In the framework of the Sustainable Development and Technologies project, this research focuses on employing an unsupervised learning approach to interpret well-log data, aiming to characterize the primary hydrostratigraphical units within the Quaternary aquifer system in the Debrecen area of Eastern Hungary. The study introduced a novel approach that bridges the traditional and data-driven machine learning approaches, which proved to be beneficial in characterizing heterogeneous aquifer systems, thereby facilitating successful groundwater resource development and management.
Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters
