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How Votorantim used Leapfrog to model a complex nickel deposit

Company

Votorantim Metais (Brazilian multinational working with base metals)

Project

A lateritic, mafic-ultramafic nickel deposit located in Niquelandia, 300Km north of Brasilia, Brasil. The open pit mine produces nickel carbonate using a hybrid pyro-hydrometallurgical process. The deposit is 26 km (N-S) by 6 km (W-E) drilled at a 25×25 m space.

Data

Approximately 372,000 metres of drilled cores.

The problem

Until 2011, Voltorantim Metais used explicit modelling to construct and update geological models, taking approximately six months, depending on the modeller’s skill. Due to the excessive time spent generating and updating domains, not enough time was available for developing subsequent stages of mineral resource evaluation.

Geological challenges

  • Strong structural variation along ore bodies
  • Dips ranging from sub-horizontal to sub-vertical
  • Thickness variations from 1-120m
  • Very large dataset (372,000 of drilled core)

Business benefits

Despite learning a new geological modelling tool, it took only four months to complete work, compared to at least 5 months previously.

Benefits are even more remarkable considering time saved updating the model with approximately 15,000 metres of new drillholes, from three months to only three weeks with Leapfrog.

Further Advantages

  • Able to process very large datasets including drillhole, channel samples, geologic contact points, structural dataset and topography.
  • Flexibility to add points and control lines to better reproduce geology.
  • Ability to reproduce the model to avoid subjective bias. Assisting with due diligence and auditing. Using the same database and parameters, the same isosurfaces and geological domains are created.
  • Rapidly built and updated, able to evaluate more than one scenario.

The RBF function can be easily fitted by the user to make the model closely represent reality. Many different parametric settings were tested to fit the 3D interpolation for each and every lithotype (such as isotropic/anisotropic, capping values, nugget effect, resolution, directional bias, structural trends).

Assumptions

Lithotypes were grouped into six geological domains, by modelling sequence:

  • Bedrock
  • Dunite Saprolite (Basic Ore)
  • Chalcedony
  • Clay (waste)
  • Oxide Ore
  • Silicate Ore

Geological expertise is essential in defining the relationship between geological contacts and stratigraphic sequence.

Modelling application

To model bedrock as a continuous surface, the contact points were extracted directly and interpolated, creating a contact surface. Additional points were included at the end of holes that did not intercept the bedrock and, in areas with poor geological information. Both sets of points helped define the bedrock surface.

The dunite saprolite ore bodies have a flat and smooth shape, usually lying on the bedrock surface, formed by the weathering process of dunites. To generate this surface, hanging wall contact points from dunite saprolite were used. In areas with no dunite saprolite mineralisation, a minus 2 m offset from the bedrock surface was used to interpolate (figure 1a), resulting in a continuous surface along the entire deposit. There are only dunite saprolite orebodies where their surface is above the bedrock surface, to guarantee this chronology, Boolean calculations were carried out (figure 1b).

For other rock types exhibiting complex shapes (strong variations in thickness, length, dip and along the strike), the contact points between the litho types were extracted and converted to a volume function (f (x,y,z)) within Leapfrog. Points inside (>0), points outside (<0) and contact point on surface (=0) were defined and arranged according to the position (x,y,z) related to the contact point. This equation described the infinite numbers of coordinates that lay on the surface. Positive and negative values increased linearly as they moved away from their point of reference (figure 2). Figure 3a shows the control points that were used for chalcedony modelling. Figure 3b shows the geological domain constructed from the control points.

Figure 1a) Dunite saprolite and bedrock surfaces. Dark grey represents the dunite saprolite.
b)  Dunite saprolite on bedrock surface after the Boolean process.
Figure 2: Positive and negative values increase linearly as they move away from their point of reference (contact point).
a) Control points used for chalcedony modelling.
 b) Chalcedony geological domain constructed from control points.

Laerico Guedes Bertossi & Gustavo Usero
Resource Geologists