Uranium exploration comprises a critical activity at the front end of the nuclear fuel cycle but it is often poorly understood compared to other capital-intensive activities (Fig. 1). Exploration is a high-risk, high-reward business activity that is akin to a research-and-development process.
Exploration can lead to the identification of economic mineral resources that are developed through mining. Refined metal is subsequently converted, and enriched, for fuel fabrication and the generation of electricity in nuclear power reactors.
FIG. 1. Situating exploration in the nuclear fuel cycle. Adapted from [3].
The Nuclear Energy Agency (NEA) and the International Atomic Energy Agency (IAEA) co-publish a description of the global distribution of uranium resources in what is informally known as the ‘Red Book’. The ‘Red Book’ published in 2016 indicates that the total identified (reasonably assured and inferred) resources are 5,718,400 tonnes of uranium metal (t U) in the
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< US$130/kg U category. This estimate includes 3,458,400 tonnes of reasonably assured resources. Identified resources increased by only 0.1% since publication of the 2014 ‘Red Book’. The 2016 report attributes the lack of growth in identified resources to lower levels of investment and associated exploration activity under depressed uranium market conditions. In addition, the majority of exploration expenditures during this period were related to the development of the Cigar Lake and Husab uranium mines in Canada and Namibia, respectively.
Annual global uranium production has declined by 4% since 2013, to 55,975 t U as of 1 January 2015. Current levels of production satisfy about 99% of world reactor requirements [1, 2].
Future production of uranium resources is anticipated to be more than adequate to meet the high demand case for nuclear power generation through to 2035 if mine developments proceed as planned. However, several factors could impede the production of new uranium resources including significant capital investments, a paucity of technical expertise, geopolitical risk factors, government regulations, a relatively sparse network of production facilities, and weak uranium market prices in the face of rising mining costs. In the face of these challenges, the perception of robust resource estimates available for the industry can be scrutinized to understand if more precise measures are warranted [1, 2].
The distribution of the 2014 ‘Red Book’ uranium resources is presented in Fig. 2. The IAEA classifies resources into reasonably assured resources (RARs), inferred resources (IRs), prognosticated resources (PRs), and speculative resources (SRs), recoverable at various production cost categories. The RARs include economic, sub-economic, and uneconomic resources. The IRs include implied and unverified economic, sub-economic, and uneconomic resources. The PRs and SRs include inconsistently reported, dated, and unreliable information of limited utility. In the 2014 ‘Red Book’, some countries have declined to report on these categories given the level of uncertainty associated with these measures. In addition, the levels of uncertainty in resource estimates are not clearly described in the IAEA classification framework.
FIG. 2. Country-wise distribution of global uranium resources using data from the ‘Red Book’. Adapted
49 from [1].
The United Nations (UN) framework classification for mineral resources (UNFC-2009) is another framework for portraying mineral resources in a tri-axial format informed by geological knowledge, project feasibility, and socio-economic viability [4]. This framework offers an alternative way to understand uranium resources (Fig. 3). Economic deposits are characterized by robust ore reserves, sound mining economics, and acceptance from environmental safeguard and social license perspectives. When the IAEA classification scheme is mapped onto the UN scheme, the IAEA SRs and PRs fall in the high uncertainty realm. The IAEA has considered the merit of the application of this framework classification to nuclear fuel resources [5].
At a fundamental level, the exploration process involves the discovery of significant indications of uranium mineralization in the geosphere through the drill testing of geological, geochemical and geophysical anomalies defined by exploration experts. Follow-up drilling programs are used to define the grade of mineralization and physical dimensions of the deposit and to collect samples for geo-metallurgical studies. Based on the results of drilling programs, the grade and tonnage of the deposit can be defined with some degree of confidence, providing one of the most important indications of the economic potential of the deposit. With an increase in geological knowledge, one aspect of the risk associated with the economic viability of developing the deposit into a mine is reduced.
Reducing the economic uncertainty from a mining project feasibility, social license, and sustainable development perspective, is a complimentary objective to ore deposit definition.
Information on the establishment of uranium mining operations in the context of sustainable development can be found in [6].
Countries that have a significant amount of reasonably assured uranium resources are illustrated in Fig. 4. The 2014 “Red Book” indicates that Australia ceased to report resources at
<US$80/kg U pointing to a trend away from the lower cost production category previously reported. A significant portion of Australia’s resource base is drawn from by-product uranium resources indicated at the Olympic Dam copper deposit.
Global reasonably assured uranium resources by production method are illustrated in Fig. 5.
Open-pit mining, underground mining, and in-situ acid leach mining are leading methods. A future emphasis on the in-situ-recovery (ISR) method, as a lower cost mode of production for sandstone-hosted uranium deposits, is indicated. Methods of exploitation of different types of uranium deposits are described in [7].
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FIG. 3. United Nations framework classification for resources. Adapted from [3].
FIG. 4. Reasonably assured uranium resources by countries with significant resources. After [2].
