Back-Flagging Drilling Data

Evaluating geological models on wells creates a new lithology table containing the lithologies from the selected model. This is useful for validating models created from drilling data as you can generate statistics for the correlation between modelled geology and drilling data.

To created a back-flagged drilling data table, right-click on a drilling dataset in the project tree and select New Evaluation Table. The New Evaluation Table window will appear:

The New Evaluation Table window, with the model set to GM, the Evaluation type greyed out, and the column and table names filled in

Select the model to use and enter names for the column and table.

When the selected model is a faulted model, the Evaluation Type setting determines whether the model’s output volumes, faulted output volumes or fault blocks are evaluated.

Click OK to create the new table, which will appear in the project tree as part of the drilling dataset. The new table contains From, To and Lithology columns defined using the intersection between the model’s output volumes and the wells.

For output volume evaluations, you can view the correlation between modelled geology and actual logged well segments. To do this, right-click on the table and select Statistics. In the Correlation Statistics window, you can compare model values to drilled lithologies or vice versa.

See:

You can export the information displayed in the Correlation Statistics window in CSV format for use in other applications. To do this, click the Export button ().

Comparing Modelled Values to Drilling Lithologies

Comparing model values to drilling lithologies shows how accurately drilling lithologies are modelled in the selected geological model. High matching percentages for drilling lithologies in the left-hand side of the window mean the model closely matches the drilling data for that lithology:

The Correlation Statistics window with the Compare list set to 'model values to drilling lithologies', showing matching and non-matching lengths and percentages for each drilling lithology on the left and, for the selected lithology, the model values that make it up on the right

The right-hand side of the window shows the composition of the modelled values for the selected Drilling Lithology. Here, D1 in the geological model corresponds to D1 in the lithology data for 88.2% of the length of the well. D1 in the model is actually D2 for 2.37% of the length of the wells, and 9.44% of the drilled D1 values fall outside of the boundary of the geological model.

The Correlation Statistics window with the D1 drilling lithology selected and its 88.2% matching percentage highlighted, and the right-hand panel showing that the remainder is 9.44% outside the model and 2.37% modelled as D2

In the images that follow, we will look at the correlation between the D5 drilling lithology and modelled D5. Here, two drilling data tables are displayed with the D5-D4 contact surface from the geological model:

A close-up scene view of drillholes crossing the green D5-D4 contact surface, with an arrow marking a drillhole where the red D5 interval of the inner original-data trace extends past the surface while the outer back-flagged cylinder is green

The inner wells show the original drilling data. The outer wells show the geological model back-flagged onto the drilling data table. In the highlighted well, we can see there is a discrepancy between the actual lithology data and that modelled. When we view correlation statistics for this model, we can see that this discrepancy is explained by the fact that 17.97% of the D5 drilling length is modelled as D4:

The Correlation Statistics window with drilling lithology D5 selected, and an arrow linking its 17.97% non-matching percentage to the right-hand panel showing that portion is modelled as D4

You might consider this an acceptable match, but if it is too low, there are several ways to refine the geological model so that the geological model more closely reflects the original wells, which are discussed below. For this example, we will adjust the resolution of the geological model. The modelled segment now corresponds more closely to the original drilling data:

The same drillholes after the model resolution has been adjusted, showing the contact surface now following the drillhole so the modelled interval matches the original drilling data

Viewing the correlation statistics shows that 99.62% of modelled wells now match the original data:

The Correlation Statistics window after the model resolution has been adjusted, with the D5 matching percentage highlighted at 99.62% and only 0.38% modelled as D4

Comparing Drilling Lithologies to Modelled Values

Comparing drilling lithologies to model values shows the lithological composition of modelled values. Again, high matching percentages in the left-hand side of the window mean the model closely matches the drilling data for that modelled lithology:

The Correlation Statistics window with the Compare list set to 'drilling lithologies to model values', so the left-hand table lists modelled values and the right-hand panel breaks the selected modelled value down into the drilling lithologies that make it up

The non-matching percentage indicates how much of the modelled lithology is not the drilling lithology. You can see in the right-hand side of the window the lithologies that make up the non-matching portions of the modelled value.

In the images that follow, we will look at the correlation between the D5 drilling lithology and modelled D5 once again. The non-matching percentage is 4.8, and on the right-hand side of the window, we can see that this is exclusively drilling lithology I2:

The Correlation Statistics window with modelled value D5 selected, and an arrow linking its 4.8% non-matching percentage to the right-hand panel showing that portion is all drilling lithology I2

Adjusting the resolution of the geological model improves the matching percentage to the point where only 0.09 percent of the D5 modelled value is drilling lithology I2:

The Correlation Statistics window after the model resolution has been adjusted, with the D5 modelled value matching at 99.91% and only 0.09% made up of drilling lithology I2

Refining the Geological Model to Improve Correlation Statistics

If the matching percentages are too low for the lithologies of interest, there are several ways to refine the geological model so that the geological model more closely matches the wells:

Creating a Merged Table Including Assay and Geological Model Lithologies

Creating a back-flagged evaluation table will result in a new table like this:

A back-flagged evaluation table with id, holeid, from, to and modelled lithology columns, in which each drillhole is divided into a few long intervals, one per modelled lithology

To obtain a table that includes both assay and back-flagged geological model lithologies, create a merged table as described in Merging Drilling Data Tables. The result will be a merged table like this:

A merged table with id, holeid, from, to, Cu and modelled lithology columns, in which the short assay intervals have been split at the depths where the modelled lithology changes

Note that this merged table will split assay intervals where the geological model showed a transition from one lithology to another, as shown above at lines 1 and 2 , and also lines 6 and 7, and so on. Below, in scene A, a modelled vein cutting across wells is illustrated. The drillhole diameter is indicating the assay value and the colour is indicating the lithology. Thin orange lines have been over-draw to show the original assay intervals, while the thicker pink lines show new intervals created by the merging of the tables. An alternative that utilises the existing interval midpoints when allocating the geological modelling lithology as an additional column is illustrated in scene B. If this strategy is preferred, see Evaluated Column From Geological Model.

Two scene views of drillholes crossing a modelled vein: in scene A, magenta ticks mark the extra intervals a merged table creates at the lithology boundaries, alongside orange ticks marking the original assay intervals; in scene B, an evaluated column instead uses the existing interval midpoints, so only the orange original intervals remain