Search Results (6,459)

The complex fracture networks, multiphase flow behavior, and nonlinear flow mechanisms induced by hydraulic fracturing in horizontal wells of shale oil reservoirs pose significant challenges to production evaluation. In this study, a semi-empirical productivity evaluation method for multiphase shale oil systems is developed by integrating production dynamics with flow mechanisms. Three-phase productivity equations for oil, gas, and water are established, explicitly incorporating the underlying flow mechanisms. A nonlinear flow index is introduced to characterize both the stress sensitivity of fractures and the threshold pressure gradient in the matrix. Key unknown parameters, including oil saturation, water cut, stimulated reservoir volume, and nonlinear coefficients, are determined through history matching of production data. The impacts of geological properties, fracturing parameters, operating conditions, and nonlinear flow parameters on oil–gas productivity are systematically investigated using the proposed multiphase semi-empirical model. The model is validated against production data from fractured horizontal wells in a field case, demonstrating its accuracy and applicability. Furthermore, the model enables reliable production forecasting based on the derived productivity relationships. The proposed approach provides a practical and efficient tool for rapid post-fracturing productivity evaluation in shale oil reservoirs. Full article

Waterflooding in oilfields for oil displacement and reservoir pressure maintenance has led to the production of scale in several reservoirs. The formation of scale occurs both in the porous media of the reservoir and in the production equipment, leading to production disruptions that result in a decline in revenue. The aim of this paper is to investigate the effects of mixing samples of seawater and aquifer water. This is achieved by conducting turbidity, salinity, pH, and zeta potential measurements. The risk of self-precipitation of the prepared samples was assessed using the PHREEQC program. A PVT cell was used to assess the impact of temperature and pressure on the prepared seawater and aquifer samples. When 40% of the seawater sample was combined with 60% of the aquifer water sample, the turbidity findings indicated maximum precipitation. The amount of precipitation dropped as temperature and pressure increased. To assess the impact of scale formation on the permeability of a Berea sandstone core, a core flooding experiment was conducted employing liquid and gas as the flowing fluid. Additionally, SEM and EDS analyses were used to examine the shape and composition of scale. It was found that SO₄²⁻ and Ca²⁺ ions predominated in scale precipitation. Full article

Rotavirus A (RVA) G3P[3] genotype is widely reported in dogs and less frequently in cats, with only sporadic human cases worldwide. All reported human infections have occurred in children, suggesting increased susceptibility likely linked to close contact with pets and age-related hygiene practices. The identification of a novel genotype constellation in Brazilian canine G3P[3] strains in 2017 prompted full-genotype characterization of the historical RVA/Human-wt/BRA/IAL-R451/2011/G3P[3] strain, previously sequenced only for VP7 and VP4, to define its genomic constellation and relatedness to canine strains. All 11 segments were analyzed by RT-PCR, sequencing and phylogenetics. The rare genotype–lineage constellation G3.III-P[3]-I2.XX-R3.II-C2.V-M3.II-A9-N2.XXIV-T3.II-E3.II-H6.I, shared with Brazilian canine strains, was identified, supporting a potential common origin. RVA/Human-wt/BRA/IAL-R451/2011/G3P[3] strain showed high genetic similarity (93.2–99%) with canine, feline and canine/feline-like human strains worldwide, with six genes (VP1, VP6 and NSP2–NSP5) closely related to Brazilian dog isolates (97.6–99%), indicating its canine origin. NSP2 clustered with strains from domestic (bovine), synanthropic (rat) and human hosts, while VP7 and VP4 were associated with wildlife (bat; raccoon dog) and environmental (sewage; river water) strains, supporting interhost reassortment and highlighting aquatic environments as reservoirs for interspecies transmission. Identification of new lineages (VP1, VP3 and NSP2) within the AU-1-like backbone reflects its underexplored diversity. This novel constellation likely circulated in dogs and may spill over to humans via close contact, reinforcing a One Health approach to understand RVA zoonotic risk, especially in hotspot regions like Brazil. Full article

