Webinar: Block Model Types in Geology

Block models are the foundation of modern resource estimation and mine planning. They are built during geological modeling and resource estimation and then serve as input data for optimization, mine design, drill and blast planning, and both short- and long-term scheduling. This webinar walks through the block model types available in K-MINE, explains how each one handles different deposit geometries, and sets out selection criteria for stratiform deposits, structurally complex vein systems, narrow orebody modeling, and open-pit versus underground scenarios. It closes with a brief comparison against other geology software packages.

In most cases, a block model consists of tightly packed orthogonal cells — cubes or rectangular blocks. Over the past fifteen years, and especially for stratiform deposits, there has been wider adoption of models with truncated prism cells, known as HARP models, as well as grid-based models.

Most block models contain a set of attributes whose values can vary in each block or sub-block. These attributes are used for interpolation and other calculations when estimating the quantity and quality of minerals, as well as the overall economic viability of a project. Each block typically has centre coordinates and represents a specific volume in space. In some software, in addition to the XYZ coordinates of the block centroid, there is also information about the block's position relative to neighbouring blocks, often stored as a three-digit code. The attribute values are assigned to the block centroid and are assumed to apply to the entire volume of that block.

Different geology software offers several types of block models to choose from. In this context, K-MINE is one of the more flexible geological information system products — it allows you to create nearly all types of block models used in geology, planning, and design.

K-MINE supports the following block model types: regular block models, sub-block models, percent (volume / partial) block models, and HARP (stratigraphic / seam) and irregular block models. The sections below walk through each type, the selection criteria for stratiform deposits, structurally complex vein systems, and narrow orebodies, the differences between open-pit and underground scenarios, and a short overview of commonly used software such as Leapfrog, Surpac, Datamine, and Micromine.

The regular block model is the simplest and the most limited in functionality. It is a set of blocks of the same size within defined boundaries. Each model has a start point and overall dimensions along each axis. The start point always has the minimum coordinate values on all three axes. In most cases, this is the corner of the block located on the lower-left part of the model. In some software, the start point can also be defined as the centroid of the block with the minimum coordinate values; in that case you need to subtract half the block size along all three axes from the centroid coordinates. This detail matters when importing or exporting block models between different software packages. In K-MINE, the start point is always on the block corner with the minimum coordinate values.

In K-MINE, you can create a regular block model in two ways. You can create an octree model with a minimum block size that is divisible by the model dimensions along each axis, or you can create a sub-block model with a fixed parent block size and no sub-blocking. In the first case, you can later sub-block the model to a smaller size if needed.

For example, we create an octree model with dimensions X = 80 m, Y = 160 m, Z = 40 m and a minimum block size of 5 × 5 × 5 m. We then add a couple of attributes to assign values to the blocks — integer type for categories and rock codes, and double type for grade values and physical-mechanical properties. With the block edge visibility adjusted, you can see that all parent blocks have been created at 40 × 40 × 40 m. These are consistent with the block model dimensions (80 × 160 × 40) and the minimum block size of 5 × 5 × 5, which is essential for an octree model.

Later, you can sub-block this model into smaller but still regular cells — for example, 20 × 20 × 20 or 10 × 10 × 10. If you need to sub-block along the boundary of a solid, the model converts from regular to sub-blocked: at the contact with the solid, blocks are created at the minimum size while the remaining blocks keep their original size. In this case, along the boundary of the green solid, 5 × 5 × 5 blocks are generated. You can filter only the blocks whose centroids fall within the solid and assign them a rock code of one and a red colour. The 5 × 5 × 5 blocks were defined as the minimum size when the model was created, so it is important to plan ahead and define the minimum block size based on project needs. If something is missed — for example, you need to increase the block size later — the model can easily be rebuilt at any stage. You define a new minimum block size and recalculate all block properties using a weighted-average formula.

In the second case — creating a sub-blocked model with a fixed parent block size — you can choose the option without sub-blocking. The main advantage of the regular model is simplicity and compatibility with optimization and mine planning, including the Lerchs-Grossmann algorithm. The main drawback is limited representation of geological context, particularly in complex deposits or where orebodies are thin.

