Possibilities and Limitations of the Use of Seafloor Photographs for Estimating Polymetallic Nodule Resources—Case Study from IOM Area, Pacific Ocean

Importance of Spatial Autocorrelation in Machine Learning Modeling of Polymetallic Nodules, Model Uncertainty and Transferability at Local Scale

Machine learning spatial modeling is used for mapping the distribution of deep-sea polymetallic nodules (PMN). However, the presence and influence of spatial autocorrelation (SAC) have not been extensively studied. SAC can provide information regarding the variable selection before modeling, and it results in erroneous validation performance when ignored. ML models are also problematic when applied in areas far away from the initial training locations, especially if the (new) area to be predicted covers another feature space. Here, we study the spatial distribution of PMN in a geomorphologically heterogeneous area of the Peru Basin, where SAC of PMN exists. The local Moran’s I analysis showed that there are areas with a significantly higher or lower number of PMN, associated with different backscatter values, aspect orientation, and seafloor geomorphological characteristics. A quantile regression forests (QRF) model is used using three cross-validation (CV) techniques (random-, spatial-, and cluster-blocking). We used the recently proposed “Area of Applicability” method to quantify the geographical areas where feature space extrapolation occurs. The results show that QRF predicts well in morphologically similar areas, with spatial block cross-validation being the least unbiased method. Conversely, random-CV overestimates the prediction performance. Under new conditions, the model transferability is reduced even on local scales, highlighting the need for spatial model-based dissimilarity analysis and transferability assessment in new areas.

Exploration of Polymetallic Nodules and Resource Assessment: A Case Study from the German Contract Area in the Clarion-Clipperton Zone of the Tropical Northeast Pacific

In 2006, the BGR signed a contract with the International Seabed Authority (ISA) for the exploration of polymetallic nodules in the Clarion-Clipperton Zone of the northeast Pacific. During nine expeditions, in particular, “Area E1”, the eastern part of the contract area, with a size of ~60,000 km2, was explored in detail. Here, we outline BGR’s exploration methods and provide resource estimates for Area E1 and three sub-areas. The resource assessment is predominantly based on statistical analyses of data obtained by 12-kHz multibeam bathymetry and backscatter mapping, box core sampling and geochemical analysis of nodules. The main parameter for the assessment is the nodule abundance (kg/m2), as its coefficient of variation (CoV) over the entire eastern contract area is relatively high at 36%. In contrast, the metal contents of nodules show only minor variation, with a CoV of 8% for manganese and 8% for the sum of copper, nickel and cobalt. To estimate mineral resources for the entire Area E1, we used an artificial neural network approach with a multivariate statistical correlation between nodule abundance derived from box cores and hydro-acoustic data. The total estimated resources are 540 ± 189 million tonnes (Mt) of dry nodules, and the total estimated metal contents are 168 Mt of manganese, 7.5 Mt of nickel, 6.3 Mt of copper, 0.9 Mt of cobalt, 0.4 Mt of rare-earth elements and 0.3 Mt of molybdenum. A geostatistical resource estimate of three economically prospective areas with a total size of 4498 km2, intensively sampled by box cores, was carried out using ordinary kriging of nodule abundance and metal grades. Within these three nodule fields, 7.14 Mt of dry nodules are classified as measured mineral resources covering an area of 489 km2. Indicated mineral resources amount to 11.2 Mt, covering an area of 825 km2, and inferred mineral resources of 35.5 Mt of dry nodules were estimated for an area of 3184 km2. In total, the metal contents of the three prospective areas amount to 16.8 Mt of manganese, 0.74 Mt of nickel, 0.63 Mt of copper and 0.09 Mt of cobalt.

