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A clustering approach applied to time-lapse ERT interpretation — Case study of Lascaux cave.

Authors :
Xu, Shan
Sirieix, Colette
Riss, Joëlle
Malaurent, Philippe
Source :
Journal of Applied Geophysics. Sep2017, Vol. 144, p115-124. 10p.
Publication Year :
2017

Abstract

The Lascaux cave, located in southwest France, is one of the most important prehistoric cave in the world that shows Paleolithic paintings. This study aims to characterize the structure of the weathered epikarst setting located above the cave using Time-Lapse Electrical Resistivity Tomography (ERT) combined with local hydrogeological and climatic environmental data. Twenty ERT profiles were carried out for two years and helped us to record the seasonal and spatial variations of the electrical resistivity of the hydraulic upstream area of the Lascaux cave. The 20 interpreted resistivity models were merged into a single synthetic model using a multidimensional statistical method (Hierarchical Agglomerative Clustering). The individual blocks from the synthetic model associated with a similar resistivity variability were gathered into 7 clusters. We combined the resistivity temporal variations with climatic and hydrogeological data to propose a geo-electrical model that relates to a conceptual geological model. We provide a geological interpretation for each cluster regarding epikarst features. The superficial clusters (no 1 & 2) are linked to effective rainfall and trees, probably a fractured limestone. Another two clusters (no 6 & 7) are linked to detrital formations (sand and clay respectively). The cluster 3 may correspond to a marly limestone that forms a non-permeable horizon. Finally, the electrical behavior of the last two clusters (no 4 & 5) is correlated with the variation of flow rate; they may be a privileged feed zone of the flow in the cave. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269851
Volume :
144
Database :
Academic Search Index
Journal :
Journal of Applied Geophysics
Publication Type :
Academic Journal
Accession number :
124491171
Full Text :
https://doi.org/10.1016/j.jappgeo.2017.07.006