道达尔

Geological carbon sequestration (GCS) will play a critical role in decarbonization and in facilitating the transition to clean energy systems. Because CO2 is highly mobile, ensuring its safe and permanent injection into subsurface geological formations involves monitoring over larger spatial domains and longer time periods than is typical for hydrocarbon reservoirs. This can benefit from simulation tools capable of modeling key CO2 trapping mechanisms, particularly those optimized for speed and scalability on high- performance computing systems. Using isothermal versions of the SPE11B and SPE11C benchmark cases, we conduct a mesh refinement study simulating CO2 injection into kilometer- scale rock formations at centimeter resolution with the GEOS open- source simulation framework. We focus on how mesh refinement improves the accuracy of convective mixing in both 2D and 3D simulations. The computational costs associated with achieving a converged solution highlight the need for predictive upscaling techniques. A systematic performance scaling analysis- including both central processing unit (CPU) and graphics processing unit (GPU) architectures-complements the "Results" section.

Synthetic data has gained attention for training large language models, but poor-quality data can harm performance (see, e.g., Shumailov et al. (2023); Seddik et al. (2024)). A potential solution is data pruning, which retains only high-quality data based on a score function (human or machine feedback). Previous work Feng et al. (2024) analyzed models trained on synthetic data as sample size increases. We extend this by using random matrix theory to derive the performance of a binary classifier trained on a mix of real and pruned synthetic data in a high dimensional setting. Our findings identify conditions where synthetic data could improve performance, focusing on the quality of the generative model and verification strategy. We also show a smooth phase transition in synthetic label noise, contrasting with prior sharp behavior in infinite sample limits. Experiments with toy models and large language models validate our theoretical results.

This paper examines the strategic adoption of artificial intelligence (AI) by authoritarian leaning regimes in the Middle East, focusing on Iran, Saudi Arabia, and the United Arab Emirates (UAE). By analyzing the commonalities and divergences in AI-driven governance practices across these states, the study explores the broader implications of AI on authoritarian control. Employing an interdisciplinary theoretical approach, it traces how AI-powered technologies such as facial recognition, predictive policing, and digital censorship have transformed surveillance into an adaptive and pervasive mechanism of state control. The study highlights the dual nature of these technologies, demonstrating their capacity to enhance governance efficiency while simultaneously reinforcing political repression. To conceptualize the evolving landscape of digital governance, the paper, drawing on comparative case studies from the Middle East, introduces the TRIAD Framework (Technology, Regulation, Influence, and Adaptive Dynamics). This novel analytical model elucidates the complex interplay between technological advancements, regulatory changes, and geopolitical influence, thereby contributing to the understanding of how these factors sustain authoritarian resilience within the region. The framework illustrates how AI not only fortifies existing mechanisms of control but also fosters a feedback loop wherein technological innovations drive regulatory evolution and reinforce autocratic adaptability.

The Comoros archipelago located in the western Indian Ocean has been a topic of debate for ca. 50 years regarding its origin. Various mechanisms have been proposed to explain its formation, ranging from the impact of a mantle plume to the development of a plate boundary between the Somalia and Lwandle plates. Determining the timing of the volcanic activity is crucial to understanding the archipelago's origin. Despite recent geochronological studies, the age of the initial volcanic eruptions on the islands remains uncertain due to the difficulty of accessing the earliest lavas. This study uses high- quality seismic reflection profiles and regional stratigraphy to identify the first volcanic series that marked the onset of volcanism on each island of the Comoros Archipelago. Our findings reveal that localized volcanic activity began ca. 32 Ma at Z & eacute;l & eacute;e and Geyser banks and Mayotte edifice, the eastern portions of the archipelago, much earlier than previously believed. Volcanism spread across the Comoros archipelago ca. 9-8 Ma, from the northern part of the Mayotte edifice to Moh & eacute;li Island in the west. Ca. 4 Ma, volcanic activity occurred on Anjouan Island and the Jumelles seamounts, followed by Grande Comore Island ca. 2 Ma. This progression of ages from east to west indicates a chronological sequence over time. The timing of volcanic activity in the Comoros archipelago is similar to the magmatism evolution documented at Madagascar and along the East African Rift System (EARS). Magmatic activity began in the late Oligocene, followed by quiescence during the middle Miocene, and resumed in the late Miocene, coinciding with widespread deformation along the EARS, including its offshore branches and Madagascar. Our study shows that the regional tectonic control of volcanic activity in the Comoros archipelago began during the early Miocene, thereby suggesting that the Comoros archipelago developed as an offshore branch of the EARS south of the Somalian plate at that time.

To obtain an analytical solution for the extension of the failure zone around a wellbore, we consider the problem of a hollow cylinder subjected to boundary stress and pore pressure, and the rock having a brittle elasto-plastic behavior obeying the plastic criterion of Mohr-Coulomb (M-C), which features a sharp transition from intact rock (elastic behavior) to failed rock (plastic). Two cases of effective stress combination have been studied (a) σ'θ > σ'z > σ'r which correspond to a production well and (b) σ'z > σ'θ > σ'r for an injection well. The analytical stress solution in the plastic zone clearly shows that the pore pressure gradient plays a role reducing of rock strength, a kind of "drag force", in case of production well. The condition for unstable plastic extension is demonstrated. Sensitivity studies can be easily conducted using the analytical stress solution. The relationship between the extension of the failure zone and the applied drawdown pressure can be established. The effects of smooth ramp-up or aggressive ramp-up of production on the extension and volume of the failure zone have been studied by varying the outer radius b of the hollow cylinder. The results indicate that a smooth ramp-up can significantly limit the volume of the failure rock for the same drawdown pressure.