The Earth below ground is the subject of interest for many geophysical as well as geological
investigations. Even though most practitioners would agree that all available information …

Abstract Three-dimensional (3D) geological modeling from limited and scattered information
is essential for engineering geological investigation and design. Previous studies have …

We propose a novel approach to link solute transport behavior to the physical heterogeneity
of the aquifer, which we fully characterize with two measurable parameters: the variance of …

This paper presents the results of a research project which investigated permeability
prediction for the Precipice Sandstone of the Surat Basin. Machine learning techniques were …

Abstract Study region The Milan metropolitan area lies on one of the most important aquifer
in Italy, heavily exploited for public and industrial water supply. The area, covering 3135 km …

Stratigraphy and facies analysis in a mining waste domain such as in tailings storage
facilities (TSFs) is still a complex task due to sparsely distributed field data. Geophysical …

The Chennai aquifer system, which occupies an area of 6629 km2, is one of the most
stressed aquifer systems in southern India and is under severe threat of over exploitation …

Uncertain or indirect “soft” data, such as geologic interpretation, driller's logs, geophysical
logs or imaging, offer potential constraints or “soft conditioning” to stochastic models of …

This research proposes an innovative approach utilizing geophysical well logging data
analyzed with multiple machine learning (ML) methods including, self-organizing maps …

The study proposes a stochastic approach to quantify the uncertainty of groundwater
vulnerability (GV) produced by classical index-overlay methods. In the analysis, the physical …