In the course of more than two decades as a geologist, I’ve had the opportunity to manage and implement geological surveys and exploration programmes all over the world – including recent work with Seventy Ninth Resources in the Republic of Guinea.
Exploration geologists seek to identify mineral deposits and other natural resources under the earth’s surface. This process is vital for assessing the value of an exploration license. It is only following the work of exploration that we can reach an understanding of the subsurface mineralisation within a given region and assess its economic potential.
But the work of exploration is by no means simple or straightforward. In fact, it is an uncertain process, one that deals with probabilities rather than absolutes. Ultimately, there is no way to state beyond doubt what might be hidden beneath the ground. We have to use a wide range of strategies to evaluate the potential of a license, from remote sensing and geochemical surveys to extensive drilling operations.
In its inherent uncertainty, exploration has much in common with the investment sector. In both cases, there are no guarantees. It’s simply a question of taking the soundest and best-informed approach to minimise the risks involved.
For this reason, data is fundamental for both geologists and investors. Whether you are deciding how – or if – to continue exploration in a particular area or if you should invest in a venture, the choice you make may have consequences worth millions of pounds. In these circumstances, the accumulation, integration, and interpretation of data is imperative.
Is data “the new gold”?
The growing importance of data in virtually every sector has led to a range of pronouncements that, interestingly, frame data as a raw material. The World Economic Forum (WEF) described data as “the new gold”[i] while both the European Parliament and the International Monetary Fund (IMF) have asked whether data might be “the new oil”.[ii] And the financial value of data may justify this type of statement – a WEF report from 2018 estimated that 84% of S&P500 company value came from intangible assets including data.[iii]
However, I think it’s important to remember that data is not inherently valuable. Indeed, an overemphasis on data for its own sake can do more harm than good. What really matters is the type of data we collect, how we store it, and how we interpret it. No amount of data will help us if we persist in posing the wrong questions or if we fail to accurately assess its quality.
This is something that those of us in the exploration field encounter first-hand. The way that we approach data is fundamental to the success of an exploration programme. As I’ll explain below, mineral exploration moves through a series of stages, and at each stage our approach must be guided by the data gathered and the conclusions drawn from the preceding stage. This means that we need to get our approach to data right from the very beginning.
And in the work of an exploration geologist, nothing exemplifies the importance of data better than the question of where and how to drill.
Data-driven drilling
Drilling boreholes into the subsurface is the only definitive method for sampling subsurface mineralisation. As a result, there is perhaps no more consequential moment in establishing the value of a particular lease – for this reason, geologists often refer to drilling as “the truth machine”.
However, drilling is also one of the most expensive parts of exploration. And while any form of drilling has significant costs, there is also a direct trade-off between the quantity of information and the cost incurred. Diamond drilling (DD) provides more information about the subsurface than alternatives such as reverse circulation (RC) or auger drilling, but it is also one of the most expensive approaches.
This means we need to maximise the value of data gathered by drilling – we need to choose the right place to drill as well as the right type of drilling. To this end, deciding where and how to drill will be informed by a range of other data sources that we can acquire in an earlier stage of the exploration process.
Thankfully, there are many opportunities to acquire a broad range of datasets prior to drilling. For instance, in many cases we can access historical data from previous studies that revealed mineralisation in the region – though questions may need to be asked about the quality or veracity of this data depending on its nature and source.
We can also conduct broader surveying activities to help direct our decisions about drilling, each of which offers us rich and complex datasets. This can include remote sensing, airborne and ground-based geophysical surveys, soil or stream sediment sampling, geological mapping and many other techniques, each of which contributes to establishing the likelihood of mineralisation at a particular location.
It is only by amassing and carefully analysing such a broad range of data that we can make a sensible, informed choice about where and how to drill. This allows us to maximise the value of the data we amass through drilling and ensure that we’re making the best possible use of the financial investment that it requires.
The importance of interpretation
The specific example of drilling highlights two key aspects of the way data is used in exploration geology – both of which I believe have wider applicability and will likely resonate with the world of investment.
In the first case, it shows how, at each stage of the process, the available data informs the next stage. We use the data we have already acquired to shape the kinds of data we subsequently gather – the method we use, the area we focus on, what we look for, and so on. We identify the best place to drill by integrating and interpreting our existing data to identify the location that is most likely to host economic mineralisation. But it is only by understanding the value of this data and how to interpret it that we can reach this conclusion.
