Search Results (219)

Consisting of phospholipids, sperm membranes surround the head and tail, playing essential roles in maintaining cellular structural integrity and functions. Their characteristics directly influence sperm fertility and cryopreservation outcomes. This minireview provides a summary of how sperm fertility and freezability are affected by the characteristics of its cell membranes. The primary emphasis is on the molecular and cellular anatomy as well as the physiology of sperm membranes and their attributes associated with fertility determinants or biomarkers for fertility and freezability. It also explores how this knowledge can guide the development of extenders to improve sperm freezability and enhance reproductive technologies in mammals. By providing integrity, fluidity, and selective permeability, the membranes play vitally important roles in sperm motility, which is required for successful fertilization. Cryopreservation, which involves freezing and thawing of sperm for storage or ART, alters the integrity and functionality of the sperm membranes. Sperm freezability, its viability following freezing and thawing, is influenced by several properties of the sperm cell membranes, such as lipid composition, cholesterol content, and structures and functions of the membrane proteins. This review provides concise information about the nature of sperm membranes. It highlights the importance of understanding specific biophysical and biochemical features, including lipid composition, protein distribution, and membrane phase behavior. Particular attention is given to parameters such as the cholesterol–phospholipid ratio and membrane phase transition temperature (Tm). A deeper understanding of these factors can contribute to the identification of reliable fertility biomarkers and the optimization of cryopreservation techniques used in ART and animal breeding programs. Furthermore, this review underscores the need for comprehensive investigations into the molecular and cellular architecture of sperm cells. Such studies are essential for advancing both fundamental and applied aspects of reproductive biology in food-producing animals, endangered species, and humans. Full article

Underground gas storage (UGS) is critical to national reserves and seasonal peak-shaving, and its safe operation is integral to energy security. In UGS surface process pipelines, heterogeneous bimetal composite pipes—carbon-steel substrates lined with stainless steel—are widely used but susceptible under coupled thermal–pressure–flow loading to geometry-induced instabilities (local buckling, adhesion, and collapse), which can restrict flow, concentrate stress, and precipitate rupture and unplanned shutdowns. Conventional ultrasonic testing and magnetic flux leakage have limited sensitivity to such instabilities, while standard eddy-current testing is impeded by the ferromagnetic substrate’s high permeability and electromagnetic shielding. This study introduces magnetically saturated pulsed eddy-current testing (MS-PECT). A quasi-static bias field drives the substrate toward magnetic saturation, reducing differential permeability and increasing effective penetration; combined with pulsed excitation and differential reception, the approach improves defect responsiveness and the signal-to-noise ratio. A prototype was developed and evaluated through mechanistic modeling, numerical simulation, laboratory pipe trials, and in-service demonstrations. Field deployment on composite pipelines at the Hutubi UGS (Xinjiang, China) enabled rapid identification and spatial localization of liner collapse under non-shutdown or minimally invasive conditions. MS-PECT provides a practical tool for composite-pipeline integrity management, reducing the risk of unplanned outages, enhancing peak-shaving reliability, and supporting resilient UGS operations. Full article

The optimization of pump setting depth in low-permeability oil wells remains a persistent challenge, as conventional inflow performance relationship (IPR) curves fail to capture the coupled effects of downhole pump intake depth and reservoir productivity. To address this limitation, this study proposes a novel Low-Permeability Intake Inflow Performance Relationship (LIIPR) framework. The method establishes a theoretical link between pump depth and production by integrating low-permeability reservoir inflow models with multiphase wellbore flow calculations. On this basis, a series of derivative concepts and analytical tools are introduced, including (i) a three-zone classification of inflow curves to distinguish effective, inefficient, and abnormal production regimes; (ii) a multi-pump-depth analysis to determine the feasible range and optimal boundaries of pump setting depth; and (iii) a three-dimensional deep-pumping limit map that couples inflow and outflow dynamics through nodal analysis, providing a comprehensive criterion for system optimization. The proposed LIIPR methodology enables accurate identification of optimal pump depth and intake pressure conditions, overcoming the ambiguity of traditional IPR-based approaches. Unlike previous IPR- or EIPR-based methods, LIIPR introduces for the first time a unified inflow–outflow coupling framework that quantitatively links pump intake depth with well productivity. This integration represents a novel theoretical and computational advance for deep-pumping optimization in low-permeability reservoirs. Applications for field cases in Shengli Oilfield confirm the theoretical findings and demonstrate the practical potential of the method for guiding efficient deep pumping operations in low-permeability reservoirs. Full article

