I’ll describe here an easy way to pop one profile onto another – in this example overlaying a benzene profile on top of a stratigraphy profile.

1. Create your two profile diagrams using the same annotation settings and the same profile slice.  This assures that the profile panels will have the same coordinate range.  I find it helpful to arrange the two profile windows on my screen, one above the other, so that they are both accessible.

Arrange both profiles on your screen so they're both visible.

2. With the RockPlot Edit Arrow tool activated, click on the I-Data profile contours to select them. (Note the red selection handles in the panel corners in the upper image.) Type Ctrl+C to copy this layer into memory.

Click on the I-Data profile color contours to select that layer, and copy it to the clipboard.

3. Click in the Stratigraphy profile window and type Ctrl+V to paste the I-Data profile into this diagram.

Paste the I-Data panel onto the Stratigraphy profile

4. Double-click on the I-Data layer you just pasted into the combined diagram to adjust the minimum contour level and transparency, so that the stratigraphic layers will be visible in the background.

Adjust the minimum contour level and/or transparency.

5. Click OK to close the Colorfill Attributes window.

Now you can see the stratigraphic profile in the background.

6. If you like, you can copy /paste the I-Data color legend in to the combined diagram.  Use your mouse to resize/rearrange the legends as desired.

Combined Stratigraphy and Benzene Profiles

1. Create your contour map in RockWorks without faulting turned on.

• Use the Utilities Map | Grid-Based Map if your XYZ data is entered into the Utilities datasheet.
• Use any of the Borehole Manager contour mapping options (Map | Borehole Locations for ground surface contours, Stratigraphy | Structural Elevations for stratigraphic structure maps, etc.) if your data is entered into the borehole database.

2. In the displayed map, use the Draw | Line Types | Polyline to draw a fault polyline on your map.  Double-click to terminate the polyline.  You can repeat this if you have multiple faults.

Unfaulted contour map with drawn polyline

3. Choose the arrow-shaped Edit tool from the RockPlot2D toolbar, and click on the polyline you drew, to select it.  (If selected, you’ll see square icons on the vertices.)  If you have multiple polylines drawn, hold down the Shift key on your keyboard to click on the next polyline to select it as well.  Continue in this manner for as many polylines as you drew so that all are selected.

4. Right-click on any of the selected polylines in the map window and choose Save to Faults Table.

Save Fault Polyline to a "Faults Table"

Enter a name to assign to the Faults Table and click OK.  This will be saved to the project database.

5. Return to the options along the left side of the map window, and click on the Gridding Options button.  Here, turn on the Faulting option (which is available under Inverse-Distance).  Enter the “distance multiplier” (usually 10) and browse for the name of the Fault Table that you just created.

Gridding Options - Faulting settings

Click OK to close this window. Click on the Grid Name prompt and enter a new name for the faulted grid model (such as “Potosi_faulted.grd”).

6. Click Process to recreate the grid model and map, now applying faulting.

Faulted Contour Map

Here are three-dimensional views of these surfaces:

Unfaulted Surface in 3D

Faulted Surface in 3D

RockWorks applies faulting by creating an interpolation barrier on either side of the polyline(s) – as it’s interpolating a grid node, any control points on the other side of the fault are now considered to be 10 times further away than they actually are, thus having no influence on that node.

Link to original paper: http://www.rockware.com/assets/products/165/casestudies/6/9/computing_aggregate_reserves.pdf

 Introduction

 The purpose of this study is to compute the total economic reserves for a site that includes two carbonate units; an upper limestone and a lower dolomite separated by a shale unit. Quality analyses have been obtained at one-foot intervals within the carbonates. The following diagram depicts a typical log showing the lithology, stratigraphy, and aggregate quality.

Figure 1: Typical log depicting aggregate quality (bargraph on left), stratigraphy (patterns in center), and lithology (subdivisions within stratigraphy)

Step 1. The Problem

Modeling the rock quality en-masse is problematic because the node values would include the quality values for both the limestone and the dolomite. The following diagrams depict a solid model based on the rock quality and a stratigraphic block model. Notice how the rock quality (I-Data) model interpolates quality values where there is no corresponding carbonate.

 Compare this stratigraphic model with bulk rock quality model above and note how quality values were interpreted within overburden (light yellow) and interburden.

Step 2. The Solution

The solution to this problem is to use the “Stratabound” option within the I-Data / Model menu. Two rock-quality models were created; one for the upper limestone and another for the lower dolomite.

In the example below, the I-data model is confined to points and nodes within the Hanford Limestone unit.

Figure4: Hanford Limestone Rock-quality Model

 In this example, the I-Data model is confined to points and nodes within Shuller Dolomite.

Figure5: Shuller Dolomite Rock Quality Model

Step 3. Combining the Models

The next step involved adding the two models together and removing all voxels with a quality value less than 50 (the minimum acceptable quality).

Figure6: Fence diagram depicting combined rock-quality models for upper limestone and lower dolomite.

Figure 7: Block Model depicting voxels with a quality value greater than 50.

Figure 8: Block model depicting zones from previous model in which the thickness for any single contiguous ore zone is more than 6 feet thick for any given column.

Figure 10: Block model depicting zones from previous model in which the stripping ratio is less than 1.2. This area represents a good place to start mining in order to gain the highest return on investment.

 Step 4. Checking the Model

The final, and most important step, is to create a 3D log diagram, combine it with the final ore model, and examine the data to see if it make sense.

Figure 11: 3-Dimensional Lithology/Quality Logs Combined With Final Ore Model.

Figure 12: Enlargement of area around highest-ROI ore depicting lithology and quality logs.

Step 5. Conclusion

By combining the preceding approach with increasingly more tolerant filter cutoffs, it is possible to create a mining strategy that will yield the highest return on investment from the onset.

Cell Area .............................. 100.0
Map Area (X*Y) ......................... 738,000.0
Grid Area (Sum(Cell Area)).............. 755,300.0
Model Volume (Sum(Cell Area*Z)) ........ 5,493,616.411554  *
Non-Zero node area ..................... 119,600.0