Accurate reservoir-fluid identification and water saturation prediction are essential for remaining-oil evaluation and water-flooding adjustment in heterogeneous oilfields. However, in the Youshashan Oilfield, southwestern Qaidam Basin, China, thin interbeds, strong reservoir heterogeneity, complex oil–water transitions, and inter-well logging-response differences make conventional single-task interpretation difficult. To address these problems, this study proposes a joint prediction method based on the Youshashan Fluid Prediction Network (YSF-Net) for six-class reservoir-fluid identification and continuous water saturation (S_w) prediction. A total of 200 wells were used and strictly divided by well into 140 training wells, 30 validation wells, and 30 independent test wells to avoid data leakage. Conventional logs were first processed through depth matching, outlier correction, robust standardization, and missing-value masking. Then, sliding-window logging sequences, regional stratigraphic embeddings, and reservoir-prior parameters, including shale volume, porosity, and permeability, were jointly input into the YSF-Net. The model uses a shared feature encoder with classification and regression branches to simultaneously identify oil layers, oil–water layers, water layers, and weakly, moderately, and strongly water-flooded layers, while predicting continuous S_w. A modified Simandoux-based physical consistency constraint was further introduced during training to improve the geological rationality of S_w prediction. Experimental results show that YSF-Net outperforms the CNN, BiLSTM, CNN-BiLSTM, and Transformer. It achieves an Accuracy of 0.926, Macro-F1 of 0.913, Macro-AUC of 0.968, S_w RMSE of 0.061, S_w MAE of 0.047, and S_w R² of 0.947. In direct cross-well testing without fine-tuning, YSF-Net obtains a Cross-well Accuracy of 0.918, Cross-well Macro-F1 of 0.904, and Cross-well S_w RMSE of 0.064. Ablation, transition-boundary, and typical well-interval analyses further demonstrate that regional constraints, reservoir-prior inputs, multi-task learning, and physical consistency improve class-boundary discrimination and S_w prediction reliability. The proposed method provides an accurate, consistent, and practical workflow for intelligent reservoir-fluid interpretation in heterogeneous reservoirs. Full article

Depleted hydrocarbon reservoirs (DHRs), particularly depleted gas reservoirs (DGRs), are increasingly regarded as promising candidates for geologic carbon storage (GCS). However, their low abandonment pressure poses significant thermo-hydraulic challenges during the injection of cold, high-pressure CO₂. In such non-isothermal conditions, complex processes may occur, including Joule–Thomson (J-T) cooling, hydrate formation, salt precipitation, and thermal fracturing, all of which may affect storage performance. This study presents an integrated assessment of the impact of CO₂ injection into DGRs on the three key pillars of GCS: capacity, injectivity, and containment. The analysis integrates laboratory experiments conducted at our institute, simplified analytics and numerical simulations to assess the governing physical mechanisms. The findings indicate that the cold CO₂ injection can enhance effective storage capacity during the injection phase. This is attributed to the increase in fluid density and the delay in pressure buildup. However, the post-injection thermal equilibrium may result in pressure rebound. The CO₂ injectivity has been demonstrated to be significantly impacted by the near-wellbore thermal effects. While thermo-induced fracturing may enhance injectivity, it poses potential risks to wellbore and caprock integrity. The process of hydrate formation depends on the local temperature and petrophysical conditions, with dynamic factors further reducing the likelihood of pore plugging. Salt precipitation has been found to be less critical under typical DGR conditions with low initial water saturation, although having the potential to become significant in the presence of water influx and/or cyclic injection. The findings provide a technical basis for enhancing the engineering design, accelerating the certification process, and ensuring the safe operation of future GCS projects in DGRs. Full article

Slump-type gravity-flow deposits are extensively developed in the Jiufotang Formation of the Naiman Sag, representing a core frontier for deep-water subtle hydrocarbon reservoir exploration. However, these deposits exhibit strong internal reservoir heterogeneity, while their diagenetic mechanisms are complex and their development pattern remains unclear. Integrating macroscopic and microscopic investigation of cores, scanning electron microscopy (SEM), micro-CT, and high-pressure mercury injection capillary pressure (MICP) data, a systematic study was conducted on the petrological characteristics and diagenesis of the gravity-flow reservoirs. The results indicate that the lithology is dominated by feldspathic lithic sandstones with low compositional maturity. The present-day reservoir quality is governed by the high spatiotemporal coupling between deposition and burial diagenesis. Compaction is the absolute dominant diagenetic factor driving the densification of these reservoirs. The strong compaction resistance, derived from a low argillaceous matrix content and a well-developed grain-supported framework, is the key to the formation of high-quality reservoirs. Furthermore, three distinct diagenetic pathways are revealed: the “high-energy freezing—rigid pore preservation” pathway controls the development of high-quality exploration sweet spots; the “shear mixing—plastic pore reduction” pathway forms low-permeability transitional reservoirs; and the “viscous suspension—compaction densification” pathway indicates widespread tight sandstone exploration targets. Full article

