Search Results (221)

The potential for oil and gas exploration within inter-salt reservoirs is substantial, primarily due to their significant heterogeneity, which complicates accurate predictions. This study focuses on the inter-salt reservoirs of the sixth sub-member of the fifth member of the Majiagou Formation (hereafter referred to as O₂m₅⁶) in the Ordos Basin, North China. Utilizing core samples, thin sections, and petrophysical data, we investigated the differential evolution and primary controlling factors of the inter-salt carbonate reservoirs. The key findings are as follows: (1) During the sedimentary phase of O₂m₅⁶, high-energy sediments, such as shoals and microbial mounds, were deposited in highlands, while low-energy sediments, including dolomitic lagoons and gypsiferous lagoons, emerged in depressions from west to east. (2) In a restricted–evaporative environment, highlands are prone to karstification, which significantly enhances the development of inter-salt reservoirs and generates a variety of reservoir spaces, including interparticle dissolved pores, growth-framework dissolved pores, and micropores between vadose silts. (3) The presence of alternating highlands and depressions obstructs seawater flow, leading to a progressive increase in salinity from west to east. This process ultimately facilitates the infilling of reservoir spaces with calcite, anhydrite, and halite cements in the same direction. (4) The three components—reservoir rocks, karstification, and infilling features—exert varying effects in the region and collectively govern the north–south distribution of inter-salt reservoirs. Overall, this study examines the characteristics and controlling factors of carbonate reservoirs within a restricted–evaporative platform environment and provides pertinent research cases for the exploration of inter-salt reservoirs. Full article

Modified starch and other natural polymer materials have found extensive applications in drilling fluids. However, conventional modification methods offer limited scope for further enhancing their temperature resistance, typically with the applicable temperature being below 140 °C. This paper presents the preparation of composite plant phenols using walnut shells, peanut shells, straw, and lignin, which are rich in the fundamental “three elements” of plants. To explore the improvement of the temperature resistance of cellulose-based drilling fluid additives, this study investigated the apparent viscosity, dynamic shear force, filtration performance, and adhesion coefficient of water-based drilling fluids supplemented with composite plant phenols. Additionally, the mechanism of action of the composite in drilling fluids was analyzed via infrared spectroscopy. The results revealed that the combined use of starch and composite plant phenols elevated the temperature resistance limit of starch from 160 °C to 180 °C. After aging at 180 °C, the filtration loss of the drilling fluid formulation containing composite plant phenols dropped to 3.6 mL, while the apparent viscosity climbed from 3.1 mPa·s to 13.6 mPa·s. This clearly demonstrates the excellent high-temperature resistance and filtration-reducing capabilities of composite plant phenols. When the addition of cassava starch was 2%, the filtration loss of the drilling fluid system reached a minimum of 6.2 mL. A positively charged gel was identified as the optimal high-temperature-resistant cutting agent. At a dosage of 1%, the dynamic plastic ratio of the formulation increased from 0.51 to 2.11. Tannin extract emerged as the ideal high-temperature-resistant and environmentally friendly drilling fluid treatment agent. After its addition, the apparent viscosity of the drilling fluid system increased from 2.4 mPa·s to 7.3 mPa·s, and the filtration loss decreased from 140 mL to 14.6 mL. Full article

Accurate long-term and high-resolution forest disturbance monitoring are pivotal for forest carbon modeling and forest management. Many algorithms have been developed for this purpose based on the Landsat time series, but their nationwide performance across different regions and disturbance types remains unexplored. Here, we conducted a comprehensive comparison and validation of six widely used forest disturbance- monitoring algorithms using 12,328 reference samples in China. The algorithms included three annual-scale (VCT, LandTrendr, mLandTrendr) and three daily-scale (BFAST, CCDC, COLD) algorithms. Results indicated that COLD achieved the highest accuracy, with F1 and F2 scores of 81.81% and 81.25%, respectively. Among annual-scale algorithms, mLandTrendr exhibited the best performance, with F1 and F2 scores of 73.04% and 72.71%, and even outperformed the daily-scale BFAST algorithm. Across China’s six regions, COLD consistently achieved the highest F1 and F2 scores, showcasing its robustness and adaptability. However, regional variations in accuracy were observed, with the northern region exhibiting the highest accuracy and the southwestern region the lowest. When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles. Full article

