Understanding the geological and geotechnical characteristics of the shallow subsurface is crucial for engineering decisions in densely populated regions like the Netherlands. Urban areas are for a large part built on a complex stack of sand, clay, silt, gravel and organics that were deposited over the last hundreds of thousands of years under gradually subsiding tectonic conditions. One of these units, a fluvially deposited sand known as the Kreftenheye Formation, is widespread across the western part of the country and is vital for foundation design and groundwater dynamics. The Kreftenheye Formation is therefore well described by geotechnical and geological tests, yet integrating both types of data has rarely been done on a nationwide scale.

This paper focuses on 76 pairs of Cone Penetration Tests and boreholes that include Kreftenheye, out of a full database of nearly 200 pairs from TNO - Geological Survey of the Netherlands, generally reaching depths up to 40 meters. The study reveals significant spatial variations and depositional patterns within the Kreftenheye Formation, illustrating how overlying or interlayered flood plain or soft channel lag sediments influences the response of the CPT. Furthermore, CPT response and borehole samples have helped with making geological distinctions between the upper, Weichselian part of the Kreftenheye Formation and the lower Saalian part, showing how integrating both datasets can give both geological and geotechnical insights.@en

Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability simulated with a basin-scale advection-diffusion SFM to a data-rich real-world setting, i.e. the Holocene Rhine-Meuse fluvio-deltaic system in the Netherlands. SFM model calibration to real-world data in general has proven non-trivial. This study focuses on a novel inversion process constrained by the top surface and the sand proportion observed at specific pseudo-wells in the study area. Goodness-of-fit expressed by a new fitness function gives the error calculated as the average of two calibration constraints. Computational efficiency was increased significantly by implementing a new optimization process in two hierarchical steps: a) optimization in terms of sediment load and discharge, which are the most influential parameters having the largest uncertainty and b) optimization with respect to the remaining uncertain parameters, these being sediment transport parameters. The calibration process described allows for the most optimal combination of achieving acceptable levels of goodness-of-fit, feasible runtimes and multiple (non-unique) solutions to obtain synthetic stratigraphic output best matching real-world datasets. By removing model realizations which are geologically unrealistic, calibrated SFM models provide a multiscale stratigraphic framework for reconstructing static models of reservoirs which are consistent with the palaeogeographic layout, basin-fill history and external drivers (e.g. sea level, sediment supply). The static reservoir models that are matched with highest certainty therefore contain the highest geological realism and may be used to improve deep subsurface reservoir or aquifer property prediction. The new methodology was applied to the well-established Holocene Rhine-Meuse dataset, which allows a rigorous testing of the optimization; the calibrated SFM allows investigation of controls of the Holocene development on the sedimentary system.

@en