In view of increasing import dependencies and decreasing ore grades in conventional mining, societies with large resource needs such as those of the EU are looking for new potential sources of mineral supplies. Seabed areas in international waters host considerable amounts of mineral resources that contain various elements, among them metals such as cobalt, copper, nickel and manganese that are used in today’s high- and green-tech applications, e. g., electric vehicles. The EU-funded (FP 7) Blue Mining project has investigated the resource potential of manganese nodules and seafloor massive sulphides. Blue Mining has studied and developed associated exploration methods and mining technologies. This paper gives insights into RWTH Aachen University’s work focussing on the economic relevance of deep-sea mining – both from the markets and the mining perspective. It is concluded that the use of deep-sea deposits may allow countries such as Germany to gain access to raw materials of high importance to the EU economy and of high risk associated with their supply.
1.1 Marine mining and research
Covering about 70 % of Earth’s surface, the oceans and seas contain many types of mineral deposits (SPC, 2013). There are alluvial minerals such as diamonds, phosphates and iron ore, which are washed out of land-based deposits and deposited in sediments near shore. It has been known for a long time that the deep sea may contain rich mineral resources. Vast fields of polymetallic nodules that cover the seafloor at depths between 3,500 and 6,500 m have already been identified. Attempts to mine seafloor manganese nodules (SMnN) date back to the 1970s and 1980s when first pilot mining tests were carried out in international waters in the midst of the Pacific Ocean. Besides SMnN, seafloor massive sulfides (SMS) are most promising. Although there are no mining activities to this date, government agencies and private companies are preparing for Deep-Sea Mining (DSM) and conduct considerable investments into exploration, research and development of technologies to discover, assess and mine such resources (Blue Nodules, 2019; ISA, 2017; JPI Oceans, 2019; Kim et al., 2013; NIOZ, 2019).
In recent years, four EU-funded projects – Blue Mining, Blue Nodules, Midas, and ¡VAMOS! – have revitalized research in Europe to develop new technologies and knowledge-based solutions to discover, assess and extract deep-sea mineral resources in a sustainable manner (Blue Mining, 2018; Blue Nodules, 2019; MIDAS, 2016; Vamos, 2018). The European offshore industries and marine research institutions have global experience and already provide technology to the dredging and oil and gas sectors. Also Germany plays a crucial role in marine research, in particular in marine surveying, extraction and processing technologies. About 400,000 employees and a turnover of 50 bn € confirm the economic importance of the marine sector in Germany (BMWi, 2019).
1.2 The Blue Mining Project
The EU FP7-funded project “Breakthrough Solutions for the Sustainable Exploration and Extraction of Deep Sea Mineral Resources” (GA No. 604500) started in 2014 with 19 EU partners from industry, research institutions and academia. During four years, the consortium worked interdisciplinary to promote knowledge and to raise the technological readiness level of DSM. The work programme included a wide range of topics from exploration through extraction and hoisting to economic evaluations. Step changes have been made in computer modelling, new exploration methods and technology concepts. Unique geological data sets have been acquired during new research cruises at sea. Multi-scale laboratory tests, unique in size and scope, focussed on the vertical transport system (VTS). Computer codes developed in Blue Mining further allowed detailed simulation of riser dynamics and slurry transport processes. The scope of the RWTH Aachen University (RWTH), Aachen/Germany, work package included technical solutions for sustainable mining, deposit modelling and the economic evaluation of DSM. Based on two deposit models, project plans for mining SMS and SMnN deposits, cash flow models and a market analysis were developed. Finally, all findings were summarized in two blue print feasibility studies.
1.3 Approach of this paper
This paper aims to present assessments of the economic importance of future DSM. The approach uses two levels of economic evaluations – from the perspective of national economies and from the perspective of potential mine operators. Two major research questions tackled during the study were: Do societies need DSM, and how could their economies benefit? Is it worthwhile to mine in the deep-sea, and would it be economically feasible?
The main sections of this paper are based on Blue Mining research results achieved by two RWTH institutes, including the Institute of Mineral Resources Engineering (MRE) and the Geological Institute being part of the Energy and Mineral Resources Group (EMR). The study focusses thereby on SMS and SMnN deep-sea deposits in international waters, called the “Area”. The International Seabed Authority (ISA) supervises the Area which is subject to economic interest worldwide.
