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The Convert 3D Data to 2D Data tool is used to convert 3D cell data to a 2D UGrid with data sets. The user selects a 3D cell data set as input to the tool (the data set may have multiple time steps). Then the user may choose to output multiple data sets from the tool; the following data sets may be computed by the tool: highest active value, average, maximum, minimum, value for each layer. The 3D UGrid cells are organized into columns of cells to compute the various output data sets. Examples follow that explain how the tool works for different types of UGrids.
===Convert 3D Data to 2D Data===
The ''Convert 3D Data to 2D Data'' tool is used to convert 3D cell data to a 2D UGrid with datasets. The user selects a 3D cell dataset as input to the tool (the dataset may have multiple time steps). Then the user may choose to output multiple datasets from the tool; the following datasets may be computed by the tool: highest active value, average, maximum, minimum, value for each layer. The 3D UGrid cells are organized into columns of cells to compute the various output datasets. Examples follow that explain how the tool works for different types of UGrids.
This tool will only work on UGrids that are made up of 3D cells and those cells must all be prisms (the side faces of the cells must be vertical). Further, the grid must have layers assigned to the cells. The tool will return an error if any of these conditions are not met.  
This tool will only work on UGrids that are made up of 3D cells and those cells must all be prisms (the side faces of the cells must be vertical). Further, the grid must have layers assigned to the cells. The tool will return an error if any of these conditions are not met.  
Input parameters
====Input parameters====
Cell data set– The input 3D data set that will be converted to 2D data sets
*''Cell dataset'' – The input 3D dataset that will be converted to 2D datasets
Name of the output grid Name for the newly created 2D UGrid. If this value is left blank then the name of the output grid will be set to be the name of the input cell data set.
*Name of the output grid – Name for the newly created 2D UGrid. If this value is left blank then the name of the output grid will be set to be the name of the input cell dataset.
Compute highest active cell in column Option to output a 2D data set where the value will come from the highest active cell in the 3D column of cells.
*''Compute highest active cell in column'' – Option to output a 2D dataset where the value will come from the highest active cell in the 3D column of cells.
Compute average value in column Option to output a 2D data set of the average value in the 3D column of cells.  
*''Compute average value in column'' – Option to output a 2D dataset of the average value in the 3D column of cells.  
Compute maximum value in column Option to output a 2D data set of the maximum value in the 3D column of cells.  
*''Compute maximum value in column'' – Option to output a 2D dataset of the maximum value in the 3D column of cells.  
Compute minimum value in column Option to output a 2D data set of the minimum value in the 3D column of cells.  
*''Compute minimum value in column'' – Option to output a 2D dataset of the minimum value in the 3D column of cells.  
Compute value for each layer in column - Option to output 2D data sets of the value for each layer in the 3D column of cells.  
*''Compute value for each layer in column'' – Option to output 2D datasets of the value for each layer in the 3D column of cells.
Output parameters
 
The output is a 2D UGrid and data sets.
====Output parameters====
Current location in Toolbox
*The output is a 2D UGrid and datasets.
UGrids/Convert 3D Data to 2D Data
 
Examples  
====Current location in Toolbox====
Files for example 1 and example 3 can be downloaded here. (Include a link to download these files.)
Unstructured Grids/Convert 3D Data to 2D Data
Example 1
 
====Examples====
Files for example 1 and example 3 can be downloaded [https://s3.amazonaws.com/gmstutorials.aquaveo.com/3d_to_2d.zip here].  
=====Example 1=====
The first example is a simple structured 3D Grid. The grid is made up of 4 rows, 4 columns, and 3 layers.  
The first example is a simple structured 3D Grid. The grid is made up of 4 rows, 4 columns, and 3 layers.  
 
