Identifying geohazards such as landslides and methane leakage is crucial during gas extraction from natural gas hydrate(NGH)reservoirs,and understanding reservoir settlement behavior is central to this assessment.Hori...Identifying geohazards such as landslides and methane leakage is crucial during gas extraction from natural gas hydrate(NGH)reservoirs,and understanding reservoir settlement behavior is central to this assessment.Horizontal wells can enlarge the pressure relief zone within the formation,improving single-well productivity,and are therefore considered a promising approach for NGH development.This study examines the settlement response of hydrate-bearing sediments during depressurization using horizontal wells.A fully coupled thermal,hydraulic,mechanical,and chemical(THMC)model with representative reservoir properties(Shenhu region in the South China Sea)is presented accordingly.The simulations show that lower production pressures,while increasing gas output,also intensify formation settlement.The maximum difference in settlement between the lowest and highest production pressures reaches 0.016 m,contributing to more pronounced differential subsidence.Optimal well placement,specifically targeting a low-saturation hydrate zone containing free gas and situated adjacent to a high-saturation hydrate layer,markedly improves both gas production rate and cumulative yield,while reducing overall settlement and limiting changes in effective stress.展开更多
Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal sca...Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal scale tasks.In this study,we report an OECT-based neuromorphic device with tunable relaxation time(τ)by introducing an additional vertical back-gate electrode into a planar structure.The dual-gate design enablesτreconfiguration from 93 to 541 ms.The tunable relaxation behaviors can be attributed to the combined effects of planar-gate induced electrochemical doping and back-gateinduced electrostatic coupling,as verified by electrochemical impedance spectroscopy analysis.Furthermore,we used theτ-tunable OECT devices as physical reservoirs in the RC system for intelligent driving trajectory prediction,achieving a significant improvement in prediction accuracy from below 69%to 99%.The results demonstrate that theτ-tunable OECT shows a promising candidate for multi-temporal scale neuromorphic computing applications.展开更多
Neuromorphic devices have garnered significant attention as potential building blocks for energy-efficient hardware systems owing to their capacity to emulate the computational efficiency of the brain.In this regard,r...Neuromorphic devices have garnered significant attention as potential building blocks for energy-efficient hardware systems owing to their capacity to emulate the computational efficiency of the brain.In this regard,reservoir computing(RC)framework,which leverages straightforward training methods and efficient temporal signal processing,has emerged as a promising scheme.While various physical reservoir devices,including ferroelectric,optoelectronic,and memristor-based systems,have been demonstrated,many still face challenges related to compatibility with mainstream complementary metal oxide semiconductor(CMOS)integration processes.This study introduced a silicon-based schottky barrier metal-oxide-semiconductor field effect transistor(SB-MOSFET),which was fabricated under low thermal budget and compatible with back-end-of-line(BEOL).The device demonstrated short-term memory characteristics,facilitated by the modulation of schottky barriers and charge trapping.Utilizing these characteristics,a RC system for temporal data processing was constructed,and its performance was validated in a 5×4 digital classification task,achieving an accuracy exceeding 98%after 50 training epochs.Furthermore,the system successfully processed temporal signal in waveform classification and prediction tasks using time-division multiplexing.Overall,the SB-MOSFET's high compatibility with CMOS technology provides substantial advantages for large-scale integration,enabling the development of energy-efficient reservoir computing hardware.展开更多
Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-me...Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.展开更多
Microbial communities play indispensable roles in the biogeochemical cycling of river ecosystems.However,the response patterns of microbial community diversity,niche breadth,and assembly to rainfall disturbances in co...Microbial communities play indispensable roles in the biogeochemical cycling of river ecosystems.However,the response patterns of microbial community diversity,niche breadth,and assembly to rainfall disturbances in complex mountainous riverine reservoirs remain inadequately understood.We employed high-throughput sequencing of 16S and 18S ribosomal RNA genes,along with multivariate statistical methods to systematically investigate prokaryotic and eukaryotic microorganisms in the riverine Zhaoshandu Reservoir,Wenzhou,Zhejiang,East China.Results show significant temporal heterogeneity in both prokaryotic and eukaryotic microbial communities,with eukaryotic microbes showing more pronounced temporal variation.Canonical correspondence analysis revealed that rainfall and water temperature were the key drivers shaping microbial communities.Additionally,eukaryotic microorganisms exhibited a more pronounced response to rainfall and water temperature compared to prokaryotes.Modified stochasticity ratio model indicated that deterministic processes predominantly governed microbial community assembly,with stronger deterministic processes in eukaryotic compared to prokaryotic microorganisms.Rainfall has significantly altered water quality,notably increasing phosphorus concentration in the water column.Total phosphorus and total nitrogen showed significant correlations with the niche breadth of prokaryotic and eukaryotic microorganisms,and phosphorus nutrients served as keystones and playing indispensable roles in their co-occurrence networks.A structural equation model confirmed the notable impacts of rainfall and water temperature on microbial community diversity,further revealing that rainfall indirectly influenced the niche breadth and co-occurrence relationships of microbial communities by altering phosphorus concentrations.The findings underscore the influence of rainfall and water temperature on microbial distribution,highlighting the sensitivity of riverine reservoir ecosystems to climate change.展开更多
