Rockworks

First developed in 1985 by RockWare Inc, RockWorks is used by the mining, petroleum, and environmental industry for subsurface visualization, borehole database management as well as the creation of grids, solid models, calculating volumetric analysis, etc. First developed in 1985 by RockWare Inc, RockWorks is used by the mining, petroleum, and environmental industry for subsurface visualization, borehole database management as well as the creation of grids, solid models, calculating volumetric analysis, etc. Computer modeling in RockWorks provides a means for tailoring a mine, environmental, petroleum, etc. plan based on the end-user specifications. The basic strategy involves the creation of a borehole database that includes analytical results for various physical and chemical properties as a function of depth. Once the database has been created, visualizations such as cross-sections, fence diagrams, and block diagrams are generated to check the validity and geological reasonability of the modeling. The next steps can involve the calculation of volumetrics and optimal pit-designs for example, in mining, based on a series of user-defined parameters. The foundation of these analyses involve the creation of imaginary block models in which a site is subdivided into a series of three-dimensional cells called a voxel (volumetric element). Values are estimated for these voxels based on their proximity relative to downhole data. For example, a clay deposit may involve the creation of separate models representing shrinkage, brightness, and slip. These models are then filtered and combined into a final model that shows where all of the parameters (models) meet a set of user-defined criteria. The net result is high-grade, or “surgical” mining in which the quarry is designed to maximize profitability rather than simply mining the entire lease and relying on the sorting/milling process to separate the ore and the non-ore. A healthy level of skepticism must be employed when using computer software to compute resource volumetrics. The algorithms or methods used to create the volumetric models have limitations that may be acceptable for one type of deposit while being completely inappropriate for another. For example, a sand and gravel deposit requires an approach that is completely different from the methods used to evaluate a phosphate reserve. The best way to avoid misuse is to always compare “slices” through the models with borehole logs that show the original data. These cross-sections are used to make sure that the model “honors” the data. Just as importantly, cross-sections should be evaluated to make sure that the modeling conforms to the expected geology. The raw dataset that are used for industrial mineral deposit modeling can be classified into two major types: borehole and non-borehole data. The management of borehole data is very different from non-borehole data. Specifically, borehole data requires a relational database management system (e.g. Access, FileMaker, SQL, Oracle,) whereas non-borehole data (with the exception of land ownership) can be handled with simple “flat” file managers (e.g. Microsoft Excel, Lotus 1-2-3). “Modeling” refers to the process of creating a spatial array of estimations. The parameter that is being estimated may be the thickness of the ore, the grade of the ore, or some other property that is useful for the evaluation of the resource. These arrays may be two or three-dimensional depending upon the number of independent variables. In a two-dimensional array (also referred to as a “grid model”), the dependent variable (z) is a function of the horizontal (x,y) coordinates. In a three-dimensional array (also referred to as a solid or block model), the dependent variable (g) is a function of the horizontal (x,y) and vertical coordinates (z). Grids are used to model topography, stratigraphic contacts, isopachs, and water levels, while solids are used to model geochemistry, ore grades, and geotechnical properties. The key difference between grid models and block models is that a gridded surface (e.g. a stratigraphic contact) cannot fold or wrap under itself whereas an isosurface within a block model can. Stated differently, when dealing with grids, there can only be one z-value for any given xy coordinate. On the other hand, when dealing with block models, there can only be one g-value for any given xyz coordinate. Another major difference is that gridding is computationally fast while block modeling can be very slow. Consider the evaluation of a clay deposit in which the only important parameter is the thickness of the clay (i.e. the clay grade is homogeneous or “anisotropic”). Variations in the clay thickness encountered within nine boreholes are depicted by Figure 1.