Documentation

Data Tables

Data tables hold the interval data you log against each drillhole — lithology, alteration, mineralization, assays, geotechnical, samples, and anything else. You define the tables once at the project level; every drillhole then has those tables available in its sidebar, ready to log into.

A typical exploration project might have:

  • Lithology — rock type, texture, colour, structure per interval
  • Mineralization — ore minerals, sulphide percentages, style
  • Assay Results — sample IDs, grade values, recovery
  • Alteration — alteration type and intensity
  • Geotechnical — RQD, core loss, fracture count
  • Samples — sample dispatch information

You can have as many or as few as your program needs.

Open the data tables editor

From the Dashboard, settings gear (⚙) → Templates. Click the Data Tables tab. Each table you’ve created appears as a tab at the top of this panel.

Create a table

Click + Create Table. Give it a name (e.g., Lithology, Assays) and confirm. The new table appears as a tab and is empty until you add columns.

Add columns

With a table tab selected, click + Add Column. Each column has:

  • Name — the column identifier (e.g., depth_from, rock_type, au_g_t)
  • Type — see Column Types
  • Depth From / Depth To markers — see below
  • Required — must be filled before a row saves
  • Default Value — pre-fill new rows. Can be a literal value or @PREV(column_name) to copy from the previous row
  • Dropdown options — for dropdown columns, the list of allowed values
  • Validation Rules — see Validation Rules
  • Formula — for formula columns, the mathjs expression. See Formula Columns

Drag the ⠿ handle to reorder columns. Click 🗑 to delete a column (the data in that column is lost).

Depth From / Depth To markers

Every table that represents interval data should mark one numeric column as Depth From and another as Depth To. To do this, open the column card and toggle the Depth From or Depth To switch.

Marking depth columns has three effects:

  1. Pinned to the left. Depth From and Depth To always appear as the leftmost two columns in the spreadsheet, no matter their order in the template.
  2. Validation. The depth-interval rule (which catches reversed intervals like From > To and overlapping rows) uses these markers.
  3. Visualisation. The Strip Log and the 3D Viewer both rely on depth markers to know how to map your data to depth.

A table can have one pair of depth markers — one Depth From column and one Depth To column. If your table doesn’t have intervals (e.g., a samples summary table), leave the markers off.

Default values and @PREV

Default values pre-fill new rows so you don’t retype the same value over and over. Two flavours:

  • Literal — any constant. e.g., default unit to m or quality to Good.
  • @PREV(column_name) — copy the value from the same column in the previous row. Useful for fields that change rarely, like a logger’s name across consecutive rows or a continuing rock unit. Example: set @PREV(rock_type) as the default for rock_type so each new lithology row starts as the same unit until you change it.

Lithology source — boundary validation

If you log alteration, mineralization, or any other interval table that should “respect” lithology boundaries, you can have Blue Butterfly warn you when an interval crosses a lithology contact.

In the Lithology source dropdown at the top of a table’s column list, select your lithology table. Any row whose interval crosses a boundary in that table will be flagged with a yellow warning. Warnings don’t block saving — they just surface a potential issue for review.

Reorder and delete tables

Tables appear as tabs at the top of the Data Tables editor. To rename, double-click the tab name. To delete, click the 🗑 button on the active tab. Deleting a table removes it from every drillhole — all records in it are lost.

What’s next

Once your tables and columns are defined, head to a drillhole and start logging — see Enter Interval Data. If you want to lock down data quality at entry time, set up Validation Rules on the columns that matter.