Simulation Post-processing

The Simulation Post-processing task is designed to perform statistical calculations on the results of numerical simulations (macro variable), such as the average of simulations, confidence intervals, probability of exceeding a threshold, etc. The tool offers the same post-processing results as in Simulations, but you can easily add a new statistical output without recomputing the entire set of simulations, which can be time consuming.

Input

Click the directory icon to pop up a Data Selector and select the input Data table which contains the simulation results. The input file is mainly a Grid file, but it can be of any type, Sub-blocks, Points, etc. This data table can also be defined by a simple and quick drag-and-drop from the Data tab. A Selection variable may be specified. In this case, only the samples defined by the selection (i.e. samples where the value of the selection is equal to 1) will be considered for the calculations. This selection can also be defined by a categorical variable.
Then define the Simulation set to be considered for the statistical calculations. It must be a numerical macro variable. You can select several simulation sets. In this case, the same kind of statistics will be calculated on output for each simulation set.

Output & Parameters

The objective of the Pattern (and Context) parameter is to help the definition of output results names. You can edit this pattern and define the name of your choice. Click on to retrieve the default pattern: %context-%var-%label

The Label section is editable by a double-click for modification. The Preview enables you to see the final name associated to each output result (for the first simulation set).

You may then specify several output variables grouped in three different tabs:

General: Under this tab, you will find main statistics (mean value, standard deviation, variance, coefficient of variation, minimum or maximum of the realizations of the target variable and quantiles).
- Mean: gives the mean value of the set of simulations on each cell or block of the grid.
- Standard Deviation / Variance: gives the standard deviation / variance of the set of simulations on each cell or block of the grid.
- Coefficient of variation: corresponds to the ratio of the standard deviation to the mean.
- Minimum: gives the minimal envelope of the set of simulations on each cell or block of the grid (that means that, for each node of the grid, the program selects the simulation which is the smallest one. It could be different from one node to another).
- Maximum: gives the maximal envelope of the set of simulations on each cell or block of the grid (that means that, for each node of the grid, the program selects the simulation which is the biggest one. It could be different from one node to another).
- Quantiles: enables the calculation of different quantiles for each cell or block of the grid. For a given quantile p, the quantile map displays the value for which there is p% of chance (i.e. p% of the simulations) that the real value z is smaller than this value. In this application, a quantile is always one of the simulation values of the macro variable.
  
  Click Edit to pop up the Value Definition window and customize the list of quantiles.
Cutoffs: Under this tab, you will find results associated with threshold(s).
- The two following options only appear if we consider several variables (with a multivariate geostatistical set or selecting several sets of simulations):
  - Thresholds on main variable: Select this option if you want to apply threshold(s) to one of your simulated variables only. Other variables will not consider threshold(s).
  - Thresholds per variable: Select this option if you want to apply different threshold(s) to each simulated variable.
  When defining several thresholds, the two following options appear:
  - Above a threshold: Select this option if you want to consider simulated values greater or equal to a defined threshold.
  - Between two thresholds: Select this option if you want to consider simulated values within an interval defined by two thresholds, i.e. values greater or equal to the lowest threshold and strictly lower to the greatest threshold.
  Click Edit to pop up the Value Definition window and customize the list of thresholds.
- Mean grade: for each node of the grid, the program computes the average value of the simulated values greater than or equal to the defined threshold or within the two defined thresholds.
- Accumulation: for each node of the grid, the program calculates the sum of the simulated values which are greater than or equal to the defined threshold or within the two defined thresholds, multiplied by the area or the volume of the cell. This sum is then divided by the total number of simulations.
  
  In 3D, a Density factor is also applied to compute masses. The density can be a constant value or defined by a variable. In this last case, the selected variable should be associated with a Mass density unit class.
  
  In 2D, a Thickness factor is also required. The thickness can be a constant value or defined by a variable. In this last case, the selected variable should be associated with a Length unit class.
  
  Depending on the type of the variable, the result can be homogeneous to a tonnage for a grade, or a volume for a thickness in 2D for example.
- Tonnage: corresponds to the rock quantity (in weight) where the simulated value of the variable is greater or equal to the cutoff value (or within the interval in the case we consider two thresholds).
- Benefit: corresponds to the difference between the metal quantity you should obtain with the calculated grade and the metal you would have obtained if the blocks had the exact cutoff value, so a value lower than the grade value.
- Probability: for each node of the grid, the program computes the number of simulations whose the value is greater than or equal to the defined threshold or within the two defined thresholds. When normalizing this value to the total number of simulations, this gives a probability (between 0 and 1) for the node to exceed the defined threshold.
Uncertainty:
- Confidence interval width: the confidence interval map represents the width of the interval which contains the real value at a given confidence level. For each node of the grid, simulated values are sorted in increasing order to compute quantiles (a quantile is always one of the simulation values of the macro variable). The p% confidence interval is based on the computation of two symmetric quantiles:
  
  Click Edit to pop up the Value Definition window and customize the list of confidence intervals.
- Relative-to-mean estimation error: corresponds to the ratio of the confidence interval width to the mean multiplied by two:
- Relative-to-median estimation error: corresponds to the ratio of the confidence interval width to the median
- Tolerance width: combined with the probability within tolerance variable, this result is used for the Parker's classification.
  
  Click Edit to pop up the Value Definition window and customize the list of tolerances. By default, the tolerance is set to 15%.
- Probability within tolerance: for each node of the grid, the program computes the number of simulations whose value lies in the interval defined by the mean value more or less the tolerance. When normalizing this value to the total number of simulations, this gives a probability (between 0 and 1).

Note: When one or more realizations of the macro variable are not defined on a node, this node will not be taken into account in the calculations. Statistics are calculated on the same number of nodes for all the realizations.

As some results are saved in macro variables, these ones can be overwritten if they already exist by checking the Overwrite macro option. Otherwise, results will be appended (i.e. new indices will be added in the existing macro variable).
At the end of the run, statistics on the output variables are printed in the Messages window. You can click on the Store chart file button to save the statistics table in a Chart File.