2 Mineral potential and strategic role
Why do we need DSM? This question was posed as an open question to the participants of the Blue Mining final workshop in Aachen in 2017. A word cloud (Figure 1) shows the most frequent answers. The strategic potential of DSM is evident. Consequently, the society’s perspective may even be as important as the economic perspective of a mining company.
2.1 Need for minerals
Access to raw materials is vital for the development of societies (Blue Mining, 2018). The increasing number of people does not only contribute to increasing demand, but also improving living standards do so as well (Lusty & Gunn, 2015; United Nations, 2017). In addition, technological trends such as e-mobility increase the diversity of mineral raw materials needed by industries and people. At the same time, conventional mineral deposits on land deplete and miners have to operate in increasing depths and they have to process lower ore grades than before (Lehnen, 2016). Consequently, mining costs increase and so do environmental challenges.
Such developments in the minerals industry have led to mine closures in Europe. Consequently, import dependencies and risks have increased. The EU uses two indicators – economic importance and supply risks – to define “critical raw materials”, which are contained in a list that comprises in 2017 further nine elements compared to the last update of 2014. Besides rubber, all commodities are of geological origin. Moreover, the import rates of non-critical mineral resources to the EU are quite elevated and the EU requires these materials as well (Table 1).
2.2 Mineral potential of the deep-sea
The international seabed bears the chance to secure mineral supplies for the European economy. The metals marked bold are defined as the economic key metals within Blue Mining (Table 1). In addition, SMnN and SMS may contain other elements (underlined in Table 1). Based on the economic models, nickel, cobalt, copper and manganese have been defined as key elements for SMnN deposits while copper, gold, silver, lead and zinc are regarded as the key drivers for SMS projects.
SMnN are widespread in the oceans, with the most significant occurrences in the eastern Pacific Ocean, the Peru Basin, the Central Indian Ocean Basin and the Penrhyn Basin (Hein & Koschinsky, 2014). 81 % of the SMnN fields are located in the Area, 14 % in the Exclusive Economic Zones (EEZ) and 5 % are part of the proposed extension to the continental shelf (Petersen et al., 2016). The total area is estimated to 38 M km2 (Petersen et al., 2016), of which only 1,275,000 km2 are being explored today (holding an exploration license). In the Clarion-Clipperton-Zone (CCZ) a total of 21,100 Mt contain about 6,000 Mt of manganese, 278 Mt of nickel, 42 Mt of cobalt and 224 Mt of copper (Hein & Koschinsky, 2014; ISA, 2010).
SMS deposits are located in the deep-sea at mid-ocean ridges, back-arc basins and submarine volcanic arcs (Hannington et al., 2010). They are considered to be modern analogues of ancient volcanogenic massive sulfide (VMS) deposits found on land that make a significant contribution to global metal supply today (Monecke et al., 2016). With an estimated number of 1,000 deposits ranging in size between 100 t and 10 Mt located in the neovolcanic zone of the world’s oceans, 600 Mt of SMS deposits cover an area of 3.2 M km2 (Hannington et al., 2010; Petersen et al., 2016). They contain a median grade of 3 wt % copper, 9 wt % zinc, 2 ppm gold and 100 ppm silver (Petersen et al., 2016). Extinct deposits, which are far off-axis and potentially buried by marine sediments, are difficult to detect. That is why it is unclear how many of them are still undiscovered and how well they are preserved (Monecke et al., 2016; Petersen et al., 2016). Only a few deposits – TAG, Middle Valley, Solwara 1 and Snakepit – have been drilled yet due to the challenges of deep-sea exploration. Thus, SMS deposits with resource estimates compliant with internationally recognized reporting standards are very rare. A total area of 3.2 M km2 may be favourable for SMS deposits, from which 58 % are located in the Area, 36 % in EEZ, and 6 % in areas included in proposals for the extension to the continental shelf (Petersen et al., 2016). Only 60,000 km2 are currently covered by license contracts in the Area.
Since there is neither economic technological readiness nor a legal framework (mining code) for DSM available, none of the deep-sea deposits may be classified as reserves yet. That is true for SMnN as well as SMS. However, the mine planning concepts developed by Blue Mining may contribute to a classification of “potential reserves” (Volkmann & Lehnen, 2017).