The fracturing and driving oil technology used in shale oil provides a new approach for the development of offshore low-permeability reservoirs. However, the main control role of technical parameters is unclear, resulting in unsatisfactory accuracy and effectiveness of the enhanced oil recovery plan. For this reason, this study is based on the production and process data of five wells in the WZ oilfield. Fuzzy analytic hierarchical process analysis method (FAHP) was used to evaluate the parameter weights. Combined with numerical simulation technology, the evaluation results were verified by geological-engineering integration. The results show that in offshore low-permeability oilfields, the reservoir pressure coefficient has the greatest influence on the fracturing and oil repelling effect. The comprehensive weight reaches 0.450 compared to not adopting hydraulic fracturing oil displacement technology. This improves the recovery rate by 10.19% in 5 years. The surfactant concentration and the residual oil saturation of the reservoir rank are second, with a comprehensive weight of 0.219. Finally is the effective thickness of the reservoir, with a comprehensive weight of 0.113. In this study, the key parameters of fracturing and oil repelling in offshore low-permeability reservoirs are clarified. It provides theoretical basis and practical support for improving the success rate of well selection, layer selection and recovery capacity. Full article

To address the challenge of identifying water-flooded layers in the high-porosity, high-permeability, and strongly heterogeneous reservoirs of the Guantao Formation in the Penglai 19-3 Oilfield, research on water-flooded layer identification methods was systematically conducted. The logging characteristics of oil layers and water-flooded layers at different levels overlap considerably, which limits the accuracy of traditional identification methods. Meanwhile, the Archie equation shows significantly reduced applicability during the moderate and strong water-flooding stages. A water-flooded layer identification model was constructed using HistGBDT, and performance comparison between the base model and the optimized model reveals that the latter achieves a test accuracy of 91.6%. Compared with BPNN and SVM, the optimized HistGBDT model demonstrates substantially higher test accuracy and better generalization performance. Based on six sets of logging data, the optimized HistGBDT model developed enables the accurate identification of oil layers and multi-level water-flooded layers. It provides a reliable technical approach for tapping remaining oil in the high-water-cut stage of the Penglai 19-3 Oilfield and offers a new method and engineering reference for water-flooded layer identification in similar high-porosity, high-permeability heterogeneous reservoirs in the Bohai Bay Basin. Full article

Nowadays, most of the heavy oil fields around the world have entered difficult exploiting stages, with problems regarding high viscosity and poor fluidity. However, there has been little previous research on the accurate identification and distribution of remaining oil with different levels of steam dryness. Therefore, this paper proposes a new nuclear magnetic resonance (NMR) interpretation method, as well as a new samples analysis method for remaining oil in the core. We conducted core displacement experiments using different methods. The nuclear magnetic resonance (NMR) tests and analysis of core thin sections after steam flooding were used to study the effect of different steam dryness levels on the migration and sedimentation mechanisms of heavy oil components. The results showed that the viscosity of crude oil and the permeability of rock cores are both sensitive to steam dryness; therefore, the improvement of steam dryness is beneficial for improving oil recovery. Heavy oil is mainly distributed in the medium pores of 10–50 μm and the small pores of 1–10 μm. However, with the decrease in steam dryness, the dynamic amount of crude oil in both medium and small pores decreases, and the bitumen in crude oil stays in the pores in the form of stars, patches, and envelopes, which leads to a decline in oil displacement efficiency. Thus, our study provides a micro-level understanding of remaining oil which lays the foundation for the further enhancement of oil recovery in heavy oilfields. Full article