:[[File:2D-3dUgrid3layer4by4.png|thumb|none|400 px|Example 1 UGrid]] 
The data set “elev” has constant values for each layer of the grid: layer 1 – 41.6, layer 2 – 25.0, and layer 3 – 8.3. Running the tool on this data set produces the following 2D UGrid and data sets.
The dataset “elev” has constant values for each layer of the grid: layer 1 – 41.6, layer 2 – 25.0, and layer 3 – 8.3. Running the tool on this dataset produces the following 2D UGrid and datasets.
:[[File:2D-3Dprojectexplorerelevhighestactive.png|thumb|none|200 px|Example 1 results]]
:[[File:2D-3dUGridHighestActiveElev.png|thumb|none|400 px|Example 1 elevation highest active]]
In this example the data sets are straight forward.  
In this example the datasets are straight forward.  
The elev_highest_active creates a data set with values from the top of the 3D UGrid. All of the values are 41.6. The elev_average data set gives the average value in each cell column and in this case that will match the values from layer 2 of the 3D UGrid (25.0). The elev_max data set matches the values of the top layer of the 3D UGrid (41.6). The elev_min data set matches the values from the bottom layer of the 3D UGrid (8.3). The elev_layer_1, elev_layer_2, and elev_layer_3 match the values from the respective layer of the 3D UGrid.
 
Example 2
The "elev_highest_active" creates a dataset with values from the top of the 3D UGrid. All of the values are 41.6. The "elev_average" dataset gives the average value in each cell column and in this case that will match the values from layer 2 of the 3D UGrid (25.0). The elev_max dataset matches the values of the top layer of the 3D UGrid (41.6). The "elev_min" dataset matches the values from the bottom layer of the 3D UGrid (8.3). The "elev_layer_1", "elev_layer_2", and "elev_layer_3" match the values from the respective layer of the 3D UGrid.
The second example is the same 3D Grid from example 1 except in this case the 3D data set has activity. That is to say, some of the values in the data set are considered inactive.  The cells with inactive values are shown in red in the following figure.
 
=====Example 2=====
The second example is the same 3D Grid from example 1 except in this case the 3D dataset has activity. That is to say, some of the values in the dataset are considered inactive.  The cells with inactive values are shown in red in the following figure.
:[[File:2D-3dUGridInactiveValues.png|thumb|none|400 px|Ugrid with inactive values shown in red]]
Typically, these values are not contoured on the 3D UGrid.
Typically, these values are not contoured on the 3D UGrid.
:[[File:2D-3dUGridInactiveValuesMissing.png|thumb|none|400 px|Ugrid with inactive value not contoured]]
When the tool runs with this example the following datasets are created. First, examine the layer datasets and notice the effect that activity has on the created datasets.
:[[File:2D-3dUGridLayerActivity.png|thumb|none|200 px|Example 2 results]]
The "active_layer_1" dataset shows the 2 cells with inactive values.
:[[File:2D-3dUGridLayer1activity.png|thumb|none|400 px|Layer 1 active layer]]
The "active_layer_2" dataset show the 1 cell with an inactive value.
:[[File:2D-3dUGridlayer2activity.png|thumb|none|400 px|Layer 2 active layer]]
The "active_layer_3" dataset shows the 1 cell with an inactive value.
:[[File:2D-3dUGridlayer3activity.png|thumb|none|400 px|Layer 3 active layer]]
The "active_highest_active" has values from 2 of the lower layers in the 3D UGrid.
:[[File:2D-3dUGridactivehighest.png|thumb|none|400 px|Highest active result]]
The "active_average" has 3 values that are affected by the dataset activity. The "active_maximum" and "active_minimum" datasets are similar to the "active_average".
:[[File:2D-3dUGridactiveaverage.png|thumb|none|400 px|Active average result]]
=====Example 3=====
The third example is a 3D UGrid with variable number of cells per layer and variable refinement in each layer. A figure of the entire grid is shown, followed by figures of individual layers.
:[[File:2D-3dUGridVariableCells.png|thumb|none|400 px| Grid with variable number of cells per layer]]
Layer 2 of the 3D UGrid:
:[[File:2D-3dUGridVariableLayer1.png|thumb|none|400 px| Layer 2 of the Ugrid]]
Layer 3 of the 3D UGrid:
:[[File:2D-3dUGridVarialbeLayer2.png|thumb|none|400 px| Layer 3 of the Ugrid]]
Layer 4 of the 3D UGrid:
:[[File:2D-3dUGridVariableLayer3.png|thumb|none|400 px| Layer 4 of the Ugrid]]
Layer 5 of the 3D UGrid:
:[[File:2D-3dUGridVariableLayer4.png|thumb|none|400 px| Layer 5 of the Ugrid]]
When the tool is run with this example the following datasets are created.
:[[File:2D-3dProjectExplorerVariableUgrid.png|thumb|none|200 px|Example 3 results]]
The next figure shows the resulting 2D UGrid with the "elev_highest_active" dataset contoured.
:[[File:2D-3DVariablehighestactiveresult.png|thumb|none|400 px|THe "elev_highest_active" dataset]]
Notice that the 2D cells are defined by the smallest 3D cells in any column. The 2 cells that are not pink have values that came from layer 2 of the 3D Grid. The "elev_average", "elev_maximum", "elev_minimum" are computed in a straight forward manner and are not shown here.
The "elev_layer" datasets are shown next. Notice that some layer datasets have inactive values because there were no cells defined  in those cell columns.
   
