table=nnc_table
)

# Export NNC keyword for Eclipse / OPM Flow
nnc_to_flowsimulator_input(nnc_hybrid, "some_path/NNC_HYBRID.INC")

# Or map NNCs onto grid properties for visualisation
tx_nnc, ty_nnc, tz_nnc = nnc_to_gridproperty(merged, nnc_hybrid)
tx_nnc.to_roxar(project, GNAME, "TRANX_NNC_QC")  # etc

Concepts

NNC table

The NNC table is a DataFrame returned by create_nested_hybrid_grid with columns:

Column	Description
I1, J1, K1	Mother cell indices (1-based)
I2, J2, K2	Refined cell indices (1-based)
DIRECTION	Face direction from the mother cell toward the refined cell (I+, I-, J+, J-, K+, K-)

This table is passed to xtgeo.Grid.get_transmissibilities() via the nnc_table parameter. The transmissibility computation uses geometric face-overlap calculations (Sutherland–Hodgman algorithm) and two-point flux approximation (TPFA).

NEST_ID property

The merged grid carries a discrete property called NEST_ID:

• 0 — inactive hole cells (carved out to make room for the refined region)

• 1 — mother (coarse) cells

• 2 — refined cells

Eclipse / OPM Flow export

nnc_to_flowsimulator_input() writes the NNC keyword in Eclipse format. The output file can be included in the simulator deck:

INCLUDE
  'NNC_HYBRID.INC' /