This review provides an analysis of non-perovskite hybrid halides of coinage metals templated by metal–organic cations (CCDC November 2023). These materials display remarkable structural diversity, from zero-dimensional molecular complexes to intricate three-dimensional frameworks, allowing fine-tuning of their properties. A total of 208 crystal structures, comprising haloargentates, mixed-metal haloargentates, and halocuprates, are categorized and examined. Their potential in photocatalysis is discussed. Special attention is given to the structural adaptability of these materials for the generation of functional interfaces. This review highlights key compounds and aims to inspire further research into optimizing hybrid halides for advanced technological applications. Full article

This study focuses on addressing the limitations of fluid loss additive in cement slurry under higher temperatures. The synthesis process of glutaraldehyde-crosslinked polyvinyl alcohol (PVA) was optimized to develop an efficient fluid loss additive for oil well cement slurries. Using one-factor experiments and the uniform design method, the optimal synthesis parameters were established: a reaction temperature of 50 °C; an acid concentration of 1 mol/L; a PVA mass concentration of 8%; a molar ratio of glutaraldehyde to PVA hydroxyl group of 1.47; and a crosslinking degree of 1.49%. The optimized crosslinked PVA demonstrated the ability to control API fluid loss within 50 mL when applied at 1% concentration in cement slurry under conditions of 30–110 °C and 6.9 MPa. Rheological analysis at medium and high temperatures revealed improved slurry properties, including smooth thickening curves and unaffected compressive strength. Further analyses, including thermogravimetric analysis (TGA), Zeta potential testing, and scanning electron microscopy (SEM), revealed that the crosslinked PVA hydrogel remained thermally stable up to 260 °C. Chemical crosslinking transformed the linear PVA into a network structure, enhancing its molecular weight, viscoelasticity, and thermal stability. This thermal resistance mechanism is attributed to the hydrogel’s high-strength reticular structure which forms a uniform, dense, and highly stable adsorption layer, thereby improving both the additive’s efficiency and the hydrogel’s temperature resistance. Full article

Tight sandstone reservoirs are characterized by fine-grained rock particles, a high clay content, and a complex interplay between the electrical properties and gas content. These factors contribute to low-contrast reservoirs, where the logging responses of the gas and water layers are similar, resulting in traditional logging interpretation charts exhibiting a low accuracy in the fluid-type classification. This inadequacy fails to meet the fluid identification needs of the study area’s reservoirs and severely restricts the exploration and development of unconventional oil and gas resources. To address this challenge, this study proposes a fluid identification method based on Bayesian-optimized Support Vector Machine (SVM) to enhance the accuracy and efficiency of the fluid identification in low-contrast reservoirs. Firstly, through a sensitivity analysis of the logging responses, sensitive logging parameters such as the natural gamma, compensated density, compensated neutron, and compensated sonic logs are selected as input data for the model. Subsequently, Bayesian optimization is employed to automatically search for the optimal combination of hyperparameters for the SVM model. Finally, an SVM model is established using the optimized hyperparameters to classify and identify the following four fluid types: water layers, gas layers, gas–water layers, and dry layers. The proposed method is applied to fluid identification in the study area, and comparative experiments are conducted with the K-Nearest Neighbor (KNN), Random Forest (RF), and AdaBoost models. The classification performance of each model is systematically evaluated using metrics such as the accuracy, recall, and F1-score. The experimental results indicate that the SVM model outperforms the other models in fluid identification, achieving an average accuracy of 91.41%. This represents improvements of 16.94%, 4.39%, and 8.30% over the KNN, RF, and AdaBoost models, respectively. These findings validate the superiority of the SVM model for fluid identification in the study area and provide an efficient and feasible solution for fluid identification in tight sandstone reservoirs. Full article

