High-resolution subsurface marine mapping tools, including chirp and 3D seismic, enable the reconstruction of ancient landscapes that have been buried and subsequently submerged by marine transgression. However, the established methods for paleotopographic reconstruction require time consuming field and data interpretation efforts. Here we present a novel methodology using machine learning to e…
Accurately modeling highly heterogenous aquifers is one of the big challenges in hydrogeology. There is a pressing need to develop new methods that transform high-resolution data into hydrogeological parameters representative of such aquifers. We use random forest-based machine learning to predict the distribution of hydrostratigraphic units and hydraulic conductivity (K) at a regional scale. W…
The delineating of bedrock from sediment is one of the most important phases in the fundamental process of regional bedrock identification and mapping, and it is usually manually performed using high-resolution optical remote-sensing images or Light Detection and Ranging (LiDAR) data. This task, although straightforward, is time consuming and requires extensive and specialized labor. We contrib…
We propose a workflow for updating 3D geological meshed models to test different layering scenarios and to assess their impact on the simulation of injection. This workflow operates on a tetrahedral mesh that encodes rock unit information as well as rock physical properties. The alternative layering meshes are built by modifying the input mesh and inserting a new horizon defined by a scalar …
Previously glaciated landscapes often share similar surficial characteristics, including large areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These materials play significant roles in geologic and hydrologic resources, geohazards, and landscape evolution; however, the vast extents of many previously glaciated landscapes have rendered comprehensive, detailed f…
Carbonate rocks are known for their high heterogeneity and textural and compositional complexity. Evaluating their petrophysical properties is thus challenging, especially with limited information. One way to obtain an internal image of such rocks is to scan them with X-ray computed tomography scanners, revealing their internal structures. The problem with this approach is the trade-off between…
Geological modeling commonly results in a single prescribed geometric representation of the subsurface with no consideration of uncertainties. Accounting for uncertainties is of particular importance in the triangle zone at the leading edge of deformation of the foreland fold-thrust belt of the European Alps, the Subalpine Molasse. Here, interpretations of the complex structures are limited to …
Enhanced Oil Recovery (EOR) is as a key tertiary recovery strategy that aims at enhancing the oil recovery from the earth's subsurface of existing oilfields. One such EOR process that is dependent on multiple variables of complex surface interactions between the formation brine, injected brine, hydrocarbon and rock surface is different composition water flood. This specific EOR technique has be…
Rock type classification is one of the most crucial steps of geological and geotechnical core logging. In conventional core logging, rock type classification is subjective and time-consuming. This study aims to automate rock type classification using Machine Learning (ML). About 35 m of core samples from five different rock types obtained from an open pit mine were logged using a Multi-Sensor C…
Rock glaciers (RG) are landforms that occur in high latitudes or elevations and — in their active state — consist of a mixture of rock debris and ice. Despite serving as a form of groundwater storage, they are an indicator for the occurrence of (former) permafrost and therefore carry significance in the research for the ongoing climate change. For these reasons, the past years have shown ri…