2.3 Potential deep-sea mine production
Although SMnN contain critical elements such as cobalt, rare earth elements, tellurium, and gallium (Hein et al., 2013), which are of strategic importance for the EU economy (European Commission, 2017), most studies to date have focused on the extraction of nickel, cobalt, copper and optionally manganese (Pophanken et al., 2013). Even if the focus is mainly on the metals nickel, cobalt and copper, the recovery of manganese is currently indispensable for economic reasons (Volkmann et al., 2019). The metal production of a single deep-sea mining project could significantly reduce the import dependency of highly industrialised and import dependent countries such as Germany (Table 2). In the foreseeable future, the demand for these metals is predicted to increase due to their application in future technologies such as batteries (Marscheider-Weidemann et al., 2016).
Other than for SMnN mining, the processing of SMS will be most similar to established routines for massive sulfides on land. The metals of economic interest are copper, gold, silver, lead and zinc. However, compared to the global production and today’s largest active copper mines, the metal production of a single SMS mine is assumed to be insignificant. It may produce about 5,000 t copper, 0.4 t gold, 2 t silver, 70 t lead and 390 t zinc per year. However, besides the raw materials, responsible nations would also benefit from tax income, royalties and other economic profits.
Besides such production rates, Blue Mining has developed further production key figures for DSM projects. Such insights help to plan and calculate future mining operations, e. g., within feasibility studies and mine planning. With respect to SMnN yield per area, duration of mining, seafloor consumption and requirement may be estimated. Moreover, resource utilization, mining efficiency and extraction efficiency may be calculated. Over a typical project duration of 20 years, e. g., an area roughly the size of Luxembourg (2,300 to 3,700 km2) would be mined, which represents about 4 to 6 % of the eastern German licence area E1 (Volkmann & Lehnen, 2017). In contrast, SMS mining requires less area. Assuming again 40 Mt of ore to be mined over a period of 20 years, the total land consumption sums up to about 3.8 km2.
3 Feasibility of a deep-sea mining project
In order to realize the potentials of mineral supply from the deep-sea, mining companies need economically feasible concepts to prepare production sites at sea. As in conventional mining, knowledge of the deposit is crucial to plan a future mine set-up. Preparing such mine and project plans finally allows the calculation of costs and thus economic evaluations.
3.1 Deposit models
For SMnN, a deposit model was built using bathymetry and 55 box core sample data extending over an area of 255 km2 in the German license area in the CCZ. Mapping of the seafloor was conducted in multiple cruises, e. g., using echo sounders (Rühlemann et al., 2009). Areas with a slope over 3° were subtracted from the total tonnage, since there is no mining considered technically feasible (Rahn, 2016). Resource estimation was generated using ordinary kriging for the interpolation.
With respect to SMS, Blue Mining research cruises collected geophysical data over several extinct deposits in the TAG area of the Mid-Atlantic Ridge (26° N). Sub-seafloor structures, lithological boundaries and volumes allowed for an estimate of the ore content of such SMS deposits. The SMS deposit model cluster “Virtual Blue” built by RWTH consists of 30 single deposits ranging from 0.3 Mt to 5.4 Mt with an overall tonnage of 40 Mt. They are situated along the Mid-Atlantic Ridge, 12.5 km to each side of the spreading axis. 142 drill holes from Solwara 1 in the Bismarck Sea, explored by Nautilus Minerals, served as the basis for the deposit model. The metal grades from this back arc system were adjusted to a system that could be located along the Mid-Atlantic Ridge. Then, metal grades were interpolated between drill holes with ordinary kriging and finally a block model was created to calculate the tonnage of the deposit (Rahn, 2016; Rahn et al., 2019).
Geological deposit models provide mining engineers with information, e. g. bathymetry, grade and nodule abundance, which is a prerequisite for mine planning. Mine planning may cover the entire value chain – from exploration to the scheduling of machines and from financing of mining projects to the study of its economics. Blue Mining developed a set of different tools, methods and approaches to be used by both industry and authorities to establish mine plans (Volkmann et al., 2018a; Volkmann & Lehnen, 2017). They are to transform geological models into “economic maps of the seafloor”.
3.2 Potential mine set-up
For the studies conducted by Blue Mining, a number of technical specifications were pre-defined (“Terms of Reference”; Table 3), which are based on assumptions and estimates of the technical partners of the consortium. The studies examined whether the assumptions, e. g., on the mining and production rate, were reasonable.
To date, a common technical language is lacking for mine planning of DSM projects. During the Blue Mining project, a set of mine planning terms were defined for SMnN (Figure 2) (Volkmann & Lehnen, 2017).
