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Journal Article

Downhole logging data for time series analysis and cyclostratigraphy

Authors

Zeeden,  Christian
External Organizations;

Ulfers,  Arne
External Organizations;

/persons/resource/pierdo

Pierdominici,  S.
4.2 Geomechanics and Scientific Drilling, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Abadi,  Mehrdad Sardar
External Organizations;

Vinnepand,  Mathias
External Organizations;

Grelle,  Thomas
External Organizations;

Hesse,  Katja
External Organizations;

Leu,  Katharina
External Organizations;

Wonik,  Thomas
External Organizations;

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Citation

Zeeden, C., Ulfers, A., Pierdominici, S., Abadi, M. S., Vinnepand, M., Grelle, T., Hesse, K., Leu, K., Wonik, T. (2023): Downhole logging data for time series analysis and cyclostratigraphy. - Earth-Science Reviews, 241, 104436.
https://doi.org/10.1016/j.earscirev.2023.104436


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017507
Abstract
Numerous borehole logging datasets gathered for commercial and scientific purposes are available around the globe. However, studies valorising the chronostratigraphic potential of these datasets through time series analyses remain sparse despite the excellent completeness of downhole logging data retrieved in a fast and high-resolution fashion. The major reason for this is the complexity of such approaches and potential pitfalls that may discourage non-experienced users. Here we provide an overview that summarizes the most relevant properties of borehole logging measurements for time series analysis and cyclostratigraphy. Further, we provide a brief introduction of most relevant time series analyses methods, including several examples of borehole logging cyclostratigraphy. Compared to analyses and interpretations of data from cores or exposures, it is important to be aware of borehole logging data specific pitfalls. These include environmental corrections like the effect of variation in borehole diameter, the effects of drilling fluids, and that presented logs may consist of merged results logged in several depth sections.