XRFコアスキャンデータを用いた地層の統計的対比

Abstract

A method is developed to quantitatively correlate geological layers based on similarities in the shape of the statistical frequency distribution of a large volume of multi-element count data obtained with an X-ray fluorescence (XRF) core scanner. A distance measure between probability distributions called Jensen–Shannon divergence is adopted as a criterion for similarities in statistical distributions with the assumption of a Gaussian distribution. Using artificially created elemental count data, the flow of analysis and the effectiveness of the method for detecting the query layer of interest from the search target core dataset is demonstrated. By applying the system to geological samples, which were disturbed by the 2011 Tohoku-oki tsunami, located in Higashi Matsushima City, Miyagi Prefecture, the system is shown to appropriately correlate surface layer, Jogan-tsunami (A.D. 869) layer, and beach sediment layer, which indicates the effectiveness of the proposed system for obtaining a stratigraphic correlation of two cores. In the future, by developing the method to automatically determine layer boundaries, it will be possible to detect narrow event layers and to automatically correlate the stratigraphy. By applying it to many cores, the proposed method is useful for evaluating spatial distributions of tsunami deposits and wide-spread tephra layers, and it is expected to contribute to disaster prevention and mitigation.