The “mine plan” is considered to represent a map, which shows all information required to execute a mining project. It provides one, e. g., with information on the seafloor geology, such as nodule abundance, metal grades and bathymetric information including slope angles. Besides geological information derived from exploration data, mine sites, mining fields, and mining routes would be outlined in such a plan. A license area is proposed to be divided into several “mine sites” in which mining could be carried out over a longer period (probably several years). A “mining field” is the next smaller unit in a mine site, which is divided into strips that represent the harvesting path, i. e. the traffic pattern of the seafloor mining tools (SMT). The Blue Mining concept for SMnN mining was inspired by the high-tech farming industry (Hunt & Wilson, 2015) and involves harvesting a field partitioned into long, narrow strips (Volkmann & Lehnen, 2017).
The mining support vessel (MSV) follows one or two SMT on predefined mining routes that autonomously collect SMnN from the seafloor. About 60 to 100 football fields would have to be harvested on about 250 d/a to yield in a production of 1.5 to 2 Mt. Autonomously or remotely operated vehicles (AUVs/ ROVs) are envisaged to support the mining operation by scanning the seafloor. Information of the seafloor, geology, e. g., nodule abundance, obstacles and bathymetric data, are processed to update the mining routes and mining rates, i. e. SMnN are lifted to the MSV, where they are dewatered, stored and discharged onto bulk carriers for the transport to the processor on shore (Figure 3). Seawater and fine particles of sediments from the dewatering process are pumped back into the vicinity of the seafloor in order to reduce plume generation.
Blue Mining has contributed towards the development of SMnN mine planning tools. Computer-aided GIS programs offer a wide range of tools for spatial analysis. To identify the seafloor areas with the highest mineable proportions, so-called neighbourhood filters were developed (Volkmann & Lehnen, 2017). Through computational image analysis several mining fields with potentially mineable proportions of about 90 % (slopes ≤ 3°, nodule abundances ≥ 10 kg/m2) were discovered and analysed for a strip-like mining pattern. It was derived that each of the identified fields could sustain mining for several weeks or up to several months.
In the case of SMS mining, the mining concept proposed by Nautilus Minerals (Jankowski et al., 2010) served as a basis for mine planning. The DSM system basically comprises an Auxiliary Miner (AUX), a Bulk Cutter (BC) and a Gathering Machine (GM), which are operated remotely – on board of the MSV. The MSV is positioned above a deposit and remains there until it is mined. A deposit is bulk-mined in a top-down sequence. First, the top sediment layer is removed by using the AUX to cut and the GM to collect and transport the material. For the Blue Mining case study, the top layer is considered to already contain significant amounts of metals. The ore is lifted to the MSV, whereas waste is dumped outside of the pit shell. After the removal of overburden, the AUX prepares the initial bench by flattening out uneven terrain. Production is then ramped up by using the BC, resulting in an annual production of estimated 1.32 Mt at 3,300 operating hours per year. The AUX assists the BC by shaping the geometry of the pit by bench cutting or ramp preparation. After a bench is cut, the BC moves to the next mine site in sequence, which has already been prepared. Concepts to investigate the optimal pit shell have been considered but the parameters to define the optimal pit shell, e. g., the maximum slope angle, have yet to be investigated.
3.3 Economic evaluation
Two discounted cash flow models were developed to investigate the net present value (NPV) and internal rate of return (IRR) for SMnN and SMS mining operations. A good-, average-, poor- (GAP) analysis was carried out to investigate the economic viability of SMnN mining for different scenarios. In addition to the NPV and IRR, calculated minimum metal prices (for SMS) and sales values required to generate net profits (for SMnN) were compared to estimate future metal prices and sales values. Technical parameters such as capacities, mining and dilution, mineral processing and concentrate recovery were applied. Financial model parameters such as capital expenditures (CAPEX) and operational expenditures (OPEX), mineral processing and smelter costs (TC/RC), metal prices, royalties, taxes and discount rates were used. Geological parameters such as grade and nodule abundances were derived from the geological models, accordingly (Volkmann, 2018). All financial figures are stated in US-Dollars.
