沙特阿拉伯国家石油公司

The present study investigated the level of microplastic (MP) contamination in the benthic environment of the Arabian Gulf waters of Saudi Arabia for the first time. The green tiger prawn, Penaeus semisulcatus, a commercially valuable shrimp species, was chosen to assess MP pollution. This study examined the gastrointestinal tracts (GT) of 101 composite shrimp samples collected from trawl catches at two fishing harbors. Following morphometric measurements, the GT samples were subjected to alkali digestion, vacuum filtration, and microscopic examination. Suspected particles were further validated using LUMOS II FTIR microscopy with micro-ATR-FTIR, enabling reliable polymer identification. A total of 238 MPs were found, with an average of 2.93 ± 1.63 MPs sample−1 (n = 5 individuals per sample), corresponding to 0.47 ± 0.50 items individual⁻1. Grey (33

The growing global water crisis necessitates innovative solutions that are both cost-effective and environmentally sustainable. Atmospheric water harvesting (AWH) has emerged as a promising avenue of research to address this pressing challenge. Here, we present a novel approach that re-purposes low-value petroleum feedstocks for AWH through their conversion to porous carbon (PC). Utilizing a potassium carbonate-assisted carbonization process, we develop PC from heavy and light cycle oils, and vacuum residue. While all sources yield materials with near superhydrophilic surfaces, only the cycle oils produce PC with high surface area and micoporous architectures. These engineered carbons demonstrate great water adsorption capacities of up to 23 wt

A previously unreported crater is identified on 3-D reflection seismic data onshore eastern Saudi Arabia. It is 6.5 km in diameter and buried a few hundred meters below ground level, yet the only surface expression is a subtle topographic depression in the present-day environment of sabkhas and windblown dunes. Strata are affected by the crater to a depth of approximately 1 km and are tied to a drilled well, 17 km from the crater rim, that provides lithology and age of the deformed sediments, which range from Neogene to Upper Cretaceous. The crater age is late Miocene or Pliocene in this interpretation. The structural geology of the crater is clearly imaged in 3-D across a present-day depth range of 200-600 m below ground level. Structural elements include a central high surrounded by well-developed concentric and radial fault sets that bound fault blocks in the crater walls. Causal mechanisms are examined with a focus on dissolution tectonics since the affected strata include evaporites. However, the scale, unique structural style, and vertical extent of the crater that reaches far below the evaporites rule out evaporite dissolution as the primary genetic mechanism. Diapirism of deep salt and volcanism are also rejected, leaving hypervelocity asteroid or comet impact as a preferred but unproven interpretation. The size, shallow depth of burial, and complete preservation of this structure make it an excellent candidate for tailored future data acquisition and research into crater geometry and mechanics.

The drift-flux models are the fairly popular choice in the development of engineering applications for simulating multiphase flows in pipes. For this mathematical model, several different ways of writing the system of equations are known in the literature; however, there are no convincing comparison of the results that could be used to make a reasoned choice in favor of a particular model for a given application. This paper reviews several formulations of the drift-flux model in the case of one-dimensional cross-section-averaged equations. Three versions of the model are compared on a number of test problems in terms of the accuracy of modeling the results and the volume of required computations. The obtained results demonstrate good agreement between the different models for steady-state flows, but at the same time, they have significant differences in simulating unsteady flows. Moreover, the choice of a more theoretically justified formulation of the drift-flux model does not provide any significant advantage from the standpoint of comparison with experimental data, but significantly increases the computational effort. The obtained results suggest that differences in the formulations of equations contribute less significantly to the error in the simulation results than ambiguities in the empirical correlations used to close the drift-flux model.

Seismic data acquisition is inherently constrained by budget and operational challenges, which often result in datasets that fail to adequately capture geological complexity. These limitations, coupled with the subjectivity from interpreters, lead to inconsistencies in seismic interpretation. Although machine learning (ML) has shown potential for automating interpretation tasks, its generalization across diverse geological settings remains limited by the scarcity of high-fidelity training datasets. Effective seismic data augmentation is critical to addressing this gap by enhancing dataset diversity and realism. However, traditional augmentation methods often fail to replicate key geological features, such as stochastic scattering effects caused by small-scale heterogeneities, limiting their real-world applicability. We propose a novel seismic data augmentation technique that integrates sequential Gaussian simulation with synthetic internal multiples. This approach generates realistic and diverse datasets by accurately modeling stochastic scattering while preserving critical geological structures. The augmented datasets improve manual interpretation and ML model performance in tasks such as fault detection, stratigraphy truncation, and horizon picking. By enhancing data fidelity and variability, our method offers a robust solution to challenges in seismic interpretation, advancing the accuracy and efficiency of workflows across complex geological settings.