Hydraulic fracturing technology significantly enhances reservoir conductivity by creating artificial fractures, serving as a crucial means for the economically viable development of low-permeability reservoirs. Accurate prediction of post-fracturing productivity is essential for optimizing fracturing parameter design and establishing scientific production strategies. However, current limitations in understanding post-fracturing production dynamics and the lack of efficient prediction methods severely constrain the evaluation of fracturing effectiveness and the adjustment of development plans. This study proposes a machine learning-based method for predicting post-fracturing productivity in multi-layer commingled production wells and validates its effectiveness using a key block from the PetroChina North China Huabei Oilfield Company. During the data preprocessing stage, the three-sigma rule, median absolute deviation, and density-based spatial clustering of applications with noise were employed to detect outliers, while missing values were imputed using the K-nearest neighbors method. Feature selection was performed using Pearson correlation coefficient and variance inflation factor, resulting in the identification of twelve key parameters as input features. The coefficient of determination served as the evaluation metric, and model hyperparameters were optimized using grid search combined with cross-validation. To address the multi-layer commingled production challenge, seven distinct datasets incorporating production parameters were constructed based on four geological parameter partitioning methods: thickness ratio, porosity–thickness product ratio, permeability–thickness product ratio, and porosity–permeability–thickness product ratio. Twelve machine learning models were then applied for training. Through comparative analysis, the most suitable productivity prediction model for the block was selected, and the block’s productivity patterns were revealed. The results show that after training with block-partitioned data, the accuracy of all models has improved; further stratigraphic subdivision based on block partitioning has led the models to reach peak performance. However, data volume is a critical limiting factor—for blocks with insufficient data, stratigraphic subdivision instead results in a decline in prediction performance. Full article

The development of low-permeability reservoirs offshore entails substantial investment and demands high production capacity for oil and gas. Consequently, the analysis and evaluation of key elements for integrated geological–engineering sweet spots have become essential. This study systematically establishes a coupled analysis methodology for geological and engineering parameters of low-permeability reservoirs, based on Offshore Oilfield A. A comprehensive evaluation framework for geological–engineering sweet spots is proposed, which applies grey relational analysis and the analytic hierarchy process. Twelve geological–engineering sweet spots were analysed, with corresponding parameter weightings determined. Geological sweet spots encompassed factors such as porosity, permeability, and oil saturation, and engineering sweet spots considered Young’s modulus, Poisson’s ratio, fracture factor, and brittleness index. Low-permeability reservoirs were categorised into Classes I, II, III, and IV by establishing indicator factors. Integrating seismic inversion and reservoir numerical simulation methods, we constructed an analysis model. This methodology resolves challenges in evaluating offshore low-permeability reservoirs, enabling rapid and precise sweet spot identification. It provides critical technological support for enhancing oil and gas production efficiency. Full article

Species of the Ferula genus are known for their traditional medicinal applications against diverse illnesses. Our previous study was the first to suggest the cholinesterase inhibitory activity of Ferula persica L. However, the neuroprotective efficacy of therapeutic molecules is often limited by their ability to cross the blood–brain barrier (BBB) and reach the brain. In the present study, the BBB permeability of the main molecules present in the aerial parts and roots of F. persica L. extracted under optimum conditions was assessed using two well-established methods: the parallel artificial membrane permeability assay (PAMPA) and the HBMEC cell culture in vitro model. The results demonstrated a high permeability of several neuroprotective compounds, such as apigenin, diosmetin, and α-cyperone. Additionally, the neuroprotective potential of F. persica extracts was evaluated using SH-SY5Y neuron-like cells exposed to different insults, including oxidative stress (H₂O₂), excitotoxicity (L-glutamate), and Aβ1-42 peptide toxicity. However, none of the obtained extracts provided significant protection. This study highlights the importance of in vitro cell culture models for a better understanding of BBB permeability mechanisms and reports the tentative identification of newly formed sulfated metabolites derived from the metabolism of ferulic acid, apigenin, and diosmetin by HBMEC cells. Full article

