KEYNOTE CONFERENCE: Machine learning for exploration: review of current and future tools
Machine learning has seen a growing interest in the last five years and we often see the term applied in the context of mineral exploration, mine exploitation and geoscience studies. In the mineral exploration space, both recent start-up companies and well-established mining and service companies are implementing machine learning in all facets of their work. Machine learning is used to support targeting, help define and interpret exploration vectors, integrate complex datasets, extract value from geophysical data and make core logging quicker and more reliable. New applications are regularly developed, and it is not clear yet what the limitations are.
These implementations promise impressive value gains but how these gains will be achieved is not clear to a general public who is unaware of the underlying technology. In addition, the potential for these technologies to surpass human performance in specialized tasks creates fear around job loss and restructuring, motivating some to reject them altogether. As is often the case, however, the reality of the impact of these methods on the mining industry is more complex than is widely perceived. Through a series of examples and case studies, this presentation explains machine learning, shows current applications in mineral exploration and discusses future applications, opportunities and challenges.
SHORT COURSE: Valuation of Mining Projects
A major part of developing a mining project involves identifying those projects that have the potential to move on to more advanced study stages (Conceptual, PFS, FS). This is particularly important, considering that mining, and especially mineral exploration, is a risky activity that requires to adequately allocate available funds.
Likewise, as part of the purchase/sale and transfer operations of mining projects, it is important to set reference values according to the type of deposit, its results and the level of study achieved in such projects.
Both aspects are relevant in mining exploration activities and require an adequate valuation of these mining assets based on available information, which is particularly complex in the early stages of development of a mining project or asset, where limited information makes decision-making difficult.
This course covers the methodologies used and accepted in the mining industry for the valuation of mining assets and/or projects in early stages of development and exploration, as well as the qualitative and quantitative aspects to be taken into account in this process. The course will provide both technical support and practical examples for a proper understanding of the valuation process.
