Solute artificial neural network geothermometers offer the possibility to overcome the complexity given by the solute-mineral composition. Herein, we present a new concept, trained from high-quality hydrochemical data and verified by in-situ temperature measurements with a total of 208 data pairs of geochemical input parameters (Na+, K+, Ca2+, Mg2+, Cl−, SiO2, and pH) and reservoir temperatur…
High-resolution digital rock micro-CT images captured from a wide field of view are essential for various geosystem engineering and geoscience applications. However, the resolution of these images is often constrained by the capabilities of scanners. To overcome this limitation and achieve superior image quality, advanced deep learning techniques have been used. This study compares four differe…
Geological 3-D models are very useful tools to predict subsurface properties. However, they are always subject to uncertainties, starting from the primary data. To ensure the reliability of the model outputs and, thus, to support the decision-making process, the incorporation and quantification of uncertainties have to be integrated into the geo-modeling strategies. Among all modeling approache…
Lacustrine shale reservoirs present intricate attributes such as the prevalence of lamination, rapid sedimentary phase transitions, and pronounced heterogeneity. These factors introduce substantial challenges in analyzing and comprehending reservoir characteristics. Thin-section imaging offers a direct medium to observe these traits, yet the intrinsic compromise between image resolution and fie…
The Revell batholith is located within the Western Wabigoon terrane of the Superior Province, Northwestern Ontario, Canada, and is a potential site for a deep geological repository (DGR). This batholith is considered to have favourable geoscientific characteristics for hosting a DGR, including a sufficient volume of relatively homogenous rock. The subsurface geometry of the batholith plays an i…
The Tikhonov regularization parameter is a key parameter controlling the smoothness degree and oscillations of a regularized unknown solution. Usual methods to determine a proper parameter (L-curve or the discrepancy principle, for example) are not readily applicable to the evaluation of regularized derivatives, since this formulation does not make explicit a set of model parameters that are ne…
3D geologic modeling and mapping often relies on gravity modeling to identify key geologic structures, such as basin depth, fault offset, or fault dip. Such gravity models generally assume either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments, with average densities typically derived from surface and drill-hole sampling. The noise contributed …
Recently, workflow management platforms are gaining more attention in the artificial intelligence (AI) community. Traditionally, researchers self-managed their workflows in a manual and tedious way that heavily relies on their memory. Due to the complexity and unpredictability of AI models, they often struggled to track and manage all the data, steps, and history of the workflow. AI workflows a…
Plurigaussian simulation is widely used to model geological facies in geosciences and is predominantly applied in mineral deposits and petroleum reservoirs exploration. GeoSim package builds geostatistical models of categorical regionalized variables via conditional or unconditional Plurigaussian simulation and co-simulation. Co-simulation between Gaussian Random Fields representing the geologi…
Elucidating the tectonic setting of unknown rock samples has long attracted the interest of not only igneous petrologists but also a wide range of geoscientists. Recently, attempts have been made to use machine learning to discriminate the tectonic setting of igneous rocks. However, few studies have designed methods that are applicable to altered rocks. This study proposes a novel approach that…