Solid–liquid two-phase flow often occurs when pumping proppant or temporary plugging agents into hydraulically fractured wells. The final distribution of these injected particles in the fracture has an important influence on the well productivity after hydraulic fracturing. This paper focuses on simulating and analyzing particle migration within slug injection hydraulic fractures in the Sulige gas reservoir. In this study, a particle migration and settlement model in hydraulic fractures is established based on the Multiphase Particle-in-Cell (MP-PIC) method, allowing for effective simulation of particle migration and settlement in fractures. This model is validated by the results of particle-pumping experiments. The influences of fluid viscosity, injection rate, particle density, particle diameter, and particle concentration on the distribution of particles are studied. The results indicate that keeping the viscosity of the particle-carrying liquid above 50 mPa·s is necessary. It is recommended to keep the liquid viscosity above 200 mPa·s so that the particles can move farther in the fractures. For pulse fracturing, a lower flow rate leads to a more dispersed distribution of particles, but for temporary plugging with particles, a lower flow rate can lead to a decrease in particle concentration and reduce the success rate of temporary plugging. Low particle density can lead to more dispersed particles, but the amount of particle settlement will be less, so from the perspective of pulse fracturing, it is recommended that the particle density should not be lower than 2200 $\mathrm{kg}/{\mathrm{m}}^3$. Similarly, the particle size should not be too large for pulse fracturing, and the initial particle concentration should be maintained above $18\%$. Full article

This study systematically performs multi-scale numerical investigation of supercritical CO₂-energized fracturing, widely employed for enhanced oil recovery (EOR) in tight oil and gas reservoirs. Two distinct models, spanning from core scale to field scale, are designed to explore the diffusion patterns of CO₂ into the matrix and its impact on crude oil production at varying scales. The core-scale model employs discrete grid regions to simulate the interaction between fractures and the core, facilitating a comprehensive understanding of CO₂ diffusion and its interaction with crude oil. Based on the core-scale numerical model, the wellbore treatment process is simulated, investigating CO₂ distribution within the core and its influence on crude oil during the well treatment phase. The field-scale model employs a series of grids to simulate fractures, the matrix, and the treatment zone. Additionally, a dilation model is employed to simulate fracture initiation and closure during CO₂ fracturing and production processes. The model explores CO₂ diffusion and its interaction with crude oil at different shut-in times and various injection rates, analyzing their impact on cumulative oil production within a year. The study concludes that during shut-in, CO₂ continues to diffuse deeper into the matrix until CO₂ concentration reaches an equilibrium within a certain range. At the core scale, CO₂ penetrates approximately 4 cm into the core after a 15-day shut-in, effectively reducing the viscosity within a range of about 3.5 cm. At the field scale, CO₂ diffusion extends up to approximately 4 m, with an effective viscosity reduction zone of about 3 m. Results suggest that, theoretically, higher injection rates and longer shut-in times yield better EOR results. However, considering economic factors, a 20-day shut-in period is preferred. Different injection rates indicate varying fracture conduction capabilities upon gas injection completion. Full article

Glycosylation plays a critical role in various biological processes, yet identifying specific glycosyltransferase substrates remains a challenge due to the complexity of glycosylation. Here, we employ proximity labeling with biotin ligases BASU and TurboID to map the proximitome of MGAT3, a glycosyltransferase responsible for the biosynthesis of the bisecting GlcNAc structure, in HEK293T cells. This approach enriched 116 and 189 proteins, respectively, identifying 17 common substrates shared with bisecting GlcNAc-bearing proteome obtained via intact glycopeptide enrichment methods. Gene ontology analysis revealed that the enriched proteins were predominantly localized in the exosome, endoplasmic reticulum, and Golgi apparatus, consistent with subcellular localization of MGAT3 substrates. Notably, four novel substrates, GOLM2, CCDC134, ASPH, and ERO1A, were confirmed to bear bisecting GlcNAc modification, validating the utility of the proximity labeling method. Furthermore, we observed that bisecting GlcNAc modification inhibits breast cancer progression by promoting the degradation of α-galactosidase A (GLA). These findings demonstrate the efficacy of proximity labeling in identifying glycosyltransferase substrates and provide insights into the functional impact of bisecting GlcNAc modification. Full article