   
When the tool runs with this example the following data sets are created. First, examine the layer data sets and notice the effect that activity has on the created data sets.
The "elev_layer_1" dataset:
:[[File:2D-3DVariableLayer1result.png|thumb|none|400 px| The "elev_layer1" dataset]]
The "elev_layer_2" dataset:
The active_layer_1 data set shows the 2 cells with inactive values.
:[[File:2D-3DVariableLayer2result.png|thumb|none|400 px| The "elev_layer2" dataset]]
The "elev_layer_3" dataset:
The active_layer_2 data set show the 1 cell with an inactive value.
:[[File:2D-3DVariableLayer3result.png|thumb|none|400 px| The "elev_layer3" dataset]]
The "elev_layer_4" dataset:
The active_layer_3 data set shows the 1 cell with an inactive value.
:[[File:2D-3DVariableLayer4result.png|thumb|none|400 px| The "elev_layer4" dataset]]
The "elev_layer_5" dataset:
The active_highest_active has values from 2 of the lower layers in the 3D UGrid.
:[[File:2D-3DVariableLayer5result.png|thumb|none|400 px| The "elev_layer5" dataset]]
 
The active_average has 3 values that are affected by the data set activity. The active_maximum and active_minimum data sets are similar to the active_average.
=====Example 4=====
Example 3
The fourth example uses the same 3D UGrid as example 3 and the dataset now includes activity. The orange cells in the grid have a value of 5. The red cells have inactive dataset values.
The third example is a 3D Grid with variable number of cells per layer and variable refinement in each layer. A figure of the entire Grid is shown, followed by figures of individual layers.
:[[File:2D-3DUGridExample4.png|thumb|none|400 px|Example 4 UGrid]]
Layer 2 values for 3D UGrid:
:[[File:2D-3DUGridExample4layer2.png|thumb|none|400 px|Example 4 UGrid layer 2]]
Layer 2 of the 3D UGrid.
Layer 3 of the 3D UGrid.
Layer 4 of the 3D UGrid.
Layer 5 of the 3D UGrid.
When the tool is run with this example the following data sets are created.
The next figure shows the resulting 2D UGrid with the elev_highest_active data set contoured.
Notice that the 2D cells are defined by the smallest 3D cells in any column. The 2 cells that are not pink have values that came from layer 2 of the 3D Grid. The elev_average, elev_maximum, elev_minimum are computed in a straight forward manner and are not shown here.
The elev_layer data sets are shown next. Notice that some layer data sets have inactive values because there were no cells defined  in those cell columns.
The elev_layer_1 data set.
The elev_layer_2 data set.
The elev_layer_3 data set.
The elev_layer_4 data set.
The elev_layer_4 data set.
Example 4
The fourth example uses the same 3D UGrid as example 3 and the data set now includes activity. The orange cells in the grid have a value of 5. The red cells have inactive data set values.
Layer 2 values for 3D UGrid.
When the tool is executed the following results are generated from the tool.
When the tool is executed the following results are generated from the tool.
   
   
The active_highest_active data set result.
The "active_highest_active" dataset result:
:[[File:2D-3DUGridExample4ActiveHighest.png|thumb|none|400 px|Example 4 Active highest dataset]]
The active_layer_1 data set.
The "active_layer_1" dataset:
:[[File:2D-3DUGridExample4activelayer1.png|thumb|none|400 px|Example 4 active layer 1 dataset]]
The active_layer_2 data set.
The "active_layer_2" dataset:
:[[File:2D-3DUGridExample4activelayer2.png|thumb|none|400 px|Example 4 active layer 2 dataset]]
The active_layer_3 data set.
The "active_layer_3" dataset:
:[[File:2D-3DUGridExample4activelayer3.png|thumb|none|400 px|Example 4 active layer 3 dataset]]
The active_layer_4 data set.
The "active_layer_4" dataset:
:[[File:2D-3DUGridExample4activelayer4.png|thumb|none|400 px|Example 4 active layer 4 dataset]]
The active_layer_5 data set.
The "active_layer_5" dataset:
Example 5
:[[File:2D-3DUGridExample4activelayer5.png|thumb|none|400 px|Example 4 active layer 5 dataset]]
 
