The values exported are the midpoints of each segment, the X-Y-Z values and the hole ID. The Snowden Supervisor and Isatis 3D points formats also include the interval length.

Scatter plots are useful for understanding relationships between two variables. An additional variable can be introduced by setting the Colouring option to a data column. The example below plots the two variables lead and zinc against each other, with gold being indicated by the colouring. You can make either axis a log scale with the Log scale in X and Log scale in Y options. A Query filter may also be applied. With the drillhole correlation tool, you can view and compare selected drillholes in a 2D view. You can then create interpretation tables in which you can assign and adjust intervals and create new intervals. Interpretation tables are like any other interval table in a project and can be used to create models. The rest of this topic discusses options for displaying drillholes and viewing statistics on drillhole data tables. It is divided into:

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When numeric data is displayed, there is an additional option, to use a data column in the table for the cylinder radius: You can filter the data using any Query filter defined for the data table. Statistics for interval tables can be unweighted or weighted by interval length. In addition to the imported drillhole tables, the Drillholes object also has two objects that help in visualising and analysing drillhole data. These are: Text columns containing text data that is not categorical, such as comments. Text columns are not validated when imported.

Append the dataset, as described in Adding New Rows to Existing Data Tables in the Working With Data Tables topic. Depth markers can be displayed with or without text. Enable the Show text option ( ( )) to display the depth values. This option also displays the hole ID, which can be displayed at the start or the end of the drillhole. Displaying Drillhole GraphsThe Interval Length Statistics graph is a univariate graph, so for more information on the options available, see Univariate Graphs in the Analysing Data topic. Once points data has been imported to the project, it can be modified and evaluated against geological models, numeric models and estimators, as described in Evaluating Points Data. Selecting the ODBC Data Source

Once you have set up a table of statistics on a particular table, its settings will be saved so you can easily review the statistics and export the table using the same settings. Downhole numeric data can be displayed in the scene as a bar graph and downhole points data can be displayed as a line graph. To display downhole data in this way, add the Drillhole Graphs object ( ) to the scene. The Drillhole Graph Style Manager will be displayed, showing the data columns available: Having a clean and well-prepared data set is an important factor in building reliable models, and costly and time-consuming mistakes can often be avoided by putting in the upfront effort to preparing your data before embarking on building models. Plan Ahead Visualising data using the shape list and the shape properties panel is an important part of interpreting and refining data and making modelling decisions. The tools available depend on the type of object being displayed, and many objects can be displayed evaluated on other objects.If there are negative values in the data, they will be displayed on the graph with a value of zero. Import the features as separate objects. Each feature will appear in the project tree as a separate object. In this example, we have the initial table of statistics for a merged table that has two category columns and four numeric columns, plus an Interval Length column. However, nothing is displayed in the table because data columns have not yet been selected.