Comparative Study of MnO2 Dissolution from Black Copper Minerals and Manganese Nodules in an Acid Medium

The low grade of copper deposits and the use of the froth flotation process have caused excessive tailing production. In recent years, experts have looked for new alternative methods to improve this situation. Black copper minerals are abundant resources not exploited by large-scale copper mining and possess high Mn concentrations. On the other hand, manganese nodules are submarine resources and show high concentrations of Cu, Ni, Fe, and, mainly, Mn. However, both mineral resources are refractory to conventional leaching processes, and so a reducing agent is necessary for their treatment. We studied the use of tailings obtained from the flotation of foundry slags with a high content of Fe3O4 as reducing agents at different MnO2/tailings ratios and H2SO4 concentrations. Mn dissolution was compared in marine nodule and black copper minerals samples. It was found that higher Mn dissolutions are obtained from marine nodules, likely due to the acid consumption created by Cu dissolution from black copper minerals. The remnant elements in manganese nodules were leached under an oxidant condition.

Application of General Linear Models (GLM) to Assess Nodule Abundance Based on a Photographic Survey (Case Study from IOM Area, Pacific Ocean)

The success of the future exploitation of the Pacific polymetallic nodule deposits depends on an accurate estimation of their resources, especially in small batches, scheduled for extraction in the short term. The estimation based only on the results of direct seafloor sampling using box corers is burdened with a large error due to the long sampling interval and high variability of the nodule abundance. Therefore, estimations should take into account the results of bottom photograph analyses performed systematically and in large numbers along the course of a research vessel. For photographs taken at the direct sampling sites, the relationship linking the nodule abundance with the independent variables (the percentage of seafloor nodule coverage, the genetic types of nodules in the context of their fraction distribution, and the degree of sediment coverage of nodules) was determined using the general linear model (GLM). Compared to the estimates obtained with a simple linear model linking this parameter only with the seafloor nodule coverage, a significant decrease in the standard prediction error, from 4.2 to 2.5 kg/m2, was found. The use of the GLM for the assessment of nodule abundance in individual sites covered by bottom photographs, outside of direct sampling sites, should contribute to a significant increase in the accuracy of the estimation of nodule resources.

Quantitative Expression of the Burial Phenomenon of Deep Seafloor Manganese Nodules

Manganese (polymetallic) nodules on the deep seafloor in the open ocean have attracted great interest because of their economic potential. Visual data on nodules found on the deep seafloor such as photographs and videos have increased exponentially with the recent progress of related technologies. These data are expected to reflect useful information for estimating these mineral resources, as well as understanding their geological origin. Although the size, number, and coverage of manganese nodules have been measured in seafloor images, the burial of such nodules has not been sufficiently examined. This paper focuses on mathematical expression of the burial of the manganese nodules and attempts to quantitatively elucidate relations among burial degree and nodule geological parameters. The results, that is, a dataset obtained by calculations of relations among parameters, are also utilized for considerations of quantitative expression of burial. These considerations are expected to contribute to a better understanding of the geological origin of manganese nodules.

Aspects of Estimation and Reporting of Mineral Resources of Seabed Polymetallic Nodules: A Contemporaneous Case Study

Exploration of seabed polymetallic nodules identifies the Clarion Clipperton Zone and the Indian Ocean Nodule Field to be of economic interest. Mineral resource estimation is important to the owner of the resource (all of mankind; and managed by the International Seabed Authority; ISA) and to developers (commercial and government groups holding contracts with the ISA). The Committee for Mineral Reserves International Reporting Standards was developed for the land-based minerals industry and adapted in 2015 for ISA-managed nodules. Nodules can be sampled in a meaningful manner using mechanical devices, albeit with minor issues of bias. Grade and moisture content are measured using the established methodology for land-based minerals. Tonnage of resource is determined via the abundance of nodules in kilograms per square metre of seabed. This can be estimated from physical samples and, in some cases, from photographs. Contemporary resource reporting for nodules classify the level of confidence in the estimate, by considering deposit geology, sample geostatistics, etc. The reporting of estimates also addresses reasonable prospects for eventual economic extraction, including factors such as mining technology, the marine environment, metallurgical processing, and metals markets. Other requirements are qualified persons responsible for estimation and reporting, site inspection, and sample chain of custody.