For SMnN, economic figures such as the NPV, IRR and net profits were based on assumptions and estimates from the Blue Mining case study (Tables 3, 4). The investment volume was estimated at 1.3 to 1.5 bn US$ in total, and operating costs range from 200 to 340 US$/dmt (dmt – dry metric tonne). Discount rates in the range of 15 to 25 % were set to reflect the risks of pioneer projects. For the Blue Mining case study, it can be demonstrated that a mine would be profitable under moderate and good conditions if processing and selling includes four metals (4M): nickel, cobalt, copper and ferro-manganese (Table 4). The following minimum sales values were estimated (US$-2015): 400 US$/dmt for the good case (4M), 550 US$/dmt for the moderate case (4M), 430 US$/dmt for the moderate case (3M) and 815 US$/dmt for the poor case scenario (4M). The poor 4-metal scenario or even a recovery of only three metals (3M) would only be possible with high commodity prices as of 2008. According to a prepared sensitivity analysis, metal prices of nickel and ferro-manganese, the TC/RC, and the annual production rate revealed to be driving-factors of profitability.
Although proposals to identify mineable seafloor areas have been made (Volkmann & Lehnen, 2017) (UNOET, 1979), former studies have mainly considered geological factors such as slope, nodule abundance and grades (Knobloch et al., 2017; Mucha and Wasilewska-Blaszczyk, 2013; Volkmann and Lehnen, 2017). A highlight of Blue Mining research was the invention of a graphical planning tool (i. e. nomogram, Figure 4) and a deposit valuation method for spatial mine planning of SMnN. Both can be used by industry, authorities or researchers to technically and economically assess mining systems and plans (Volkmann et al., 2018a). The invented methodology and tool may also help to investigate the environmental footprint of DSM. The nomogram exemplarily presented here (Figure 4) relates to a specific scenario of the Blue Mining case study (Volkmann et al., 2018a). The nomogram was used along with generated maps on the commercial value of the seafloor to delineate the areas of potential commercial interest for a study area of E1. Larger data sets must be analysed with improved methodologies and tools for spatial mine planning. A software for spatial mine planning is conceivable.
The economic assessment of the SMS case was based on Nautilus Minerals’ mining concepts transferred to the Blue Mining settings (Table 2). At a 10 % discount rate, the project base case has an NPV of 690 M US$, an IRR of 22 % and a return on investment of 156 %. CAPEX of about 700 M US$ and OPEX of about 100 M US$ were estimated. For the mining operation as such, the OPEX were estimated at about 40 US$/t (excluding costs for processing and refining). The copper price and the discount rate revealed to be the driving-factors of profitability, according to a sensitivity analysis. Copper had the greatest effect on the profit, followed by gold. It contributed 454 M US$ or nearly 70 % of revenue in the base case scenario. The break-even price scenario including both metals was estimated at 800 US$/oz Au and 0.7 US$/lb Cu (at the same time). These are again below the estimated future prices for these metals.
Blue Mining research indicated high economic potential for both SMnN and SMS mining. Both types of DSM projects are considered technically and economically feasible in the future. Nevertheless, the accuracy of the estimates needs to be improved, e. g., by testing and continuous further development of technologies, methodologies and tools. Further research is required e. g. with respect to the recovery of trace metals such as rare earth elements, which may become economically important to sustain the expansion of renewable energies and e-mobility. However, DSM will still be competing with conventional, land-based mining. Therefore additional drivers to explore and exploit new deposits may be first depleting known reserves, second increasing costs to develop land-based resources, and third security of mineral supply and reducing import dependence (Rahn et al., 2019).
The European Blue Mining project has filled gaps towards blue-print feasibility studies for future DSM projects. Innovative exploration methods have been applied based on new information acquired during modern ship cruises. Digital models of the deposits processed such datasets und led to mine plans and project plans for all stages of a DSM project including the preparation of detailed economic models. In the field of mining engineering, RWTH’s definition of terms and key figures is applicable to resource definition by investors and authorities. The developed tools further allow the economic evaluation of mining projects and actual mine planning by entrepreneurs as well as spatial planning by authorities such as the ISA.
In the presented study, SMS mining shows a positive economic evaluation. Due to the high metal grades and the lack of overburden removal, DSM may compete with land-based mining operations. SMS mining will become attractive to investors and mining houses, if current concepts are scaled up to higher tonnages and grades since many OPEX are high and fixed.
SMnN show a high economic potential whenever production, processing (Friedmann et al., 2017) and marketing of four metals (Ni,Cu, Co and Mn) can be realized. With the production and sale of manganese, the presented studies show economic feasibility under moderate cost and price levels. Further, SMnN mining may play a major strategic role for import-dependent economies. This study has shown that, e. g., already one major DSM project could supply the entire cobalt demand of Germany. In conclusion, DSM can significantly improve the supply of strategic raw materials to the EU.
This work received funding by the European Commission as part of the 7th Framework Programme for Research and Technological Development (GA No. 604500).
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