Towards systematic probing for Milankovic cycles in borehole logging data and complex settings.

Cyclostratigraphy is an integral part of many scientific studies on the age and duration of outcrop- and core material from sedimentary geoarchives. Yet, borehole data are not systematically assessed using cyclostratigraphic methods. This has various reasons, including (a) a specific resolution and commonly no possibility to increase data resolution after logging, (b) logging proxy data cannot be connected to the sedimentary environment as easily as core investigations, (c) commonly cyclostratigraphic studies focus on one lithostratigraphical unit, but borehole logs may comprise several (d) some data generated from core material (e.g. stable isotope ratios) cannot be acquired in boreholes directly. Also some complex settings allow for different cyclostratigraphic interpretations.
To obtain a reliable understanding of (long) borehole logging datasets, and data from complex settings, a good understanding of the potential and specifics of relevant (time/depth) evolutive methods in cyclostratigraphy are an essential prerequisite. Therefore, we test a suite of evolutive cyclostratigraphic methods using several artificial datasets consisting of modelled Milankovic signals and noise. The principles of spectral moments, or other types of signal characterizations, can be used for initial assessment of signal properties over the entire record, and sometimes allow interpretations regarding sedimentation rate or changes in the climate system. Wavelet analysis and evolutive harmonic analysis (EHA) represent windowed approaches of assessing cyclicity, where wavelet analysis and evolutionary spectral analysis can also assess amplitude variations. Evolutive average spectral misfit (eASM) and evolutionary correlation coefficient analysis (eCOCO) assess the similarity of power spectra (eCOCO) and significant cyclic variations (ASM) in geological datasets against Milankovic targets, being conceptionally similar but technically different. The TimeOpt method investigates precession- and eccentricity amplitude modulations and aims at finding a best fit through assessing various sedimentation rates.
Aim of our work is the comparison of different evolutive cyclostratigraphic methods for an understanding of which methods perform good under specific conditions. Once artificial datasets are discussed, we apply these methods to rather well understood real data. A discussion of the possible issues and potential of especially uncommon methods gives insight in further potential of cyclostratigraphy.