@misc{bcker2000cddl, author={Christian J {B\"{u}cker}}, title={{Core derived downhole logs for holes CRP-2 and CRP-2A}}, year={2000}, doi={10.1594/PANGAEA.57235}, url={https://doi.org/10.1594/PANGAEA.57235}, note={Supplement to: B\"{u}cker, Christian J; Jarrard, Richard D; Wonik, Thomas; Brink, Jason (2000): Analysis of downhole logging data from CRP-2/2A, Victoria Land Basin, Antarctica: a multivariate statistical approach. Terra Antartica, 7(3), 299-310, hdl:10013/epic.28289.d001}, abstract={In the northern McMurdo Sound (Ross Sea, Antarctica), the CRP-2/2A drillhole targeted the western margin of the Victoria Land Basin to investigate Neogene to Palaeogene climatic and tectonic history by obtaining continuous core and downhole logs. Well logging of CRP-2/2A has provided a complete and comprehensive dataset of in situ geophysical measurements. This paper describes the evaluation and interpretation of the downhole logging data using multivariate statistical methods. Two major types of multivariate statistical methods were each yielding a different perspective: (1) Factor analysis was used as an objective tool for classification of the drilled sequence based on physical and chemical properties. The factor logs are mirroring the basic geological controls (i.e., grain size, porosity, clay mineralogy) behind the measured geophysical properties, thereby making them easier to interpret geologically. (2) Cluster analysis of the logs groups similar downhole geophysical properties into one cluster, delineating individual logging or sedimentological units. These objectively and independently defined units, or statistical electrofacies, are helpful in differentiating lithological and sedimentological characterisations (e.g. grain size, provenance). The multivariate statistical methods of factor and cluster analysis proved to be powerful tools for fast, reliable, and objective characterisation of downhole geophysical properties at CRP-2/2A, resulting in interpretations which are consistent with sedimentological findings.}, type={data set}, publisher={PANGAEA} }