SummaryAn innovative method is presented for full 3D pressure and temperature dominated stress evaluations in the subsurface using tetrahedra-based analytical elements combined with the inflation point source solution. A mesh-free approach suitable to industry standard 3D flow simulation models (based on hexahedral cells) is obtained by representing the grid cells in tetrahedral elements, effectively preserving the 3D geometrical complexities of the reservoir. Contributions from neighboring grid cells are added via a Tartan grid representation of point sources that enables the spatial resolution to increase and the stress evaluations to be carried out in parallel, both of which significantly improve computational efficiency. The novel approach is demonstrated for synthetic low enthalpy geothermal models with clastic reservoir characteristics and varying degrees of geometrical and structural complexity. The method is shown able to accurately capture the effects of stress arching on complex faults causing reservoir throw and flow compartmentalization, and along the rim of the cold-water volume. Results of a synthetic geothermal development model of the heavily faulted Gullfaks field show the novel method to provide an accurate and computationally highly efficient approach for evaluating pressure and temperature dominated stress changes in structurally complex sedimentary reservoirs.
SummaryPore-water pressure and clay content have influence on porosity and bonding/cementing the grain boundaries, thus affecting elastic properties, strength, and other physical properties of rocks. Similar processes take place in cementitious materials, where in particular hydration plays crucial role. This process leads to changes in pore water composition, specific surface area (or alternatively Cation Exchange Capacity, CEC), and water content. Analytical expressions can be obtained between both the CEC and porosity and a hydration state variable. The hydration state variable can be in turn related to the hydration time. These phenomena can be assessed by geoelectrical methods, which have been used for a long time to observe the evolution of the textural properties and rheology of rocks, as well as of cementitious materials. However, such use has been so far rather qualitative. The aim of this study is to better describe the evolution of complex conductivity spectra (induced polarization) in relation to the hydration, using the recently developed dynamic Stern layer model to the hydration time through Powers model. Comparisons between the model predictions and literature data are used to test the suitability of the proposed solution. The model is verified using monitoring experiments of the complex conductivity spectra of several cements to study the evolution of both the in-phase and quadrature conductivity versus the hydration time. Although the current method is still semi-empirical, it makes it possible to analyze and understand the evolution of complex conductivity spectra of geomaterials and technogenic cementitious materials with a wide variety of geophysical applications in civil engineering, especially for dams and underground civil constructions.
SummaryWe have developed a physics-guided deep learning framework for geophysical inversion that incorporates Markov chain Monte Carlo (MCMC) sampling to assess the uncertainty associated with model parameters of interest. To enhance computational efficiency, a statistical sampling method is utilized to reduce the number of samples required while ensuring the training data remain both diverse and informative. As the inversion progresses iteratively, the training dataset is dynamically expanded using outputs from the stochastic sampler along with their corresponding forward responses. A supervised deep learning model is utilized, in which the Jensen-Shannon divergence is adopted as the loss function, and a Gaussian assumption is applied for analytical computation. We test the workflow on a seismic velocity model inversion, and successfully capture the geological features and velocity distributions, with results that closely match the reference model. Compared to the MCMC sampler applied to the whole data cube, the proposed workflow is more computationally efficient, as a small fraction of data is chosen using the active learning paradigm. This workflow is strongly generalizable and effective, making it suitable for a wide range of other inversion applications as well.
Carbon sequestration, climate regulation, biodiversity support and shoreline protection: These are all benefits provided by tidal wetlands. As the climate changes, the amount of carbon captured by these vital ecosystems may be changing as well.
Researchers have long known that there is an asymmetry in the El Niño-Southern Oscillation (ENSO), the confluence of wind and water currents that creates warm El Niño events and cooler La Niña events. Large-scale climate models tend to underrepresent this asymmetry for reasons that are still not fully understood. Better modeling of the mechanisms that make El Niño events warmer could both provide insight into Earth's climate system and improve future ENSO predictions.
