Within the domain of image processing, a wide array of methodologies is dedicated to tasks
including denoising, enhancement, segmentation, feature extraction, and classification …

Significant uncertainties can be found in the modelling of geotechnical materials. This can
be attributed to the complex behaviour of soils and rocks amidst construction processes …

Computation of petrophysical properties on digital rock images is becoming important in
geoscience. However, it is usually complicated for natural heterogeneous porous media due …

Lithium-ion batteries (LIB) are inherently multiscale and multiphysics systems. Coarse-
grained models, which represent electrode components as overlap** continua, allow one …

The evaluation of rock porosity and the mercury injection capillary pressure (MICP) curve is
fundamental for oil and gas exploration and production. Digital rock (DR) technology …

Determining effective elastic properties of rocks from their pore-scale digital images is a key
goal of digital rock physics (DRP). Direct numerical simulation (DNS) of elastic behavior …

The lithology and rock-physical properties of tight sandstone reservoirs become increasingly
complex, resulting in a more challenging reservoir evaluation process. Conventional rock …

This study reviews 254 papers on artificial intelligence (AI) applications in the geoenergy
sector, categorized into conventional and future-oriented technologies. Conventional …

This research investigates the impact of data augmentation and noise injection on various
image filtering techniques employed for static image denoising and image recognition tasks …

Abstract This thesis examines Graph Neural Network-based methodologies for pore-scale
modelling and characterization of subsurface porous media, which is a vital aspect of …