Abstract
The issue of identifying stratigraphic units within a sedimentary succession is of prime importance for reservoir studies, because it allows splitting the reservoir into several units with specific parameters, thus reducing the vertical nonstationarity in simulations. A new method is proposed for semi-automatic determination of the sedimentary units from well logging that uses a customized geostatistical hierarchical clustering algorithm. A new linkage criteria derived from the Ward criteria (cluster minimum variance) is proposed to enforce the monotonic increase of dissimilarities. The discretized proportion of sand lithofacies calculated from the vertical proportion curve of the well is taken as input data. At each step of the procedure, the algorithm merges the most similar of two consecutive units of sand lithofacies, ensuring stratigraphic consistency. Finally, the number of units is deduced from the first most important step of the dissimilarity. The user can investigate a larger number of units by considering the clusters with lower levels of dissimilarities. The method is validated using two synthetic cases built for a fluvial meandering reservoir analog containing three and five units. The results from the synthetic cases show that the units are identified when the sand proportion contrast between units is larger than the internal variability within the units. For low sand contrasts between units or for a small number of wells, sedimentary unit limits may be found for lower clustering dissimilarities. Finally, the method is successfully applied to a field study, where the resulting cluster units are found to be comparable to the field interpretation, suggesting a limit between units defined by paleosols rather than close overlying lacustrine levels.
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Acknowledgements
This study is part of the first author’s Ph.D. thesis. The authors wish to thank Hélène Beucher for her valuable review. This method has been implemented as a well analysis tool in the Flumy® software within the scope of the Flumy Research Program. The authors are grateful to ENGIE (Neptune Energy) and ENI partners for support and fruitful discussions.
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Bubnova, A., Ors, F., Rivoirard, J. et al. Automatic Determination of Sedimentary Units from Well Data. Math Geosci 52, 213–231 (2020). https://doi.org/10.1007/s11004-019-09793-w
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DOI: https://doi.org/10.1007/s11004-019-09793-w