Article 2: Exploration Intelligence
In Article 1, I touched on a few of the general challenges the mining industry is facing today, including dramatically increasing global demand for diminishing and often lower-grade mineral resources, the worldwide shortage of experienced geoscientists, high employee turnover, and growing lack of collaboration between people and departments.
I also discussed what is rapidly becoming one of the biggest challenges of them all: grappling with the surge in big data and the need to manage it properly. Here, I look at the challenges of big exploration data specifically, and offer one solution for overcoming them.
Exploration data challenges
Mining is an expensive and risky business, so the more knowledge and insight you have about a deposit the better.
But all the data in the world — from traditional drilling and metallurgical tests, lithologies and assays, to high-tech core scanning and X-ray fluorescent analysers, etc. — won’t help if your mine suffers from simple things like poor communication between your exploration teams and your technical services manager, or not having a comprehensive understanding of all exploration activities, or not investing in good project management tools to manage exploration programs and projects.
It also won’t help if you are not managing your data properly. I’ve noticed that many mines around the world have been slow to adopt:
- Detailed dashboards that display in-depth analyses of necessary exploration activities and exploration data, which means these mines are not taking advantage of data analytics and trends that can help them make the best possible exploration decisions. And without sound exploration decisions, production may suffer and affect all other downstream activities.
- Centralized storage for all exploration data, which has serious ramifications. For example, the mines may only be aware of part of their data while the rest remains hidden and unexplored. But that unexplored data could hold the key to unlocking the maximum value of their entire exploration dataset. In addition, data that is not centralised is much more likely to be lost — when an employee leaves, for example, and no one else knows where the data is — which means the mines must spend more time and more money collecting the data again.
- Proper analytical tools to help exploration teams unlock data trends and value, as well as a single platform on which to analyse and display all aspects of exploration. This includes:
- exploration metrics
- sample analysis
- drillhole information
- ore grade visualisation, and
- exploration documentation, including maps, plans, SOPs, assays, permits, etc., as well as other soft data like video and photographs.
A mine that is able to analyse hard and soft data together is in a far better position to, for example, detect a subtle alteration pattern from hyper-spectral core scans that is not evident in assay results. And this may could change the mine’s entire resource estimation.
One solution
One solution to these challenges is for mines to pursue exploration intelligence — that is, to use big data management and big data analysis to take their collected data and use it to reveal unexpected possibilities or important new insights.
GEOVIA’s Exploration Intelligence application, for example, provides exploration geologists and managers with a global visual overview of all exploration activities, ensuring up-to-date knowledge of everything that has happened or is happening at the exploration site.
The application also enables exploration geologists to do things like:
- index all geological data, both structured and unstructured, hard and soft, from various source systems
- select, adopt, and customise advanced-analytics programs to, for example, measure and analyse drilling campaigns and display the status of individual drill holes
- develop detailed, drilldown views of specific exploration activities, such as drilling sampling results, sorted by their campaign code, status and period, and
- georeference stored datasets on a single platform.
Next in this series
The following articles will discuss data challenges and solutions for developing geology, production, and caving intelligence.
