The benefits of implicit geology modelling

Implicit geological modeling is here to stay. But it’s not the only thing geologists need.

Collecting comprehensive sampling and geoscience data from the field is the first step in an exploration or mining company’s quest to define the location, shape, and grade of an orebody.

After that, the operation must transform their geoscience information into reliable geological models of the subsurface. Traditional explicit modeling methods do a great job of this, by providing geologists with the tools to visualise and build their unique interpretation of the deposits' geology down to the smallest detail.

Over recent years, implicit geological modeling methods and solutions have spread through the industry and proved they are here to stay, largely in part due to ease of use, speed and intelligence.

Whether implicit modeling techniques generate better results than explicit methods remains a topic of discussion. Ultimately, both modeling methods are tools, and like any tool, in the wrong hands, they can be misused. The ability of a geologist to make a model that accurately reflects and represents in-ground conditions is still determined by the skill, knowledge, and due diligence of the individual geologist, combined with adequate field observations and data support, as it should be.

Figure 1: Implicit geology model generated with the GEOVIA Geology Modeler, supports geologic features such as normal and reverse faulting, erosional surfaces, implicit and explicit intrusions, and ore bodies. 

An overview: benefits of implicit modeling

For several years now, implicit geological modeling has been gaining ground on the highly trusted and widely used explicit geological modeling methods. There are good reasons for that. The below list outlines some of the clear benefits from implicit modeling. In the below example, the comparison is made between GEOVIA’s Surpac (explicit) and Geology Modeler (implicit) solutions.

• Speed – generate complex geological models in minutes.
• Automation – build models in an automated way, saving time and making the process auditable and repeatable.
• Accessibility – geology model generation is not dependent on a single individual user, anyone within a team can update a setting, or add new data, and update the model.
• Traceability – geology model revisions capture and retain modifications over time. This provides geologists with the capability to capture settings, input data, and decisions made for each model generated, which in turn allows for excellent traceability and auditability. This provides geologists with confidence the geology model has been generated using the right data.
• Integration – Modern implicit modelling tools can integrate with other platforms used across the business, which improves data security, management, and accessibility within other business processes (such as revision and lifecycle management, task management, issue management, risk management, or project management). In this example, GEOVIA Surpac and the Geology Modeler integrate with Dassault’s 3DEXPERIENCE platform.

Explicit models are accurate and reliable. But they are often created using repetitive manual processes; as such they can be difficult to update when new data is supplied. This makes them time-consuming and difficult to work with when responding to changing business objectives or operational demands. It can take hours and sometimes days for a geologist to digitise all their wireframes, create the meshes, make sure those meshes are valid, and then use them in block modeling processes.

An implicit geological modeler helps geologists automate that process, which in turn makes the process much faster, as well as fully traceable and repeatable. By reducing the amount of manual work geologists are now doing, an implicit solution gives them more time to spend in the field interpreting the geology or reviewing their data to better understand the genesis and evolution of a deposit.

The benefits of implicit modelling in more detail

Radial Basis Function (RBF)

Implicit modelling is a process where a continuous mathematical representation of an attribute is determined across a volume. This approach requires minimal interaction from the geologist and the computational calculations drastically reduce the amount of time it takes to perform the modelling. This approach means model generation can typically be completed in seconds or minutes. This is an improvement across orders of magnitude when compared to explicit modeling methods applied to identical data.

The Radial Basis Function algorithm (RBF) is well known throughout the mining industry today for its use and adoption in implicit modelling. It has quickly become the go-to algorithm for building implicit geology models. This algorithm defines how each point in 3D space is interpolated based on the cloud of input data points. It is well-known that RBF is well suited to multivariate interpolation with scattered data. It allows us to fit all input source points, and generate a smooth surface, it also works well with a non-uniform set of data points and provides good extrapolation results. There are many implicit geological modelling solutions available based on this approach; however, at GEOVIA we have developed our own algorithms to improve RBF and make it even faster.

Data management

An accurate and representative geology model is only as good as the data that feeds into it. This reminds me of the phrase ‘rubbish in, rubbish out’, and it’s certainly no different with geology models. Diligent and robust data management and validation practices are essential in ensuring accurate, reliable, and representative geology models. 

Geologists must manage the mass of geoscience data collected by geoscientists, engineers, consultants, and contractors. This includes drillhole records, geological, and geophysical field observations, geochemical, lithological, and remote sensing data, assays, etc.

Many exploration and mining companies today work with explicit modelling software that often uses a file-based approach, where data and files are stored in folders locally on the user’s machine or file servers. This traditional data management tends to be slow, subject to human error, and as a result often causes rework or delays.

A business enterprise platform, leveraging a unified data model, either on-cloud or on-premises, provides a secure central data repository where geologists can store geoscience and mining data in any format, structured or unstructured. From there, all geoscience data, along with all other data, such as parametric mine designs, pit optimisations, infrastructure, simulations, land use, etc. – will become part of a unified data model where one data source will always speak to another and all data is interconnected and relational. Whenever a new piece of data arrives in the repository, it is updated across the platform. 

Figure 2. The Geoscience Data Administration application provides geologists with the tools to manage borehole revisions, track changes over time and revert changes when needed.  

The best of both worlds – gaining greater control through harnessing the power of explicit and implicit modelling 

Implicit modelling methods can also leverage data and benefit from pre-existing explicit geology models to give geologists a better representation of the sub-surface environment.

For example, the GEOVIA Geology Modeller can give control back to geologists in the following ways:

• Constraint lines – associate or digitise polylines to support the available borehole data and realise desired outcrop patterns or cross-sectional interpretations within an implicit geology model.
• Explicit intrusions/orebodies – associate explicit solids to gain explicit control over high-priority domains while still implicitly modeling surrounding geology and structures.
• Pinch-outs – globally control the taper of a pinch-outs.
• Structural measurements – utilise downhole structural measurements to better model faults or folded deposits.
• Dynamic isotropy and trend surfaces – quickly model the changeable geomorphology of orebodies and/or intrusions.

These features and more, make for a comprehensive implicit geology modeling approach, which makes it possible for geologists to revise and refine models until they generate the exact model that they need, within an automated and repeatable process. This allows geologists to spend time getting the geological interpretation right, giving them confidence in the resulting implicit model.