Creating a model with sub-blocking allows the geometry of the geological model to be represented in more detail by dividing parent blocks into sub-blocks. This approach makes it possible to account more accurately for model constraints using wireframe surfaces — topography, mined-out surfaces in an open pit, domain solids, and their boundaries. As a result, sub-blocking delivers better geometric detail and improves the accuracy of volume and tonnage calculations. The main drawbacks are significantly larger file size and more complex data processing.

Octree block models are a well-established sub-block type where parent blocks are divided into fractions such as 1/2, 1/4, 1/8, and so on. Sub-blocking can be applied within a solid or across the entire model down to the required block size. This means different areas of the model can have different sub-block sizes. However, sub-blocking is only possible down to the minimum block size defined at model creation.

Today the most common approach is a model with variable sub-blocking along an axis. Here you can create a model not only within defined boundaries as a parallelepiped but also within selected solids. For example, in vein deposits you can use implicit modeling to generate vein solids and then create a sub-blocked model within those solids — the list of selected solids is loaded automatically. You can also limit the model using open surfaces such as topography. When creating a model with variable sub-blocking, you can define a dominant axis. Along that axis the number of sub-blocks is not fixed and can vary, while along the two other axes the number of sub-blocks within a parent block is fixed.

In a worked example, within four vein solids, three block models are created with the dominant axis set along X, Y, and Z. For each model, a section is generated to compare how the choice of dominant axis affects the sub-block configuration.

Modelling with sub-blocking is a three-dimensional approach that uses small sub-blocks along geological contacts and larger parent blocks elsewhere, allowing accurate representation of narrow and complex veins while maintaining computational efficiency. This approach prevents excessive smoothing of characteristics, reduces volume errors, and can decrease the total number of blocks by up to 75% compared with standard sub-blocking — especially in narrow vein systems.

Modern software uses implicit modeling to automatically classify drill-hole data into hanging-wall and foot-wall points for building three-dimensional vein models. Geologists then need to fit block models properly within the boundaries of these vein shells. In software without variable sub-blocks, parent blocks are often divided into very small sub-blocks, which can be inefficient in processing time and data handling. Variable sub-blocking also allows more accurate volume definition in thin veins and improves grade estimation by reducing ore loss and dilution from surrounding waste.

The choice of dominant axis affects not only the sub-block configuration within the model but also the shape of the vein bodies and therefore the total volume of material. Sub-blocking expands the ability to represent the shape of orebodies accurately. In the past, deposit models were often built with a block size that was not appropriate for thin orebodies — only some block centroids fell inside the solid, and gaps between blocks were later treated incorrectly as waste material. By selecting an optimal block size, or using variable sub-blocking, this issue is effectively resolved.

For models with variable sub-blocking, transformation tools are also expanded, including reblocking, regularization, splitting, resizing, and merging. Reblocking lets you change the size of parent blocks while the sub-block grid remains unchanged. Regularization rebuilds a new model with a new parent block grid at a defined block size; the sub-block grid of the original model is not taken into account. Splitting a model by wireframe surfaces into separate block models, or merging blocks with identical attribute values into larger blocks, significantly simplifies the modeling process and reduces the time required for further operations.

All the block model types discussed so far share one feature: they are created empty, without assigned rock or domain codes. Populating the model with lithological context or other domain information is only possible using solids and wireframe surfaces as constraints.

The stratigraphic model — also known as the seam model or HARP model — was developed by K-MINE to provide a more efficient way to work with stratiform deposits. It differs from the regular model in that the block height along the Z-axis is variable while block size along the X and Y axes is fixed. This model does not support sub-blocking. The shape of each block is a truncated prism with four points at the base perimeter and one point in the centre. In total, each block has ten vertices and a centre — an eleven-point block that represents seam morphology with a high degree of accuracy.