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Global reasonably assured uranium resources by deposit type are illustrated in Fig. 6. The RARs are dominated by the sandstone-hosted and unconformity-related deposit types; with a large contribution from the Olympic Dam iron-oxide breccia type deposit. Sandstone-hosted deposits contribute the largest proportion of inferred resources [1]. Uranium deposit types are described by [8] and [9].An historical profile of the world uranium industry between 1965 and 2004 is presented in the ‘Red Book Retrospective’ report [10], which includes an assessment of uranium resources, exploration, and production. Data related to this publication were updated to include information from more recent ‘Red Book’ publications, up to and including the 2016 report (Figs 7–9).
FIG. 5. Reasonably assured uranium resources by production method. After [2].
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FIG. 6. Reasonably assured uranium resources by deposit type. After [2].
FIG. 7. Global uranium production (1945–2015).
53 FIG. 8. Global cumulative historical uranium production and historical cumulative reasonably assured resources (US$<130/kg U) 1970–2015.
Historical annual global production of uranium (1945-2016) reached a peak of ~70,000 t U around 1980, decreased to ~30,000 t U around 1995, and recovered to current levels of ~60,000 t U (Fig. 7).
The historical inventory of global recoverable reasonably assured uranium resources (< US$130 kg U) including the production of uranium is estimated to be 6,263,532 t U as of 2015 (Fig. 8).
The total historical global production of uranium is estimated to be 2,805,132 t U. This leaves an inventory of recoverable RAR (<US$130 kg U) available for production of 3,458,400 t U (2015). It is unlikely that all of these resources will be ultimately mined and that actual production levels will be lower. The extrapolation of statistics for Canadian and Australian uranium deposits (presented in Part 3) suggests that less than one half of these RARs will be converted to production (< 1,729,000 t U). This is equivalent to ~30 years of production from reasonably assured resources at a rate of ~60,000 t U/year.
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FIG. 9. Global uranium exploration expenditures and uranium price (constant 2017 dollars) 1970–
2015.
Annual global uranium exploration expenditures reached levels of over US$3 billion around 1976, declined to less than US$500 million during the 1990’s, recovered to around US$2 billion starting in 2007, and as of 2016 are in decline (Fig. 9). Levels are reported in constant 2017 dollars. Uranium exploration expenditure is sympathetic to the price of uranium. Total global uranium exploration expenditures from 1970-2015 are estimated to be US$53.5 billion (constant dollars). About 4,410,991 t U of RARs (< US$130/kg U) were added to the world inventory from 1970-2015 at an estimated cost of > US$12.13/kg U (equivalent to > US$4.66/lb U3O8).
A global uranium exploration learning curve for RARs (< US$130/kg U) was developed based upon updated data related to the ‘Red Book Retrospective’ to provide additional insight into the efficiency of the historical uranium exploration process (Fig. 10). A learning curve is a mathematical model that correlates learning with experience. Learning was defined as the cumulative identification of RAR (including historical production) and was correlated with experience (the effort to identify these resources) recorded as cumulative exploration expenditure. The data was plotted graphically and modeled as two logistic functions (learning curves) that map an exponential rise to a limit. The limit is of critical interest as it defines the maximum RAR that can be anticipated on each learning curve, given exploration expenditure.
For the global exploration learning curve, the shift from the first to the second learning curve is demarcated by an ‘innovation’ (Fig. 10). The ‘innovation’ is primarily attributed in the introduction of Russian resources and Kazakhstan ISR amenable resources to the ‘Red Book’
inventory in the mid-1990’s following the dissolution of the Soviet Union. For other cases presented in Part 4, ‘innovation’ can be attributed to the adoption of a new technology. Another disruptive ‘innovation’ will be required to take the industry to a third learning curve.
For the current interpretation the shift to the second global exploration learning curve is interpreted to demarcate the ISR dominant mining era from the conventional mining era.
Although the data is sparse, the limit of the second global learning curve is postulated to occur
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(conservatively) at around 7,000,000 t U. This estimate suggests that < 750,000 t U RAR is available for exploitation on the second learning curve given additional exploration expenditure. Incorporating this estimate into the overall analysis suggests that <35 years of production of RAR (< US$130/kg U) remains available for the industry assuming a RAR to production conversion rate of <50% and annual production of 60,000 t U.
FIG. 10. Global learning curve for reasonably assured resources (US$<130/kg U).
The preceding analysis represents a contrarian view, suggesting the possibility of a constraint on the availability of RARs (< US$130/kg U) for the nuclear industry in the mid-term. This constraint also points to the utility of ongoing investment in exploration and innovative technologies to ensure the availability of future RARs. More conventional logic accepts that higher cost RARs and IRs will be brought into production to mediate any potential production shortfall. Market conditions, relatively low conversion rates of existing RARs to production, the quality of resources (grade and tonnage), increasing long time frames to bring RARs into production, and the many social, political, environmental, and economic factors that constrain development point to many risk factors associated with resource development. The analysis of future ‘Red Book’ data should continue with the goal of developing a robust model of the second learning curve. The quantitative modeling of the probability of identifying RAR given future exploration effort (expenditure) is a goal.
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