A case study for data-driven soil-layer delineation

In the past, soil-layer delineation methods can usually only take a single type of input data, e.g., soil-type data at boreholes. However, this does not fit in the geotechnical engineering practice where multiple types of data are usually available during site investigation (e.g., borehole data and cone penetration test data are both available). This paper adopts a novel data-driven method for soil-layer delineation that accommodates multiple types of site investigation data. The basic idea is to include liquid limit (LL), plasticity index (PI), and fines content (FC) into the soil parameters of analysis. According to the Unified Soil Classification System (USCS), the information of (LL, PI, FC) can be used to determine whether the soil is sand, silt, or clay. As a result, the conditional random field simulation results for (LL, PI, FC) can be used to delineate sand, silt, and clay layers. If extra soil parameters (such as cone penetration test results) are incorporated, the novel method can accommodate multiple types of site investigation data. A real example of the Fucino Basin in Italy is adopted to demonstrate the application of the novel data-driven soil-delineation method.