Tipos de modelos de bloques

Lectura estimada: 3 minutos 49 puntos de vista

The most common block model types used to define and manage the spatial distribution of geological and economic data are Regular, Percent, Subblocked, Reblocked, y GSM (Gridded Seam Model). Below is a brief overview and comparison of each type.

MiningMath block model types

MiningMath fully supports regular block models and offers practical workarounds and formatting guidelines for handling por ciento y reblocked models. Sin embargo, subblocked and GSM models are not currently supported.

Block model types

Regular Block Model: The deposit is divided into uniform blocks of fixed size in three dimensions (X, Y, Z).
This is the type natively supported by MiningMath. Formatting instructions can be seen aquí. Rotation of regular block models is also supported as described aquí.
Percent Block Model: Extends the regular model by incorporating percentage values to represent how much of a block contains a specific material or belongs to a given domain.
This is not natively supported. Sin embargo, instructions on how to format this model with and without dilution are provided aquí.
Subblocked Block Model: Refines regular blocks by dividing them into smaller sub-blocks where needed, typically along geological boundaries or to represent irregular shapes more precisely. It can give a higher detailed representation of geological features, but can also lead to large file sizes, higher computational demands, and higher complexity to prepare and manage.
This is no supported by MiningMath.
Reblocked Block Model: It is created by merging smaller blocks (often from a subblocked model) into larger ones to simplify calculations or meet specific optimization constraints.
MiningMath proporciona una aplicación en su Laboratorios MM sección que puede volver a bloquear su modelo de bloque. Further instructions can be seen aquí.
GSM (Gridded Seam Model): This is used for stratified deposits, like coal or other layered materials. It divides the deposit into horizontal layers (seams) and models variations within each layer. Sin embargo, it is less flexible for deposits with significant vertical or irregular variations.
This is no supported by MiningMath.

Comparison and use cases

These models offer flexibility in balancing accuracy in deposit representation with complexity in computational effort required for optimization.

The table below highlights the trade-offs between accuracy and complexity, using the regular block model as a reference point. It also summaries the block model types supported by MiningMath.

Model type	Best for	Complejidad (lower is better)	Accuracy (higher is better)	Apoyo
Regular	Deposits with uniform geometry	Standard	Standard
Percent	Deposits with irregular ore/waste distribution	Higher	Higher	Partial
Reblocked	Simplified optimization or large-scale production planning	Lower	Lower	Partial
Subblocked	Detailed geological models with sharp boundaries	Higher	Higher
GSM	Layered, stratified deposits with predictable structures	Higher	Higher (for stratified deposits)

MiningMath

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Tipos de modelos de bloques

MiningMath block model types

Block model types

Comparison and use cases

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