Application of multivariate geostatistics for local-scale lithological mapping – case study of pelagic surface sediments from the Clarion-Clipperton Fracture Zone, north-eastern equatorial Pacific (Interoceanmetal claim area). (June 2020)

• Record Type: Journal Article
• Authors: Maciąg, Łukasz; Harff, Jan
• Is Part Of: Computers & geosciences. Volume 139(2020)
• Publication Date: 2020-06
• Subjects: Classification probability kriging -- Multivariate geostatistics -- Regionalized classification -- Geological mapping -- Pelagic sediments -- Clarion-Clipperton Fracture Zone (CCFZ); Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2020.104474
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: Multivariate geostatistical methods were employed to describe the local facies of surface pelagic sediments from the Interoceanmetal IOM H11 and H22 perspective areas. Using these methods, we analyze spatial variability in seafloor features, sediment grain size, and mineralogical and geochemical composition. The data were acquired from the seafloor sediments sampled by box corer. Laboratory methods included laser grain size analysis, X-Ray diffractometry and Inducted Coupled Plasma Mass Spectrometry. Universal kriging was applied in order to generate lithofacies maps, following the "classification probability kriging" concept based on a Bayesian theorem. Under this concept, the class membership probabilities are regarded regionalized variables, so that methodical tool of geostatistics can be applied. The final result is a series of thematic maps, showing the spatial distribution of classified sediments facies, expressed by class membership probabilities, which provide information on reliability of mapping. The applied models can be useful for geological exploration of Clarion-Clipperton polymetallic nodules deposit and beyond. The lithofacies maps presented here provide information on formation processes of sediments, induced by several factors, such as diagenetic transformation of sediments and pathways of biogenic, hydrogenous or hydrothermal material. Graphical abstract: Image 1 Highlights: Multivariate regionalized classification for mapping of marine deep-sea sediments. "Class membership probability kriging" applied for construction of lithofacies maps. Classified sediments facies maps expressed by class membership probabilities.