Semen quality and persistence are critical for evaluating the usability of individual boars in AI, a standard practice in pig breeding. We conducted GWASs on various semen traits of Duroc boars, including MOT, DEN, ABN, MMP, AIR, and ROS levels. These traits were assessed using FCM and CASA. A total of 1183 Duroc boars were genotyped using the GeneSeek GGP Porcine 50 K SNP BeadChip. The GWAS was performed using three different models: GLM, MLM, and FarmCPU. Additionally, trait heritability was estimated using single- and multiple-trait PBLUP models, yielding 0.19, 0.29, 0.13, 0.18, 0.11, and 0.14 heritability for MOT, DEN, ABN, MMP, AIR, and ROS, respectively. All semen traits exhibited low heritability except ABN, which demonstrated medium heritability. Nine candidate genes (GPX5, AWN, PSP-II, CCDC62, TMEM65, SLC8B1, TRPV4, UBE3B, and SIRT5) were potentially associated with semen traits. These genes are associated with antioxidant and mitochondrial functions in porcine sperm. Our findings provide insight into the genetic architecture of semen traits in Duroc boars, and the identified SNPs and candidate genes may enhance economic outcomes in the pig breeding industry while improving sperm quality through targeted breeding strategies. Full article

Although osteoclasts play crucial roles in the skeletal system, the mechanisms that underlie oxidative stress during osteoclastogenesis remain unclear. The transcription factor Nrf2 and its suppressor, Keap1, function as central mediators of oxidative stress. To further elucidate the function of Nrf2/Keap1-mediated oxidative stress regulation in osteoclastogenesis, DNA microarray analysis was conducted in this study using wild-type (WT), Keap1 knockout (Keap1 KO), and Nrf2 knockout (Nrf2 KO) osteoclasts. Principal component analysis showed that 403 genes, including Nqo1, Il1f9, and Mmp12, were upregulated in Keap1 KO compared with WT osteoclasts, whereas 24 genes, including Snhg6, Ccdc109b, and Wfdc17, were upregulated in Nrf2 KO compared with WT osteoclasts. Moreover, 683 genes, including Car2, Calcr, and Pate4, were upregulated in Nrf2 KO cells compared to Keap1 KO cells. Functional analysis by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed upregulated genes in Nrf2 KO osteoclasts were mostly enriched in oxidative phosphorylation. Furthermore, GeneMANIA predicted the protein–protein interaction network of novel molecules such as Rufy4 from genes upregulated in Nrf2 KO osteoclasts. Understanding the complex interactions between these molecules may pave the way for developing promising therapeutic strategies against bone metabolic diseases caused by increased osteoclast differentiation under oxidative stress. Full article

Wellbore instability caused by hydration during the development of shale gas reservoirs poses significant challenges to drilling engineering. In this study, a novel and environmentally friendly shale inhibitor, TIL-NH₂, was synthesized via free radical polymerization using 1-vinylimidazole and N-(2-bromoethyl)-1,3-propanediamine dihydrobromide as the main raw materials. The molecular structure of TIL-NH₂ was characterized by infrared spectroscopy and nuclear magnetic resonance. Incorporating imidazole cations and amino bifunctional groups, TIL-NH₂ exhibits excellent inhibitory performance and environmental friendliness. Its performance was systematically evaluated through linear swelling tests, shale cuttings rolling recovery tests, permeability recovery experiments, and dynamic adsorption analyses. The results indicate the following: (1) At a concentration of 1.2 wt%, TIL-NH₂ reduced the linear swelling height of shale by 65.69%, significantly outperforming traditional inhibitors like KCl and NW-1. (2) Under conditions of 140 °C, the cuttings rolling recovery rate of TIL-NH₂ reached 88.12%, demonstrating excellent high-temperature resistance. (3) Permeability recovery experiments showed that at a concentration of 2.0 wt%, TIL-NH₂ achieved a permeability recovery rate of 90.58%, effectively mitigating formation damage. (4) Dynamic adsorption experiments indicated that at a concentration of 2.5 wt%, the adsorption capacity tended toward saturation, reaching 26.00 mg/g, demonstrating stable adsorption capability. Additionally, environmental friendliness evaluations revealed that TIL-NH₂ has a degradation rate exceeding 90% within 28 days, and its acute toxicity is significantly lower than that of traditional inhibitors like KCl (the LC₅₀ of TIL-NH₂ is 1080.3 mg/L, whereas KCl is only 385.4 mg/L). This research provides a high-efficiency and environmentally friendly new inhibitor for green drilling fluid systems in horizontal shale gas wells, offering important references for technological advancements in unconventional energy development. Full article

