Interesting study on the expectation for seafloor massive sulphide deposits in Norwegian waters
A recently published paper has established a model to simulate expected ranges of resource- and economic potential related to seafloor massive sulphides (SMS) deposits in Norwegian waters.
The stochastic model is developed based on selected industry knowledge, expectations, and perceptions elicited through a participatory systems mapping session with 82 participants and 20 in-depth interviews.
Ore grade and timing is key
Copper, zinc, and cobalt are expected to be the minerals of highest economical interest, where copper makes out the most significant part.
The study indicates a positive net present gain of approximately 2.5 billion USD in case of a high ore grad of 5%, while an ore grade of 3% will result in a net present loss.
The two different ore grade values represents the difference in average expectations seen from the industry and academia respectively.
The second key aspect is timing, as revenue from mining will come quite some time later than the exploration activities, as well as time needed to develop and build full scale production equipment and facilities.
While several previous estimates and studies highlight a huge resource potential, this study reminds us that high value, in terms of revenue, does not necessarily mean high net present value.
Opportunity for innovation
A key challenge for SMS deposits is associated with expensive mapping and coring to establish ore grade and resource potential. This cost comes very early in the project.
The paper highlights an open space for innovation and technological improvements to mitigate this challenge. More efficient coring technology and innovation efforts to reduce the amount of coring needed are highlighted as important.
Join the Deep Sea Minerals conference in Bergen (25) 26-27 October to learn more about the challenges and opportunities within deep sea mineral both national and international.
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The paper is written by PhD-students Rasmus Noss Bang (NHH) and Lars-Kristian Lunde Trellevik (UiB). GCE Ocean Technology has been interviewed as part of the paper.
The results presented are the average values across 1000 Monte Carlo runs where four stochastic seed variables are assigned varying values.
The paper is published in Mineral Economics, Raw Materials Repost.
