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.

Lithology Model in RockPlot3D

This presents a challenge, then, for users who wish to view lithologic SURFACES as plan-view contour maps, or in 3D, or exported to CAD.

In RockPlot3D you can access the lithology model’s Options window and filter the display for the desired material type, or range of types. Here is the above model filtered to display the Soil voxels only.

Lithology Model Filtered for Soil Only

This can be exported to DXF, but note that you’ll be getting all of the blocks representing that material. (Shown here in black and white for contrast purposes.)

Lithology Model Soil Voxels Exported to DXF

If you need a surface rather than blocks, RockWorks also has tools which will fit a surface to the uppermost elevations or the lowermost elevations of a rock type in a lithology model. These are in the Lithology | Superface (Top) and Subface (Base) menus. Here is an example of the same soil lithotype extracted as a surface (upper elevations), and displayed in RockPlot3D and then exported to DXF.

Surface Representing Top of Soil, Displayed in RockPlot3D

DXF Surface Representing Top of Soil

If you are trying to create a lithology model composed of horizontal beds that have been eroded and then overlain by a layer of soil, fill or even material such as concrete, you’ll often find that the horizontal lithoblending algorithm incorrectly places this upper layer of material below the sediments in some places.

One solution is to use some newer tools in the Lithology menu to create two separate Lithology models that can then be combined.  Here is an explanation of how this works.

Let’s start with the “Soil” layer at the top of the model.  First, it is important to assign a G-value to the Soil Lithology Type that is lower or higher than all the other material types.  In this case, the Soil material has been assigned a G-Value of 2.  All of the other material types have been assigned values between 3 and 8.

In the Lithology modeling tree menu, choose to create a model titled “Lithology Warped”.  Warp the model based on a grid that represents ground surface elevations, and turned off the “Randomize Blending” option to avoid interfingering of the soil and sand below.

While the representation of the sediments is probably not reasonable, I think that the soil layer at the top of the model looks much better in the diagram below than it does in the diagram above.

Next, create a model of just the flat lying sediments (in this example, the model is called “Lithology Sediments.mod”).  When creating this model, turn the Randomize Blending option back on, the warping option OFF, and tell the program to limit the model to just materials with G-Values between 3 and 8.

 As you can see in the diagram below, RockWorks has included everything except for Soil in this model.

Finally, use the Solid à Filter à Replacement Filter tool in the RockWorks Utilities, to insert the Soil in the warped model into the sediments model.

The diagram below displays this final model in a cross-section.

February 5+ Earthquakes: http://www.rockware.com/assets/products/165/downloads/data/37/usgsworldquakes5+feb2012.zip
March 5+ Earthquakes: http://www.rockware.com/assets/products/165/downloads/data/38/usgsworldquakes5+mar2012.zip
April 5+ Earthquakes: http://www.rockware.com/assets/products/165/downloads/data/40/usgsworldquakes5+apr2012.zip

Google Earth (TM) display of earthquakes worldwide, April 2012, from RockWorks15

Once you load the KMZ file into Google Earth, more information is available about each quake by clicking on the symbols.

First, let’s take a look at a contour map created using the EZ-Map tool in the RockWorks Utilities.

The EZ-Map tool uses simple triangulation to create contours.  For some data sets, this may be all you need to create a reasonable looking map.  However, it will often be necessary to create grid-based maps with smoother contour lines that extend to the edge of the project.  Note the increase in the groundwater elevation on the eastern edge of the map.  This is something that can be resolved by switching to a grid-based map.  We’ll explore grid-based mapping tools next.

Here is a map created using the default Inverse Distance Weighting settings.  I should note that I had both the “Smoothing” and “High-Fidelity” options turned on during grid creation.

The “bull’s eyes” that you see around the high and low points in the map are typical of the Inverse Distance interpolation method.  One way to resolve this is to decrease the number of points used during interpolation.

To do this, change the Number of Points used for the Inverse Distance Algorithm from 8 (the default setting) to 4 (which is more appropriate for a data set of this size).

Here is a map created with the modified “Number of Points” value:

The bull’s eye effect has been muted somewhat, but notice that the contours don’t honor the data extremely well.  Let’s move on to Kriging.

In the map below, I let the RockWorks program choose the appropriate variogram settings.  With Kriging especially, which can create fairly blocky models, I highly recommend that you turn on both the grid “Smoothing” and “High-Fidelity” options when
creating a contour map. 

This may be a little bit more to your liking, but the general groundwater flow direction could still be better represented along the borders of the map.  Just to cover all of our
bases, here is another map created using Triangulation gridding.  Unfortunately, there are some problems with edge effects in the resulting map as well.

None of these are really doing it for me.  At this point, I think that a lot of people would probably resort to hand drawing their contour maps, or adding additional control points to the data set to force the contours into the shape they have in mind.  Before you resort to these tedious and time-consuming options, I would recommend you look at the Densify and Polyenhancement options available in RockWorks15.

Here is a diagram showing the contour maps created with the Inverse Distance interpolation algorithm, with and without Densify turned on.  As you can see, the densification process (which adds additional control points to the data set before
interpolation using triangulation) straightens out the contour lines quite a bit.

I did the same test using the Kriging algorithm and got the following results.

Last but not least, here is a contour map created with the Polyenhancement option turned on.  When this option is activated, the program fits the data to a polynomial surface and then warps that surface to honor the data points (in this case, I choose a 2nd order polynomial surface).  I think I have my map!

In real life, I’ve found first, second and third order polynomials useful when creating groundwater contour maps.  If the groundwater flow direction is fairly constant through the area, go with a 1^st order polynomial (which is a planar surface).  If it is variable because of topography or a feature such as a river or stream, then a 2^nd or 3^rd order polynomial is the way to go.

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.

http://www.rockware.com/assets/products/165/downloads/data/36/usgsworldquakes5+jan2012.zip

http://www.rockware.com/assets/products/165/downloads/data/35/usgsworldquakes5+dec2011.zip

Google Earth (TM) display of earthquakes worldwide, Dec 2011

Once you load the KMZ file into Google Earth, more information about each quake is available by clicking on the symbols.