A Dynamic Approach To Drill Programme Design

To assist in optimising time efficiency and value for money while planning and supervising drilling programmes, companies such as SRK ES are embracing the use of implicit geological modelling software.

With clients’ exploration budgets being squeezed ever further, long gone are the days of planning collar locations and orientations for a whole drilling programme at the outset of a campaign. It is now imperative that the modern exploration geologist plan holes on the fly, modifying drilling locations to try to achieve successful drilling intercepts, to maximise time and budgets. Although it has detractors, introducing implicit modelling software programs has revolutionised resource modelling, allowing resource geologists to visualise data effectively, help identify crucial trends and structures, and create multiple interpretations of geological and mineralisation models rapidly, compared to CAD-based methods of 10 years ago. SRK Exploration Services has embraced implicit modelling software, specifically Leapfrog Geo, and uses them as a valuable tool in dynamic exploration programme design.

SRK ES recently used Leapfrog Geo to great effect during a long-term drilling programme for a client in Saudi Arabia. SRK ES was brought in to design and supervise a surface mapping and diamond drilling programme over discrete, discontinuous, gold-bearing quartz veins. The data collected and interpretations made were then used to build the Mineral Resource Estimate completed by SRK UK

SRK ES recognized this opportunity to create a dynamic programme design with implicit modelling. Data collected in the field could immediately be used to update a working 3D geological model, then used to direct drill targeting in real-time. This method made it possible to develop a dynamic drilling programme where in which informed decisions regarding collar positioning, borehole density, drilling orientations and end of hole could be made swiftly, based on evolving data. And dynamic quality control of data meant assessing issues and bias as they arise. With this approach the targets were drilled and the drilling budgets optimised. By gradually adding mapping and logging data, SRK ES’ geologists produced a more holistic model which incorporated multiple interpretations and adjustments with every new piece of information. Also, regular programme updates could be distributed through 3D visualisations.

While the usefulness of implicit modelling has been well established, quality technical, geological and structural data must be collected and interpreted in a traditional manner. Drafting scaled cross sections showing drillhole fences with annotated interpretations should continue in drill programme management to ensure that the geologist understands and interprets the geology, rather than rely on a “black-box” approach using software. The project geologists can then scan these cross sections and reference them within the software to assist with 3D digital interpretation.

To conclude, SRK ES believe the use of implicit modelling in exploration programs of all stages will become an industry norm which SRK ES plan to lead the way on for their clients.