Urban reservoirs are increasingly exposed to multiple interacting pressures associated with eutrophication, pollutant inflow, ageing sewerage and stormwater infrastructure, and climate-related hydrological instability. This issue is of growing concern because municipalities often possess fragmented monitoring and planning evidence without an operational framework for translating it into remediation action. This study develops an integrated decision-support framework for the Ternopil Reservoir based primarily on recent hydrochemical monitoring data, complemented by historical targeted sampling and local environmental and planning materials. The analysis focuses on the most informative indicators of ecological deterioration in an urban reservoir, including oxygen regime, organic pollution, nutrient-related parameters, suspended solids, and selected pollution markers. The available evidence indicates that the Ternopil Reservoir is among the most environmentally stressed water bodies within the local reservoir system, with recurrent eutrophication symptoms, seasonal water blooming, and spatially differentiated exceedances of selected water-quality indicators. The results further indicate persistent nutrient-related and organic pressure, pronounced hydrochemical tension in 2022, and hotspot vulnerability in hydraulically weak sectors of the reservoir. To address these pressures, the study proposes a four-stage monitoring-to-remediation framework that links environmental diagnosis with the identification of vulnerable zones, the prioritisation of hydraulic and hydrobiological measures, and post-remediation control. The proposed framework is intended as an operational planning tool for translating fragmented local evidence into a coherent remediation pathway for urban reservoirs under multiple environmental stressors. Full article

Cyanobacterial blooms in lakes and reservoirs pose significant environmental and public health risks. This paper presents an effective exploration strategy to detect them from Autonomous Surface Vehicles (ASVs) equipped with probes, whose sensing trajectories are optimized by an AI-based planner that considers the 3D spatial-temporal evolution of the cyanobacteria concentration obtained by a multiphysics model. The planner, simultaneously working on the AI decision-making and robotic domains, optimizes the surface displacement of the ASV and the depth of its probe by solving a constrained multi-objective optimization problem that minimizes the mission duration and trajectory length, maximizes the possibilities of the probe to overpass areas with high concentration of cyanobacteria, and satisfies operational constraints (such as ASV velocity or acceleration limits, and obstacle avoidance). The optimization is supported by two well-known versions of the Non-Sorted Generic Algorithm (NSGA-II and NSGA-III) and by encoding the trajectories with spline curves whose number of control points can be fixed, progressively increased, or freely manipulated by the algorithm. The performance of different configurations of the planner is tested against six scenarios obtained from different simulations of the multiphysics model (which couples water dynamics and temperature, light transmission, daily vertical migration of the cyanobacteria and their growth). The statistical analysis of the planner results determines that NSGA-III working with variable-length chromosomes and NSGA-II with the progressive increment of spline points as the best configurations for maximizing cyanobacteria detection, and minimizing mission duration and trajectory length. Full article

Shale gas will be the focus of global oil and gas exploration in the future. As a key mineral component in shale, the characteristics and genesis of feldspar are of great significance for reservoir quality. The feldspar in the Qiongzhusi Formation shale was studied through core observation, X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and major and trace elements analysis. The results show that the content of feldspar in the Qiongzhusi Formation shale is relatively high, with an average content of 27.3%, mainly sodium feldspar. The feldspar presents various forms, such as angular clastic particles and strongly altered particles. It exhibits localized dissolution and illitetization. The feldspar in the Qiongzhusi Formation shale is multi-source, mainly provided by the mixture of felsic sedimentary rocks and granites from the upper crust. The main source areas are the Western Sichuan Block, the Motianling Block, and the Hanyang Block. Rapid sedimentation leading to rapid burial is the primary sedimentary control factor for the high initial content of feldspar in the Qiongzhusi Formation shale. During the late burial and diagenetic stages, localized fluid action, comprising the synergy between micro-scale migration and chemical reactions driven by hydrocarbon generation, acts as a key factor influencing the minor variations in feldspar content. Under a stable tectonic background, the fluids in the Qiongzhusi Formation mainly come from organic acids produced by shale hydrocarbon generation, and the influence of formation water fluids is relatively limited, with a low degree of feldspar mineral transformation. Full article