The offshore reservoir development involves large injection and production rates and high injection pressures. High-permeability flow channels usually occur in offshore unconsolidated heavy-oil reservoirs during long-term water flux, substantially impacting the production performance. As one important method for identifying channeling, the numerical simulation method with a full-fidelity model is hampered by the low computational efficiency of the history matching process. The GPSNet model is extended for polymer flooding simulations, incorporating complex mechanisms including adsorption and shear-thinning effects, with solutions obtained through a fully implicit numerical scheme. Four flow channel characteristic parameters are proposed, and an evaluation factor M for flow channel identification is established with the comprehensive evaluation method. Finally, the field application of the GPSNet model is made and validated by the tracer interpretation result. The history matching speed based on the GPSNet model is 58 times faster than the full-fidelity ECLIPSE model. In addition, the application demonstrates a high degree of consistency with tracer monitoring results, confirming the accuracy and field feasibility. The new method enables rapid and accurate identification and prediction of large and dominant channels, offering effective guidance for targeted treatment of channels and sustainable development of polymer flooding. Full article

Due to their low permeability, the location of natural fractures is key to the successful development of buried hill reservoirs. Due to the high degree of rock fragmentation and strong absorption of seismic waves at the top of buried hill formations, it is hard to identify the distribution of natural fractures inside a buried hill using conventional seismic methods. To overcome this difficulty, this study proposes a natural fracture identification technology for buried hill reservoirs that combines a continuum damage mechanics model with finite element numerical simulation. A 3D numerical solution workflow is established to determine the natural fracture distribution in target buried hill reservoirs. By constructing a geological model of a block, reconstructing the orogenic history, developing a 3D finite element model, and performing numerical simulations, the multi-stage orogenic processes experienced by buried hill reservoirs and the resultant natural fracture formation are replicated. This approach yields 3D numerical results of natural fracture distribution. Using the G-Block in the Zhongyuan Oilfield as a case study, the natural fracture distribution in a buried hill reservoir composed of mixed lithologies, including marble and Carboniferous formations, within the faulted G6-well group is analyzed. The results include plane views of the contour of damage variable SDEG, which represents the fracture distribution within the subsurface layer at 600 m intervals below the buried hill surface, as well as a vertical sectional view of the contour of SDEG’s distribution along specified well trajectories. By comparison with the results of the fracture distribution obtained with logging data, a consistency of 87.5% is achieved. This indicates the reliability of the numerical results for natural fractures obtained using the technology presented here. Full article

The lithological dichotomy in the Hammam Faraun Member (Gulf of Suez, Egypt) reveals a stable western flank with Nullipore carbonate deposits, contrasting with the clastic-prone eastern margin influenced by tectonic activity. This study aims to decipher multifactorial controls on spatial lithological variability and reservoir implications through (1) foraminiferal-based paleoenvironmental reconstruction; (2) integrated sequence stratigraphic–petrophysical analysis for sweet spot identification; and (3) synthesis of lateral facies controls. This study uniquely integrates foraminiferal paleoenvironmental proxies, sequence stratigraphy, and petrophysical analyses to understand the multifactorial controls on spatial variability and its implications for reservoir characterization. Middle Miocene sea surface temperatures, reconstructed between 19.2 and 21.2 °C, align with warm conditions favorable for carbonate production across the basin. Foraminiferal data indicate consistent bathyal depths (611–1238 m) in the eastern region, further inhibited in photic depths by clastic influx from the nearby Nubian Shield, increasing turbidity and limiting carbonate factory growth. Conversely, the western shelf, at depths of less than 100 m, supports thriving carbonate platforms. In the sequence stratigraphy analysis, we identify two primary sequences: LA.SQ1 (15.12–14.99 Ma), characterized by evaporitic Feiran Member deposits, and LA.SQ2 (14.99–14.78 Ma), dominated by clastic deposits. The primary reservoir comprises highstand systems tract (HST) sandstones with effective porosity ranging from 17% to 22% (calculated via shale-corrected neutron density cross-plots) and hydrocarbon saturation of 33%–55% (computed using Archie’s equation). These values, validated in Wells 112-58 (ϕe = 19%, S_hc = 55%) and 113M-81 (ϕe = 17%, S_hc = 33%), demonstrate the primary reservoir potential. Authigenic dolomite cement and clay content reduce permeability in argillaceous intervals, while quartz dissolution in clean sands enhances porosity. This research emphasizes that bathymetry, sediment availability, and syn-sedimentary tectonics, rather than climate, govern carbonate depletion in the eastern region, providing predictive parameters for identifying reservoir sweet spots in clastic-dominated rift basins. Full article