Water flowing from hot springs near volcanoes often contains a mixture of meteoric water that has percolated underground and a deeper component known as magmatic water. Researchers at the University of Tsukuba used numerical simulations and isotopic data to show that magmatic water in hot springs and volcanic gases around Kussharo Caldera, Hokkaido, originates from the subducting Pacific Plate, which descends from the Kuril Trench to a depth of 125 kilometers (78 miles). The paper is published in the Journal of Volcanology and Geothermal Research.
For U.S. coastal residents, storm surge is among the deadliest hurricane hazards, causing catastrophic property damage and loss of life, and scientists expect tropical storms to grow more intense. During Hurricane Ian in 2022, storm surge accounted for 41 of the 66 direct deaths. The 2026 Atlantic hurricane season is now underway, and while NOAA expects below-normal activity, emergency managers caution that it only takes one storm to devastate a community.
In November 2025, a study led by Adrien Wehrlé, a researcher in the Department of Geography at the University of Zürich, Switzerland, looked at the massive calving response of one of West Greenland's active glaciers, Sermeq Kujalleq in the Kangia icefjord (SKK), to the drainage of two surface lakes. Called supraglacial lakes, these are temporary meltwater ponds that form and accumulate in depressions or holes on the surface of glaciers and ice sheets.
Geologists studying some of the planet's oldest volcanic rocks have uncovered new evidence that water was playing a major role in shaping Earth's interior and driving volcanic activity more than 3 billion years ago.
Tyler Spano's impact on the field of mineralogy is anything but small. So when a newly discovered mineral, modest in size but significant in meaning, was named spanoite in her honor, it became a fitting tribute to her contributions to the field.
Researchers at University of Tsukuba analyzed high-resolution topographic data from airborne LiDAR to examine the relationships among landslide area, depth, and slope gradient.
SummaryThe origin of seismic discontinuities in the Earth’s mid-mantle (∼700–1400 km) remains debated, with competing hypotheses attributing them to either partial melting due to water transport across the transition zone or compositional heterogeneities (subducted crust). Distinguishing between these scenarios has been hindered by the inability of standard imaging techniques to extract robustly the polarity of weak seismic reflections amidst noise and reverberations that contaminate mid-mantle reflections. Here, we introduce a novel signal processing framework that combines curvelet-based wavefield separation with extended multitaper deconvolution to resolve this polarity ambiguity. We validate this approach by applying it to a high-quality dataset of SS and PP precursors beneath the Central Pacific. This application yields the robust detection of a discontinuity at approximately 800 km depth, characterized by a sharp positive shear velocity contrast (δVS ≈ +4 − 5%) and a negligible density contrast. The observed positive polarity precludes partial melt or thermal plumes as primary causal mechanisms. Instead, the high-velocity, neutral-density signature is consistent with a layer of stagnant, subducted oceanic crust in thermal equilibration with the ambient mantle. These results demonstrate the efficacy of the deconvolution framework and provide direct seismic evidence for compositional stratification in the mid-mantle, supporting geodynamic models where viscosity increases facilitate the long-term preservation of recycled lithosphere.
SummaryGeodetic observations, such as GNSS and InSAR, are increasingly used to investigate co-seismic surface deformation. Efficiently and simultaneously resolving fault geometry and slip distribution from surface displacements is essential for understanding earthquake processes, accurately estimating seismic magnitude and comprehensively assessing seismic hazard. Current mainstream approaches typically rely on Bayesian inference, such as Monte Carlo sampling. However, these methods typically suffer from long burn-in periods, low computational efficiency, strong sensitivity to initial parameter values and step sizes. Given these limitations, conventional approaches may yield suboptimal fits for the observations. To overcome these limitations, we propose and develop a novel Tree-structured Bayesian Optimization method (TBO), integrated with Helmert Variance Component Estimation (HVCE), to jointly determine fault geometry and slip distribution. To rigorously assess the feasibility and reliability of the proposed approach, we test it using both synthetic and real earthquake data. In the synthetic tests, we evaluate its robustness under a variety of conditions, including different fault types, varying types and densities of geodetic observations, diverse sub-fault sizes and asperities, and complex multi-fault scenarios. Four sets of synthetic experiments are designed, and the results conclusively demonstrate that the proposed method achieves stable and reliable performance in inverting fault geometry and slip distribution. Furthermore, comparative analysis with existing methodologies shows that our approach yields substantially improved computational efficiency, significantly reduced sensitivity to initial conditions, and smaller misfits to observations. Finally, we apply the method to the 2021 Mw 6.4 Yangbi earthquake in Yunnan, China. The retrieved fault geometry and slip distribution successfully explain the fault kinematics and the observed surface deformation field, thereby confirming the applicability and robustness of the method for real earthquake event analysis.
