Geophysics
We review previous approaches to nowcasting earthquakes and introduce new approaches based on deep learning using three distinct models based on recurrent neural networks and transformers. We discuss different choices for observables and…
The critical slip distance in rate and state model for fault friction in the study of potential earthquakes can vary wildly from micrometers to few meters depending on the length scale of the critically stressed fault. This makes it…
The wettability of the rock surface in porous media has an effect on the constitutive saturation functions that govern capillary pressure and relative permeability. The term wettability alteration refers to the change of this property over…
Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and can deal with a massive amount of data and images seamlessly. Geoscientists face…
For the past few centuries, the temporal variation in the Earth's magnetic field in the Pacific region has been anomalously low. The reason for this is tied to large scale flows in the liquid outer core near the core-mantle boundary, which…
Azimuthal accelerations of cylindrical surfaces co-axial with the rotation axis have been inferred to exist in Earth's fluid core on the basis of magnetic field observations and changes in the length-of-day. These accelerations have a…
The review is conceived to help the reader to interpret present geoneutrino results in the framework of Earth's energetics and composition. Starting from the comprehension of antineutrino production, propagation, and detection, the status…
The goal of a scientific investigation is to find answers to specific questions. In geosciences this is typically achieved by solving an inference or inverse problem and interpreting the solution. However, the answer obtained is often…
Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion…
We propose two methods to calibrate the parameters of the epidemic-type aftershock sequence (ETAS) model based on expectation maximization (EM) while accounting for temporal variation of catalog completeness. The first method allows for…
The dynamics of sliding friction is mainly governed by the frictional force. Previous studies have shown that the laboratory-scale friction is well described by an empirical law stated in terms of the slip velocity and the state variable.…
Intraplate volcanic islands are often considered as stable relief with constant vertical motion and used for relative sea-level curves reconstruction. This study shows that large landslides cause non-negligible isostatic adjustment. The…
Degassing of CO2 and precipitation of calcite to the surface of stalagmites can strongly impact isotope signals imprinted into the calcite of these speleothems. Here, we show that in all the variety of conditions occurring in nature only…
A novel deep learning technique called Physics Informed Neural Networks (PINNs) is adapted to study steady groundwater flow in unconfined aquifers. This technique utilizes information from underlying physics represented in the form of…
Inductive heating with high-voltage cables reduces the risk of hydrate formation by raising the temperature of the production fluid in pipelines. Heating the pipeline results in losing a certain fraction of the heat to the surrounding soil…
A large contrast in electrical conductivity has been observed within the lithospheric mantle between the Tanzanian craton and the Mozambique belt at depths > 70 km. Such contrasts are typically attributed to changes in volatiles and/or melt…
P- and S-wave decomposition is essential for imaging multi-component seismic data in elastic media. A data-driven workflow is proposed to obtain a set of spatial filters that are highly accurate and artifact-free in decomposing the P- and…
According to general relativity theory (GRT), the clock at a position with lower geopotential ticks slower than an identical one at a position with higher geopotential. Here, we provide a geopotential comparison using a non-transportable…
Although our existing one-dimensional (1D) model provides a successful quantitative description of rupture events, a 1D description is somewhat limited. We therefore derive a two-dimensional (2D) model which allows us to investigate…
Newtonian machine learning (NML) is a wave-equation inversion method that inverts single-dimensional latent space (LS) features of the seismic data for retrieving the subsurface background velocity model. The single-dimensional LS features…