Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer
[en] Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results.
Disciplines :
Geological, petroleum & mining engineering
Author, co-author :
Rogiers, Bart; Belgian Nuclear Research Centre (SCK•CEN), Mol, Belgium > Health and Safety > Institute for Environment
Mallants, Dirk; CSIRO Land and Water, Glen Osmond, South Australia, Australia
Batelaan, Okke; Flinders University, Adelaide, South Australia, Australia > School of the Environment
Gedeon, Matej; Belgian Nuclear Research Centre (SCK•CEN), Mol, Belgium > Health and Safety > Institute for Environment
Huysmans, Marijke; Vrije Universiteit Brussel - VUB > Dept. of Hydrology and Hydraulic Engineering
Dassargues, Alain ; Université de Liège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement
Language :
English
Title :
Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer
Publication date :
03 May 2017
Journal title :
PLoS ONE
eISSN :
1932-6203
Publisher :
Public Library of Science, San Franscisco, United States - California
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