Secondly, it shows that we need to be parsimonious and focused in our data gathering. Data is not free, and more is not always better. When we are assessing land value, we need to be mindful that the costs of exploration will not always be offset by the value of any mineral deposits discovered. Any data we gather needs to be justified by the existing information and commensurate with the potential value it will reveal.
These two aspects make clear that data is enormously important for establishing land value, but also show that data must be gathered in a systematic way as part of an ongoing process of interpretation and evaluation. And these are lessons that those who have found success in the investment world will not doubt recognise.
Ultimately, making decisions without data is taking a shot in the dark – it’s something we all want to avoid as far as we can. But it is only through careful interpretation that data can show its true potential. And that’s why expertise and diligence are – and will remain – fundamental attributes, despite the rapidly changing environment we’re all inhabiting.
Automation and the future of data
The role that data plays in exploration geology shares another similarity with its role in investment – it is continually evolving. The kinds of data we can access, the quantity we can store, and the ways in which we can interpret it are changing all the time – and part of our role as experts in the field is to stay abreast of developments.
Here at SRK, we’re committed to being at the leading edge of data analysis methods in our industry. The emergence of machine learning and AI-driven data solutions are of particular interest in the context of exploration programmes, as they enable us to analyse far greater quantities of data than ever before.
This is particularly important given that data, unlike oil or gold, is not a scarce commodity. In fact, the amount of data we have access to is growing exponentially – for instance, through an increase in satellite and airborne data, including high-resolution drone imagery.[i] As a consequence, increased efficiency in interpreting this data becomes vital.
Again, we are not alone in seeing the value of these new approaches – all sectors that rely on data are exploring how they could improve their decision-making. A 2019 study from McKinsey found that data and analytics are transforming the competitive landscape across a range of businesses, and that those who are leading the way in these areas are seeing major successes as a result.[ii]
There have even been instances of a direct transfer of innovation between the business and exploration worlds, with “recommender systems” developed and deployed by firms like Amazon to understand the co-occurrence of customer purchasing behaviour being applied to mineral co-occurrence in order to predict the existence of undiscovered deposits.[iii]
Such automated approaches to data analysis have significant predictive potential, and it has even been argued they can help to reduce the subjective component of exploration planning. However, there is reason for caution here.
While machine learning, AI, and other forms of automated data analysis have a range of benefits, they are not a panacea for all our data issues. As SRK’s Chris Woodfull recently explained, machine learning can still face issues resulting from inappropriate data selection and poor-quality data, as well as inherent biases built into the algorithms used.[iv]
Building partnerships around data
Ultimately, the concerns about AI and other new technologies supplanting human expertise remain overstated. As a recent research paper has argued, “by relying solely on technological development, we may fail to consider the requirement for human innovation and creative problem-solving in the generation and critique of multiple predictions, based on disparate datasets.”[i]
Which is to say that, for the foreseeable future, there will be no alternative but to draw on the knowledge, expertise and understanding of experienced exploration geologists. Without their oversight, the data that is collected during an exploration programme can be misinterpreted and lead to costly errors. Given the importance of exploration data and the consequences of decisions made using this data, it is important to get it right at the start and ensure that data can be collected efficiently and cost-effectively for each exploration programme.
The same, of course, is true in the investment world. And it is this shared recognition of the importance of data that is at the heart of SRK’s partnership with Seventy Ninth Resources. By recognising the importance of expert-led analysis, we can bring the worlds of geology and investment together in a mutually beneficial way, sharing knowledge and helping to pave the way toward a data-driven world.
[1] World Economic Forum, “Data is the new gold”, July 2020
[2] International Monetary Fund, “The economics and implications of data”, September 2019; European Parliament, “Is data the new oil?”, January 2020
[3] World Economic Forum, “A new paradigm for business data”, July 2020
[4] Shirmard et al, “A review of machine learning in processing remote sensing data for mineral exploration”, Remote Sensing of Environment, January 2022
[5] McKinsey, “Catch them if you can: How leaders in data and analytics have pulled ahead”, September 2019
[6] Mining Technology, “Discovering new mining deposits with big data”, October 2018
[7] SRK Consulting, “Case study: Taking a combined approach to improve prospectivity modelling”, March 2022 [1] Davies et al, “Learning and expertise in mineral exploration decision-making”, International Journal of Environmental Research and Public Health, September 2021
