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Financial markets and the mining industry have lost all touch.
With a raft of innovative new technologies available, why is it that mining is still such a high risk investment? After all, this is a time when doctors can look inside patients without making incisions, robots are exploring other planets, cars are learning to drive themselves and data is so readily available that Big Data has become a business on its own.
The short answer is that it does not have to be. Just take a look at the oil industry, which shares the same genealogy as mining.
I started in the mining sector before spending time in the oil industry. This experience allowed me to understand the differences between both sectors and why things seem to work out better for oil companies. To put it simply, the whole process in the oil industry takes longer, is more complicated and is more expensive. Any project aimed at producing hydrocarbons has many more milestones before a single drop of oil is extracted. Each milestone is cumulatively more expensive, so much so that there would be no way any one in their right mind would invest in projects of such proportions if there were not a large number of dedicated analyses, risk assessments and reassurances in place. The important question is how can the mining sector benefit from this approach?
As many good things in life, it boils down to three major things. The first two are much easier to discuss. They are integration of disciplines and good practices. The last is putting this into action.
In a way, if there is one major benchmark in both mining and oil that is of interest to both investors and project developers, that will be reserves estimates. Ideally, they would like to know the real reserves and how much can actually be recovered. However, by the time these numbers are known most projects are close to completion. For oil and gas this is a major component of risk and financial assessment that starts from the very beginning of a project. The techniques available to make these forecasts are slowly making their way into the mining industry.
For both oil and gas and mining, most techniques are borrowed from other disciplines. In fact, relatively few techniques have actually been developed for geological activities specifically. Well known methods include kriging, which was developed for the estimation of gold ore in South African gold mines, and the technology pioneered by the Schlumberger brothers for the characterisation of oil reservoirs. In reality, the majority of statistical methods come from mathematics and engineering. Biology and social studies have also contributed immensely to modern algorithms and medicine, astronomy and the military have developed equipment that is now used in mining and oil.
The major problem is that most of these methods can sometimes feel a little bit dry for the geologist, and their application may not be immediately obvious. This means that opportunities are missed to use advanced methods that could save time or provide a more robust assessment of mining assets. When applied properly, many of these techniques not only support project developers but also provide investors with a better assessment of the economic potential and possible risks associated with a project from a very early stage.
We now live in very exciting times when advancements in computing capacity allows for the easier application of mathematical techniques. We can access and analyse unprecedented amounts of data, from proprietary databases to the vast amount of freely available maps and reports.
Other industries have already seen the benefits that these advancements can bring. However, they were not embraced immediately, without regards for cost/benefit or safety. Going back to medicine, new drugs need to pass a herculean marathon of trials to prove that they are not only efficient and safe but also that they provide better benefits than the previous options. They also have to prove that they do not incur any side effects that are worse than the original condition. This shows that following good practices is essential for success.
In mining and geology in general, we all know stories of how new technologies have promised so much and in some cases delivered very little. Most of the time it is to do with the bad application of these methods. They can be used in wrong situations, under the wrong assumptions, or simply just overstretched beyond the reach of the techniques. I know of people trying to justify a whole exploration programme based on satellite images alone without any other supporting data. For me, the best example of improper use of data analysis was when I was working in the oil sector and was asked to apply a statistical algorithm to a certain dataset. The people who requested the exercise did not believe in it and did not understand why or if it even should be applied. However, they were required to do so under company guidelines. As the analysis progressed, their opinion changed. If the results were good, excellent job! If the results were bad, it was because the whole technique was non-sense. What impressed me the most was that no-one new how to apply the algorithm and yet they were all ready to use a pre-prepared Excel spreadsheet to do the exercise. This was a document created by someone who had left the company and there were no proper instructions of how to use and apply it.
So, there are processes out there that can bring real financial benefit for projects in the mining industry if properly applied. The third essential element necessary to make them work is the will to action them properly.
The recent economic crisis has affected the mining sector hard just as it has affected many other sectors. Fortunately, investors are still looking to invest in mining. However, because of the high risk/high reward aspect of this industry, they are looking for safer positions. Therefore, projects at early stages are not as attractive to investors as they once were.
As competition for investment increases, companies need to become leaner and meaner. The use of these new techniques and approaches can help projects in the early stages of the mining cycle become more investor friendly by de-risking it.
Geology is a fascinating discipline, especially when viewed in combination with the many other specialities in order to understand the natural world. Big Data, computing and new approaches are affecting many other aspects of modern society. They can also be used in the mining sector; not to substitute current and established techniques, but extending them to provide additional benefits to project developers and investors.
Ruth G. Gonzaga is the founding director of Gonzaga Geology & Research in the UK. Gonzaga Geology & Research uses a multidisciplinary approach combining standard techniques, assessment of analogues and advances in analytical procedures to gather data and information that would otherwise be unavailable, too costly or time consuming to acquire by traditional methods. Our on-demand reports and data analysis products provide your team with evidence to support your decision making process as an investor or a project developer.
