This paper describes how to use RockWorks to compute total economic reserves for a site that includes two carbonate units: an upper limestone and a lower dolomite, separated by a shale unit. It involves creating separate I-Data models using the Stratabound filter, combining the models, and checking them against the observed log data.
Link to original paper: http://www.rockware.com/assets/products/165/casestudies/6/9/computing_aggregate_reserves.pdf
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.
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.
In this example, the I-Data model is confined to points and nodes within Shuller Dolomite.
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).
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.
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.