=====Example 5=====
The fifth example is a voronoi 3D UGrid.  This grid has a variable number of cells in each layer.  This example comes from the MODFLOW-USG Complex Stratigraphy tutorial.  
The fifth example is a voronoi 3D UGrid.  This grid has a variable number of cells in each layer.  This example comes from the MODFLOW-USG Complex Stratigraphy tutorial.  
:[[File:2D-3DvoronoiUGrid.png|thumb|none|400 px|Example 5 Voronoi UGrid]]
Layer 2 of 3D UGrid:
Layer 2 of 3D UGrid
:[[File:2D-3DvoronoiUGridlayer2.png|thumb|none|400 px|Example 4 layer 2 of the Voronoi Ugrid]]
Layer 3 of 3D UGrid:
Layer 3 of 3D UGrid
:[[File:2D-3DvoronoiUGridlayer3.png|thumb|none|400 px|Example 4 layer 3 of the Voronoi Ugrid]]
Layer 4 of 3D UGrid:
Layer 4 of 3D UGrid
:[[File:2D-3DvoronoiUGridlayer4.png|thumb|none|400 px|Example 4 layer 4 of the Voronoi Ugrid]]
Layer 5 of 3D UGrid:
Layer 5 of 3D UGrid.
:[[File:2D-3DvoronoiUGridlayer5.png|thumb|none|400 px|Example 4 layer 5 of the Voronoi Ugrid]]
When the tool is run  the following figure shows the output 2D UGrid.
When the tool is run  the following figure shows the output 2D UGrid:
:[[File:2D-3DvoronoiUGridoutput.png|thumb|none|400 px|Example 4 Voronoi UGrid output]]
<noinclude>[[Category:Tools]]</noinclude>
<noinclude>[[Category:Toolbox UGrid]]</noinclude>

Latest revision as of 15:02, 24 October 2023


Convert 3D Data to 2D Data

The Convert 3D Data to 2D Data tool is used to convert 3D cell data to a 2D UGrid with datasets. The user selects a 3D cell dataset as input to the tool (the dataset may have multiple time steps). Then the user may choose to output multiple datasets from the tool; the following datasets may be computed by the tool: highest active value, average, maximum, minimum, value for each layer. The 3D UGrid cells are organized into columns of cells to compute the various output datasets. Examples follow that explain how the tool works for different types of UGrids. This tool will only work on UGrids that are made up of 3D cells and those cells must all be prisms (the side faces of the cells must be vertical). Further, the grid must have layers assigned to the cells. The tool will return an error if any of these conditions are not met.

Input parameters

  • Cell dataset – The input 3D dataset that will be converted to 2D datasets
  • Name of the output grid – Name for the newly created 2D UGrid. If this value is left blank then the name of the output grid will be set to be the name of the input cell dataset.
  • Compute highest active cell in column – Option to output a 2D dataset where the value will come from the highest active cell in the 3D column of cells.
  • Compute average value in column – Option to output a 2D dataset of the average value in the 3D column of cells.
  • Compute maximum value in column – Option to output a 2D dataset of the maximum value in the 3D column of cells.
  • Compute minimum value in column – Option to output a 2D dataset of the minimum value in the 3D column of cells.
  • Compute value for each layer in column – Option to output 2D datasets of the value for each layer in the 3D column of cells.

Output parameters

  • The output is a 2D UGrid and datasets.

Current location in Toolbox

Unstructured Grids/Convert 3D Data to 2D Data

Examples

Files for example 1 and example 3 can be downloaded here.

Example 1

The first example is a simple structured 3D Grid. The grid is made up of 4 rows, 4 columns, and 3 layers.

Example 1 UGrid

The dataset “elev” has constant values for each layer of the grid: layer 1 – 41.6, layer 2 – 25.0, and layer 3 – 8.3. Running the tool on this dataset produces the following 2D UGrid and datasets.

Example 1 results
Example 1 elevation highest active

In this example the datasets are straight forward.