Objectives: A thorough understanding of pharmacokinetics and metabolism is critical during early drug development. This study investigates the absorption, distribution, metabolism, and excretion (ADME) profile of R14, a novel compound, using a combination of in vitro and in vivo approaches. Methods: In vitro studies included Caco-2 permeability assays, metabolic stability evaluations in liver microsomes and hepatocytes, and identification of CYP isoforms responsible for R14 metabolism. In vivo pharmacokinetic and metabolic profiling was conducted in rats following oral administration. R14 was quantified using UHPLC-MS/MS. Metabolites were identified using high-resolution UHPLC- QTOF MS/MS, and relative exposure was estimated using peak area-derived AUCs. Results: R14 exhibited low oral bioavailability (13.4%) and high systemic clearance (2.63 L/h/kg), indicating high hepatic extraction. A total of 21 plasma and 38 urine metabolites were identified. Major metabolic pathways included initial hydroxylation and hydrogenation, followed by sequential methylation and Phase II conjugations (glucuronidation and sulfation). Key metabolites (M3, M4, M22, M38) accounted for the majority of systemic exposure. Less than 1% of the unchanged drug was excreted in urine, confirming extensive metabolism. Notably, discrepancies between in vitro and in vivo metabolite profiles suggested rapid further transformation of initial metabolites in vivo, which were not fully captured in vitro. Conclusions: This study demonstrates an efficient and integrated strategy for early-phase ADME characterization. The combined use of in vitro assays and in vivo studies, guided by advanced analytical techniques, provides a robust framework for understanding drug metabolism. These findings can inform drug optimization and help minimize risks in later stages of development. Full article

This study developed a copper mineral prospectivity map for the Koldar massif, Kazakhstan, using an integrated approach combining geophysical and satellite methods. A strong spatialgenetic link was identified between faults and hydrothermal mineralization, with faults acting as key conduits for ore-bearing fluids. Lineament analysis and density mapping confirmed the high permeability of the Koldar massif, indicating its structural prospectivity. Hyperspectral and multispectral data (ASTER, PRISMA, WorldView-3) were applied for detailed mapping of hydrothermal alteration (phyllic, propylitic, argillic zones), which are critical for discovering porphyry copper deposits. In particular, WorldView-3 imagery facilitated the identification of new prospective zones. The transformation of magnetic and gravity data successfully delineated geological features and structural boundaries, confirming the fractured nature of the massif, a key structural factor for mineralization. The resulting map of prospective zones, created by normalizing and integrating four evidential layers (lineament density, PRISMA-derived hydrothermal alteration, magnetic, and gravity anomalies), is thoroughly validated, successfully outlining the known Aktogay, Aidarly, and Kyzylkiya deposits. Furthermore, new, previously underestimated prospective areas were identified. This work fills a significant knowledge gap concerning the Koldar massif, which had not been extensively studied using satellite methods previously. The key advantage of this research lies in its comprehensive approach and the successful application of high-quality hyperspectral imagery for mapping new prospective zones, offering a cost-effective and efficient alternative to traditional ground-based investigations. Full article

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article