A study of the solid-state intermolecular interactions of twenty-nine benzopyrans substituted with polyhaloalkyl groups was carried out by quantum chemical calculations using the Mercury and WinGX computer programs. Molecular structures were obtained from crystallographic information files (CIF) of the CCDC database. C-H—O, C-H—X, C-X—O and C-X—X type contacts, characterized as unconventional hydrogen bonds, were identified and calculated. The criteria used for distances and angles were d(D—A) < R(D) + R(A) + 0.50 and d(H—A) < R(H) + R(A)—0.12°, where D-H—A > 100.0°. D is the donor atom, A is the acceptor atom, R is the Van der Waals radius and d is the interatomic distance. In addition, Etter’s notation was used to describe sets of hydrogen bonds in organic crystals, detailing the intermolecular contacts and periodic arrangements of the crystal packing. It was corroborated that certain positions of halogen atoms and their interactions play an important role in stabilizing the crystal lattice. Full article

The aim of this study was to identify genetic variants and pathways associated with the total number of piglets born and to investigate the potential negative consequences of the intensive selection for reproductive traits, particularly the formation of bumps on the legs of pigs. We used genome-wide association analysis and methods for identifying selection signatures. As a result, 47 SNPs were identified, localized in genes that play a significant role during sow pregnancy. These genes are involved in follicle growth and development (SGC), early embryonic development (CCDC3, LRRC8C, LRFN3, TNFRSF19), endometrial receptivity and implantation (NEBL), placentation, and embryonic development (ESRRG, GHRHR, TUSC3, NBAS). Several genes are associated with disorders of the nervous system and brain development (BCL11B, CDNF, ULK4, CC2D2A, KCNK2). Additionally, six SNPs are associated with the formation of bumps on the legs of pigs. These variants include intronic variants in the CCDC3, ULK4, and MINDY4 genes, as well as intergenic variants, regulatory region variants, and variants in the exons of non-coding transcripts. The results suggest important biological pathways and genetic variants associated with sow fertility and highlight the potential negative impacts on the health and physical condition of pigs. Full article

Due to the significant threat to forest health posed by beetle infestations on pine trees, timely and accurate predictions are crucial for effective forest management. This study developed a pine tree stress probability prediction workflow based on monthly cloud-free Sentinel-2 composite images to address this challenge. First, representative pine tree stress samples were selected by combining long-term forest disturbance data using the Continuous Change Detection and Classification (CCDC) algorithm with high-resolution remote sensing imagery. Monthly cloud-free Sentinel-2 images were then composited using the Multifactor Weighting (MFW) method. Finally, a Random Forest (RF) algorithm was employed to build the pine tree stress probability model and analyze the importance of spectral, topographic, and meteorological features. The model achieved prediction precisions of 0.876, 0.900, and 0.883, and overall accuracies of 89.5%, 91.6%, and 90.2% for January, February, and March 2023, respectively. The results indicate that spectral features, such as band reflectance and vegetation indices, ranked among the top five in importance (i.e., SWIR2, SWIR1, Red band, NDVI, and NBR). They more effectively reflected changes in canopy pigments and leaf moisture content under stress compared with topographic and meteorological features. Additionally, combining long-term stress disturbance data with high-resolution imagery to select training samples improved their spatial and temporal representativeness, enhancing the model’s predictive capability. This approach provides valuable insights for improving forest health monitoring and uncovers opportunities to predict future beetle outbreaks and take preventive measures. Full article