The "elev_highest_active" creates a dataset with values from the top of the 3D UGrid. All of the values are 41.6. The "elev_average" dataset gives the average value in each cell column and in this case that will match the values from layer 2 of the 3D UGrid (25.0). The elev_max dataset matches the values of the top layer of the 3D UGrid (41.6). The "elev_min" dataset matches the values from the bottom layer of the 3D UGrid (8.3). The "elev_layer_1", "elev_layer_2", and "elev_layer_3" match the values from the respective layer of the 3D UGrid.

Example 2

The second example is the same 3D Grid from example 1 except in this case the 3D dataset has activity. That is to say, some of the values in the dataset are considered inactive. The cells with inactive values are shown in red in the following figure.

Ugrid with inactive values shown in red

Typically, these values are not contoured on the 3D UGrid.

Ugrid with inactive value not contoured

When the tool runs with this example the following datasets are created. First, examine the layer datasets and notice the effect that activity has on the created datasets.

Example 2 results

The "active_layer_1" dataset shows the 2 cells with inactive values.

Layer 1 active layer

The "active_layer_2" dataset show the 1 cell with an inactive value.

Layer 2 active layer

The "active_layer_3" dataset shows the 1 cell with an inactive value.

Layer 3 active layer

The "active_highest_active" has values from 2 of the lower layers in the 3D UGrid.

Highest active result

The "active_average" has 3 values that are affected by the dataset activity. The "active_maximum" and "active_minimum" datasets are similar to the "active_average".

Active average result
Example 3

The third example is a 3D UGrid with variable number of cells per layer and variable refinement in each layer. A figure of the entire grid is shown, followed by figures of individual layers.

Grid with variable number of cells per layer

Layer 2 of the 3D UGrid:

Layer 2 of the Ugrid

Layer 3 of the 3D UGrid:

Layer 3 of the Ugrid

Layer 4 of the 3D UGrid:

Layer 4 of the Ugrid

Layer 5 of the 3D UGrid:

Layer 5 of the Ugrid

When the tool is run with this example the following datasets are created.

Example 3 results

The next figure shows the resulting 2D UGrid with the "elev_highest_active" dataset contoured.

THe "elev_highest_active" dataset

Notice that the 2D cells are defined by the smallest 3D cells in any column. The 2 cells that are not pink have values that came from layer 2 of the 3D Grid. The "elev_average", "elev_maximum", "elev_minimum" are computed in a straight forward manner and are not shown here.

The "elev_layer" datasets are shown next. Notice that some layer datasets have inactive values because there were no cells defined in those cell columns.

The "elev_layer_1" dataset:

The "elev_layer1" dataset

The "elev_layer_2" dataset:

The "elev_layer2" dataset

The "elev_layer_3" dataset:

The "elev_layer3" dataset

The "elev_layer_4" dataset:

The "elev_layer4" dataset

The "elev_layer_5" dataset:

The "elev_layer5" dataset
Example 4

The fourth example uses the same 3D UGrid as example 3 and the dataset now includes activity. The orange cells in the grid have a value of 5. The red cells have inactive dataset values.

Example 4 UGrid

Layer 2 values for 3D UGrid:

Example 4 UGrid layer 2

When the tool is executed the following results are generated from the tool.

The "active_highest_active" dataset result:

Example 4 Active highest dataset

The "active_layer_1" dataset:

Example 4 active layer 1 dataset

The "active_layer_2" dataset:

Example 4 active layer 2 dataset

The "active_layer_3" dataset:

Example 4 active layer 3 dataset

The "active_layer_4" dataset:

Example 4 active layer 4 dataset

The "active_layer_5" dataset:

Example 4 active layer 5 dataset
Example 5

The fifth example is a voronoi 3D UGrid. This grid has a variable number of cells in each layer. This example comes from the MODFLOW-USG Complex Stratigraphy tutorial.

Example 5 Voronoi UGrid

Layer 2 of 3D UGrid:

Example 4 layer 2 of the Voronoi Ugrid

Layer 3 of 3D UGrid:

Example 4 layer 3 of the Voronoi Ugrid

Layer 4 of 3D UGrid:

Example 4 layer 4 of the Voronoi Ugrid

Layer 5 of 3D UGrid:

Example 4 layer 5 of the Voronoi Ugrid

When the tool is run the following figure shows the output 2D UGrid:

Example 4 Voronoi UGrid output