Predictive Mapping of the Nodule Abundance and Mineral Resource Estimation in the Clarion-Clipperton Zone Using Artificial Neural Networks and Classical Geostatistical Methods

Knobloch, Andreas; Kühn, Thomas; Rühlemann, Carsten; Hertwig, Thomas; Zeissler, Karl-Otto; Noack, Silke

doi:10.1007/978-3-319-52557-0_6

Cited by 16 publications

(20 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This historically oldest and simplest version of kriging methodology was considered as sufficiently accurate at the current stage of the research. The Matheron's geostatistical methods have already been successfully used many times to: (i) model the spatial variability of PN abundance, (ii) construct the contour maps, and/or (iii) estimate the quantities of PN resources (see e.g., [4,15,18,[32][33][34][35][36][37]).…”

Section: Methodsmentioning

confidence: 99%

Estimation Accuracy and Classification of Polymetallic Nodule Resources Based on Classical Sampling Supported by Seafloor Photography (Pacific Ocean, Clarion-Clipperton Fracture Zone, IOM Area)

Mucha

Wasilewska-Błaszczyk

2020

Minerals

View full text Add to dashboard Cite

The amount and accuracy of nodule resources estimation in the Pacific Ocean are among the main factors conditioning the future exploitation. The estimates are based on the results of classical, direct seafloor sampling. Due to the large distance between sampling sites, the accuracy of assessing nodule resources in small parts of the deposit is low. The accuracy can be increased by using a large number of seafloor photographs taken along the route of the research vessel performing classic sampling. The study conducted for a part of the area administered by Interoceanmetal Joint Organization (IOM) included: (i) determining a model of the relationship between nodule abundance and seafloor nodule coverage using statistical methods, (ii) assessing the accuracy of nodule resources estimation using a geostatistical kriging procedure, (iii) proposing a preliminary classification of resources referring to International Seabed Authority (ISA) classification standards as material for further discussion. It was found that achievement of high accuracy in the estimation of nodule resources (with relative standard error <5%) in blocks planned for annual exploitation based on direct sampling is difficult. While the use of seafloor photographs increases the accuracy of estimating nodule resources, this improvement is not radical due to the unfavorable, preferential arrangement of photographic data.

show abstract

Section: Methodsmentioning

confidence: 99%

Estimation Accuracy and Classification of Polymetallic Nodule Resources Based on Classical Sampling Supported by Seafloor Photography (Pacific Ocean, Clarion-Clipperton Fracture Zone, IOM Area)

Mucha

Wasilewska-Błaszczyk

2020

Minerals

View full text Add to dashboard Cite

show abstract

“…1 Clarion-Clipperton fracture zones (FZs) bordering the area where most of the ISA exploration areas for SMnN are located. The white area indicates the eastern German license area, within which the case study area of this paper is located entire E1 area is less than 10% compared to the CoVof nodule abundance which is > 30% (Knobloch et al 2017). …”

Section: Characteristics Of the Smnn Case Study Areamentioning

confidence: 99%

“…Recent studies consider grade, nodule abundance, and hydro-acoustic backscatter data in conjunction with slope angles to tag prospective SMnN fields (Volkmann and Lehnen 2017;Knobloch et al 2017;Mucha and Wasilewska-Blaszczyk 2013). Relating thereto, a method for identifying the areas of (potential) commercial interest is proposed here, which-in addition to the existing approaches-takes into account the economic value of SMnN.…”

Section: Development Of a Valuation Technique For Smnn Depositsmentioning

confidence: 99%

“…(4) The distribution of nodule abundance per square meter in the case study area (Fig. 1) was modeled based on the neural network approach by Knobloch et al (2017), who used bathymetry and backscatter data of the seafloor and several derived datasets as input data. Based on known nodule abundance at box corer sites, the neural network was trained to find patterns in the input data which correlate with the nodule abundance from box corers.…”

Section: Mapping the Seafloor's Cash Valuementioning

confidence: 99%

“…Based on known nodule abundance at box corer sites, the neural network was trained to find patterns in the input data which correlate with the nodule abundance from box corers. It could be proven that such patterns exist and, thus, it was possible to predict the nodule abundance at all sites where hydro-acoustic data are available (Knobloch et al 2017). Therefore, nodule abundance values in the study area were available with a resolution of about 100 m, leading to the application of raster data with pixel sizes of about 100 m by 100 m with one nodule abundance value per pixel (Fig.…”

Section: Mapping the Seafloor's Cash Valuementioning

confidence: 99%

See 2 more Smart Citations

A comprehensive approach for a techno-economic assessment of nodule mining in the deep sea

2018

Self Cite

View full text Add to dashboard Cite

Mine planning of land-based mineral deposits follows well-established methods. The deep sea is currently under exploration, but mine planning approaches are still lacking. A spatial planning tool to assess the techno-economic requirements and implications of manganese nodule mining on deep-sea deposits is proposed in this paper. The comprehensive approach has been validated using research findings of the Blue Mining project, which received funding from the European Commission. A part of the German exploration area E1, located in the Clarion-Clipperton Fracture Zone, Pacific Ocean, serves as a case study area. The approach contributes to a responsible utilization of mineral resources in the deep sea, considering geological, economic and financial as well as technical and operational aspects. The approach may also be applicable for an early-stage assessment of other projects related to spatially distributed mineral resources, e.g., marine phosphate nodules. Furthermore, it could also be helpful for the investigation of the environmental impacts of seafloor manganese nodule mining.

show abstract

Application of Soft Data in Nodule Resource Estimation

Ellefmo

Kühn

2020

Nat Resour Res

Self Cite

View full text Add to dashboard Cite

Minerals and metals are of uttermost importance in our society, and mineral resources on and beneath the deep ocean floor represent a huge potential. Deciding whether mining from the deep ocean floor is financially, environmentally and technologically feasible requires information. Due to great depths and harsh conditions, this information is expensive and time and resource consuming to obtain. It is therefore important to use every piece of data in an optimum way. In this study, data retrieved from images and expert knowledge were used to estimate minimum and maximum nodule abundances at image locations from an area in the Clarion-Clipperton-Zone of the equatorial North East Pacific. From the minimum and maximum values, box cores and the spatial correlation quantified through variogram, a conditional expectation and associated uncertainty were obtained through the Gibbs sampler. The conditional expectation and the uncertainty were used with the assumed certain abundance data from the box cores in a kriging exercise to obtain better informed estimates of the block by block abundance. The quality assessment of the estimations was done based on distance criterion and on kriging quality indicators like the slope of regression and the weight of the mean. From the original image locations, alternative image configurations were tested, and it was shown that such alternatives produce better estimates, without extra costs. Future improvements will focus on improving the estimation of the minimum and the maximum values at image locations.

show abstract

Predictive Mapping of the Nodule Abundance and Mineral Resource Estimation in the Clarion-Clipperton Zone Using Artificial Neural Networks and Classical Geostatistical Methods

Cited by 16 publications

References 8 publications

Estimation Accuracy and Classification of Polymetallic Nodule Resources Based on Classical Sampling Supported by Seafloor Photography (Pacific Ocean, Clarion-Clipperton Fracture Zone, IOM Area)

Estimation Accuracy and Classification of Polymetallic Nodule Resources Based on Classical Sampling Supported by Seafloor Photography (Pacific Ocean, Clarion-Clipperton Fracture Zone, IOM Area)

A comprehensive approach for a techno-economic assessment of nodule mining in the deep sea

Application of Soft Data in Nodule Resource Estimation

Contact Info

Product

Resources

About