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Research over the past few decades has shown that recent marine dinoflagellate cyst assemblages are strongly influenced by environmental factors, and statistical modelling of ecological signals (SMES) therefore has potential application for interpretation of fossil dinocysts in biostratigraphy. Towards this end a global database of recent cyst distributions from known environments has been developed using statistical methods that most accurately reflect and quantify the ecological signals expressed by the cysts. The first test is reported here of the application of SMES to industrial biostratigraphy using a palynology dataset from four wells along an onshore-offshore transect from the Norwegian North Sea provided by Statoil. The wells were part of a larger study on palaeoenvironments previously completed by Statoil on approximately 48 wells, where some of the traditional multivariate statistical methods had been tried but without success. The palaeoenvironment was thus partly understood, allowing the SMES method to be tested against a control.

Correspondence analysis on the dinocyst data from each well allowed the identification of the statistically most important species, and the relative positions of these species along the two most important axes suggested ecological trends (the coastal/oceanic being most dominant). Tracking these down-hole showed two major shifts in each well that could be correlated between all wells; the shifts corresponded to major flooding surfaces previously identified, and suggested orientation of the well sites relative to a palaeo-shoreline. This first test strongly suggests that these methods offer a much quicker, and more robust application for palaeoenvironmental interpretations from the dinocysts in biostratigraphic datasets.

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