The first step in modeling is to create a complete stratigraphic column based on the available geological database. It is important to define the chronological sequence of seams and inter-layer waste and, if necessary, assign indexing to individual seam splits. The block model is then created automatically from drill-hole data and pulls lithology or other domain information from the database during creation. You only need to define the sequence of seams and create a surface for one of them as a marker seam. From the wireframe surface of the seam floor, the thickness of all other seams is calculated upward and downward along the section. The key feature of this model is that all blocks have variable size along the Z-axis; the height of each block depends on the interpolated thickness of the seam from nearby drill holes, allowing the model to represent seam geometry in space accurately.

For simple deposits, the model can be built in a few seconds. In practice, deposits often have more complex structures. Consider a case with two fault systems. These fault surfaces divide the deposit into three tectonic blocks — below, above, and between the faults. Within these blocks, the position of the marker seam and seam thickness can vary significantly, and there is often displacement of seams along the fault surfaces. If the model is built across the entire deposit without limiting it by these blocks, the result can be incorrect.

The workaround is to divide the overall solid using fault surfaces into three separate solids — block one, block two, and block three — and use them as constraints for building the model. In the example, seam 11 is initially selected as the marker. If the marker is defined incorrectly or the wireframe surface does not match the selected seam, the software displays a warning. A new marker surface is then rebuilt for each of the three blocks. For block one, only the drill holes within that block are used, and the floor surface of the marker seam is created. The floor surface for seam 12 is created and saved as layer M1. Similarly, marker surfaces M2 and M3 are created for blocks two and three — in block two the marker is seam 52, and in block three it is seam 11. With markers in place, the stratigraphic (seam) block model is built.

Within block one, the seam structure and dip angle differ significantly from blocks two and three. Significant displacement in seam position and thickness can be observed at the fault contacts. To analyse the seam structure in a specific plane, a section through the model can be selected, and the visualization mode can be switched to edges. Attributes of individual blocks can then be analysed or modified. This model does not support further sub-blocking.

In the stratigraphic model, variable block height along the Z-axis and the truncated-prism shape bring the representation of seams close to the natural smooth geometry of geological contacts. Each seam can be visualized separately and its volume calculated. You can also create a percent block model using lithological codes from the database. The main difference is block shape: in the percent block model, blocks have a fixed size along the Z-axis. If a block contains several lithological varieties with thickness smaller than the block height, their volume can be estimated using a percentage ratio. However, you cannot accurately represent each lithological unit as in the stratigraphic model, and you cannot define the contact between ore and waste within a single block.

In the example, blocks shown in purple contain coal layers while all other blocks representing waste are shown in red. Individual seams cannot be visualized in this model. Nonetheless, this type of model is important for mine optimization and planning — the Lerchs-Grossmann algorithm used in optimization and planning works with blocks of uniform size. Here, the volume and tonnage of ore and waste in each block are calculated based on percentage distribution and total block volume. The main drawback is the inability to visualize orebodies and their contact with waste.

When choosing a block model type for open-pit or underground projects, the decision depends largely on the final objective. If the planning software is already defined, the model type — regular, sub-blocked, or stratigraphic — is selected based on its algorithms and requirements.

To summarise, the most common block models in geology — and sub-block models in particular — are clearly the leaders, thanks to their flexibility and functionality. This applies to stratiform deposits, structurally complex vein systems, and narrow orebody modeling. Modeling of domain shells for coding blocks and sub-blocks is most commonly performed using implicit modeling. Vein modeling functionality available in many software solutions also simplifies the process considerably. If you are working with coal deposits or other stratiform bodies with folded structure, and you have a sufficiently reliable drilling network along with mapping of folding and fault tectonics, you can readily create a HARP-type seam model.

K-MINE provides a wide range of block model types and addresses one of the most complex tasks in the industry — covering the full cycle from geological modeling to mine planning and design. Each software package has its own strengths and limitations. When selecting a solution, reaching out to the K-MINE team for advice on the right set of models for a specific project is the fastest way to arrive at the right setup.