East Antarctica hosts the largest ice sheet on Earth, containing enough water to raise global sea levels by 52 meters (171 feet) were it to fully melt. Yet scientists have been puzzled for decades about how and why this ice sheet formed.
In May 2018, the island of Mayotte, between Madagascar and Mozambique, began to experience a series of earthquakes that led to the discovery of an underwater volcano, now called Fani Maoré. Multiple scientific expeditions followed, taking samples of the recently erupted lava. When a team of researchers analyzed 13 samples from Fani Maoré and eight additional samples from eastern Mayotte, they discovered remnants of a mineral called bridgmanite that they believe came from Earth's earliest geologic time period, the Hadean eon. Their findings were recently published in Nature.
Author(s): Chiharu Nakatsuji, Yuji Takagi, Gabriele Cristoforetti, Sota Matsuura, Takuya Honda, Daisuke Tanaka, Dimitri Batani, Takumi Sato, Shun Horimoto, Hideo Nagatomo, Yasuhiko Sentoku, Philippe D. Nicolaï, Kai Taketoshi, Naoki Yamagata, Norimasa Ozaki, Yasunobu Arikawa, Akifumi Yogo, Shinsuke Fujioka, and Keisuke Shigemori
We present an experimental investigation demonstrating that the suppression of parametric instabilities in laser-plasma interactions under conditions relevant to direct-drive inertial confinement fusion, specifically backward stimulated Raman scattering (SRS) and two-plasmon decay (TPD), shows the e…
[Phys. Rev. E 114, 015202] Published Mon Jul 06, 2026
Author(s): Ao Xu and Yan Feng
Equilibrium molecular dynamical simulations of three-dimensional (3D) Yukawa fluids are performed to investigate thermodynamics and supercritical transition of 3D dusty plasma fluids. The normalized reduced excess entropy sex/sexm of 3D Yukawa fluids (where sexm is the excess entropy at the melting …
[Phys. Rev. E 114, 015203] Published Mon Jul 06, 2026
Author(s): Djamel Benredjem and Jean-Christophe Pain
The aim of this work is to predict the opacity of plasmas under stellar conditions. We focus on iron and nickel, as these elements have been extensively investigated both theoretically and experimentally. In certain regimes, notably under nonlocal thermodynamic equilibrium, calculating the spectral …
[Phys. Rev. E 114, 015204] Published Mon Jul 06, 2026
The state of the Atlantic Meridional Overturning Circulation (AMOC) has been a hot topic among climate scientists in recent years. The AMOC is crucial for climate regulation because it pulls warm surface water from the tropics north and sends colder, deeper water south, redistributing large amounts of heat, helping to sustain marine ecosystems and keeping global weather patterns steady. However, most standard AMOC-focused climate models may be missing an important piece of the puzzle—they don't include the growing pulse of freshwater from Greenland ice melt, which could further disrupt the AMOC.
Tropical moist forests account for 70% of global living biomass. Deforestation and degradation—that is, the partial damage to tree stands—as well as the subsequent regeneration of forests therefore play a pivotal role in the global carbon cycle. While the effects of large-scale tropical deforestation are well understood, the impacts of forest degradation have remained highly uncertain until now.