Remaining oil in high-water-cut reservoirs becomes increasingly dispersed during long-term waterflooding, while preferential flow paths cause severe ineffective water circulation and reduce the efficiency of further oil displacement. To improve the quantitative identification of remaining oil enrichment and water-flushed regions, this study proposes a displacement-unit-based classification and evaluation method for dominant remaining oil distribution. The method integrates dynamic allocation of injected water in multilayer reservoirs, time-varying characterization of reservoir physical properties, streamline-based delineation of displacement units, and saturation tracking using the φ-function. Two quantitative indicators, the remaining oil abundance index (I_so) and the water flushing intensity coefficient (C_f), were introduced to classify displacement units into strongly dominant, weakly dominant, and non-dominant types. The method was applied to a high-water-cut block of the W Oilfield, where 902 displacement units were identified from 65 oil and water wells and 36 sublayers. The results show that strongly dominant, weakly dominant, and non-dominant displacement units accounted for 37.9%, 33.7%, and 28.4% of the total, respectively. In 15 sublayers, the proportion of strongly dominant units exceeded 50%, indicating severe preferential water flow and limited remaining oil potential in these layers. Strongly dominant units were characterized by high water flushing intensity and low remaining oil abundance, whereas weakly dominant units showed remaining oil enrichment mainly at the margins of displacement units. The proposed method couples injection–production dynamics with seepage-field evolution and provides a quantitative basis for fine-scale adjustment of injection–production patterns in high-water-cut reservoirs. Full article

Precise forecasting of the initial productivity rates of infill wells is essential for the effective exploitation of offshore reservoirs characterized by high water-cut. However, conventional reservoir simulation and basic machine learning models often suffer from high computational complexity and low interpretability. This research introduces a hybrid data-driven framework that combines ensemble feature engineering with a random forest model optimized through the crayfish optimization algorithm. The primary controlling factors were identified through a majority voting mechanism involving five feature selection algorithms. Subsequently, the COA was utilized to optimize the parameters of the random forest algorithm to improve its predictive robustness. The proposed EFE-COA-RF model achieves a testing MAE of 6.831 and an R² of 0.954, outperforming standard machine learning models and other optimization-based variants. The complete training process requires approximately 10.8 min, whereas the prediction time for the testing set is approximately 0.03 s. These results demonstrate that the proposed framework provides an accurate, interpretable, and efficient tool for rapid productivity evaluation in mature offshore oilfields. Full article

A study was conducted on the construction of sulfonated poly(aryl ether ketone) nanomicelles and their dispersion–displacement synergistic behavior in deep oil recovery. Unlike conventional surfactant systems, inorganic nanoparticle-based EOR materials, and polymeric nanofluids that mainly rely on interfacial tension reduction, wettability alteration, or viscosity regulation, this study constructs self-assembled sulfonated poly(aryl ether ketone) nanomicelles that integrate a rigid aromatic backbone, ionizable sulfonic acid groups, nanoscale dispersion, and interfacial regulation within one polymeric architecture. Sulfonated poly(aryl ether ketone) nanomicelles were prepared by combining polymer sulfonation with solvent-induced self-assembly, and their structural features, dispersion stability, interfacial behavior, porous-media transport, and displacement performance were systematically evaluated. Spectroscopic characterization confirmed the successful introduction of sulfonic acid groups into the polymer backbone. The resulting nanomicelles exhibited an average hydrodynamic diameter of 117.8 nm, a polydispersity index of 0.186, and a zeta potential of −38.6 mV in deionized water, while a value of −27.4 mV was still maintained at a salinity of 150,000 mg/L, indicating good electrostatic stability under highly mineralized conditions. Further evaluation showed that the 0.30 wt% system retained a transmittance of 97.4% after 15 d of static standing, and its particle size remained at 151.7 nm even under 120 °C and 150,000 mg/L, demonstrating favorable thermal–salinity tolerance. At the same concentration, the oil–water interfacial tension decreased to 6.9 mN/m at 1800 s, while the contact angle of oil-aged quartz was reduced from 118.4° to 58.7°, indicating effective regulation of both the oil–water interface and the solid surface wettability. During microscopic displacement, the residual oil area fraction decreased from 32.8% after water flooding to 14.6%, and cluster-like oil, corner oil, and film-like oil were reduced from 14.6%, 9.8%, and 8.4% to 5.9%, 4.2%, and 4.5%, respectively. In core flooding, the incremental oil recovery reached 13.2%, the final water cut decreased to 81.2%, and the injection pressure increased only from 0.42 MPa to 0.68 MPa. These results indicate that sulfonated poly(aryl ether ketone) nanomicelles promote deep residual-oil mobilization through the combined effects of stable dispersion, interfacial regulation, and effective transport, with 0.30 wt% identified as the preferred concentration range. The main scientific contribution of this work is to establish a structure–dispersion–interface–transport–displacement relationship for SPAEK nanomicelles under deep-reservoir conditions, providing a polymeric nanomicelle-based strategy distinct from conventional surfactant, sulfonated polymer, and nanoparticle flooding systems. Full article

Numerical simulation is an effective method for studying groundwater flow and heat transfer in geothermal energy projects. Describing the characteristics of thermal plumes is important for operational planning of geothermal energy projects. In contrast to shallow geothermal system, the injection temperature differs significantly from the natural temperature of thermal reservoir in high-temperature geothermal projects, which leads to changes in fluid density and dynamics viscosity. The purpose of this paper is to investigate the impacts of temperature-induced changes in density and dynamics viscosity on simulation. The Enhanced Geothermal System (EGS) in North Jiangsu Basin, China, is taken as a case project. Based on the theory of groundwater flow and heat transfer in porous-fracture dual medium, a numerical model of EGS is established to predict the thermal performance. The density and the dynamics viscosity in the model were set as either constant or temperature-dependent to simulate the hydraulic head and temperature of the production well. The influence of temperature-induced changes in density and dynamics viscosity on the simulation was quantitatively studied. The results show that temperature-induced change in dynamics viscosity has a greater impact on the simulation, with deviation in hydraulic head exceeding 20% if the dynamics viscosity is assumed constant. The temperature-dependent variation in viscosity should be incorporated into the simulation process to improve the accuracy of the calculation. In practice, EGS projects should maximize the temperature differential between produced and injected water. The increased viscosity of lower-temperature circulation water extends its residence time within the system, thereby facilitating more thorough heat extraction. This research enhances our understanding of the role of the temperature in groundwater flow and heat transfer within EGS. Full article

Typical saline lacustrine mixed sedimentary strata are developed in the Middle Permian Lucaogou Formation (P₂l) in the Jimsar Sag, with frequent interbedding of mudstone, dolomitic mudstone, and argillaceous dolomite. The widespread development of dolomite is a key factor controlling the quality of shale oil reservoirs. To reveal the formation mechanism of dolomite in mixed sedimentary rocks and its constraint on lithological assemblages, this study focuses on comparing the differences in mineralogy, geochemistry, and sedimentary environment of the three types of lithologies based on systematic tests such as thin-section observation, X-ray diffraction, major and trace element analysis, organic petrology, and biomarker analysis. The results indicate that dolomite formation in the study area is not controlled by a single factor, but instead results from the combined control of hydrothermal activity, microbial metabolism, and paleoclimatic fluctuations. Hydrothermal activity provided a source of Mg²⁺, and together with evaporation driven by an arid climate, elevated the Mg/Ca ratio of the lake water, establishing the hydrochemical basis favorable for dolomite development. Metabolic activities of lower aquatic organisms, such as bacteria and algae, promoted the formation of a sustained alkaline environment, creating favorable conditions for dolomite precipitation. Against a background of a relatively arid climate, the alternation of extreme arid and extreme precipitation events caused frequent fluctuations in lake water saturation, potentially providing ideal dynamic conditions for rapid and abundant dolomite formation. This combined control governed dolomite development and produced the interbedded lithological succession in the P₂l mixed sedimentary strata. This study integrates the dominant controlling factors and synergistic mechanisms of dolomite development in mixed sedimentary strata of continental saline lacustrine basins, which helps predict the occurrence and distribution of high-quality reservoir lithologies within such strata and has important implications for the optimization of “sweet spots” in shale oil exploration. Full article

This article presents the results of a field study conducted in 2022 on groundwater outflows located at the edge of the Kashubian Lake District and the Reda-Łeba Proglacial Stream Valley in northern Poland. The recharge of numerous springs was found to occur from the first aquifer, locally supported by a deeper aquifer connected to the first one near the bowl of Lubowidzkie Lake. Groundwater drainage occurs by gravity. It is relatively abundant for young glacial areas and averages 82 dm³·s⁻¹, making the springs capable of acting as a drinking water reservoir. This assessment is based on major ions and nutrients only; microbiological and trace-organic/metal analyses are required before any drinking-water designation. Spring water is important in the lake’s supply, accounting for 18.0% of the total inflow to the basin. The hydrochemical characteristics of these waters keep the lake in ecological balance. The waters from the springs are characterized by little variation in chemical composition, with the Ca-HCO₃ hydrochemical type. They represent young infiltration waters associated with direct recharge from precipitation (the average age of the water is 60 years). Currently, low nitrate and chloride suggest limited agricultural and urban influence, but phosphate levels and observed human activities warrant caution. Forest management is gradually developing in its catchment, which may result in a reduction of the spring yield and a deterioration of their quality in the future. This may result in a disturbance of the hydrological balance of structures hydraulically connected to spring recharge and to groundwater inflow (river, lake). Although the springs studied are local hydrological phenomena, their functioning and the need for protection are closely linked to global challenges in the field of sustainable development. This primarily concerns the protection of groundwater-dependent ecosystems and, more broadly, water security and increased resilience to climate change. Full article