In recent years,significant breakthroughs have been achieved in the exploration of deep volcanic rocks in the Junggar Basin,highlighting their substantial exploration potential.The complex distribution of volcanic res...In recent years,significant breakthroughs have been achieved in the exploration of deep volcanic rocks in the Junggar Basin,highlighting their substantial exploration potential.The complex distribution of volcanic reservoirs is attributed to the multi-phase tectonic evolution within the basin,with their superior reservoir properties playing a crucial role in natural gas formation.However,due to the combined effects of multi-cyclic volcanic eruptions and tectonic activities,predicting volcanic facies distribution and favorable reservoirs remains highly challenging.This study focuses on the third member of the Jiamuhe Formation in the Zhongguai Uplift.By integrating drilling and petrophysical data with well-seismic analysis techniques,a seismic identification model for volcanic reservoirs has been established.The findings reveal that different facies exhibit distinct seismic response characteristics.Andesite,rhyolite,volcanic breccia,and volcanic clastic rocks show variability in amplitude,frequency,and continuity.Using structural-guided filtering,high-resolution coherence analysis,and 3D body carving techniques,the locations of volcanic craters and eruption centers were successfully identified,further clarifying the distribution patterns of volcanic facies.By combining multi-attribute clustering analysis and seismic attribute extraction,a volcanic facies zone distribution map was generated,and favorable exploration directions for volcanic reservoirs were proposed.The study provides technical guidance for the exploration of deep volcanic oil and gas reservoirs in the Junggar Basin and holds significant application value.展开更多
Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(TH...Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(THMD)coupled model was developed to describe the coupling between rock damage and mechanical,fluid flow and heat transfer fields.The model considers rock heterogeneity,and incorporates the Mohr-Coulomb failure criterion and the maximum tensile stress criterion to evaluate shear and tensile damage.This numerical modeling methodology was first verified against analytical solutions and experimental results,and was then used to simulate the THMD coupling behavior in deep geothermal exploitation.A coupled numerical model was set up to simulate the geothermal fluids extraction and re-injection process in a reservoir at 1 km depth over a 7-year period.Rock damage was found to accelerate the propagation of cold fronts away from the injection well,and have a distinct effect on the performance of geothermal exploitation.When the rock damage was considered,the field injectivity increases by 8.4 times,the range of cooled regions increases by 18.6 times,and the vertical deformation changes by 1.2 times after 7 years of geothermal operations,compared to the scenario where it was not considered.Parametric studies have suggested that thermal contraction dominates the rock damage evolution,and that thermal-induced rock damage only occurs at a sufficiently large temperature difference between fluids injected and the reservoir.This work underscores the importance of accurately accounting for the damage effect on reservoir response during fluid injection activities that cause significant cooling of reservoir rocks.展开更多
Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the ten...Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the tensile stress in the area has exceeded the tensile strength of the soil,leading to local instability.To explore the impact of tensile failure behavior on the stability and failure modes of reservoir landslides,the Huangtupo Riverside Slump#1 is taken as a case study.By considering local tensile failure,potential tensile cracks are incorporated into the analysis via the limit equilibrium method and reliability theory.The reliability of landslides under different tensile failure scenarios is quantified.Strain-softening characteristics of the soil are combined to further analyze the failure transmission path of the landslide.Finally,these potential failure modes were validated through physical model tests.The results show that cracks developing at rear positions reduce the stability of the slope and increase the probability of instability.During the destruction process,retrogressive failures with multiple sliding surfaces are likely to occur.However,tensile failure at the forefront reduces the likelihood of an individual slide mass descending.Progressive failure results in both regular and skip transmission patterns.Additionally,cracks and water level changes can also lead to shifts in the positions of the most dangerous blocks.Therefore,in practical landslide analysis and prevention,it is necessary to consider local tensile damage and identify potential tensile crack locations in advance to optimize prevention measures and accurately evaluate landslide risk.展开更多
With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has ...With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has broad potential for improving production efficiency.Currently,the Jiyuan Oilfield in the Ordos Basin relies mainly on manual reprocessing and interpretation of old well logging data to identify different fluid types in low-contrast reservoirs,guiding subsequent production work.This study uses well logging data from the Chang 1 reservoir,partitioning the dataset based on individual wells for model training and testing.A deep learning model for intelligent reservoir fluid identification was constructed by incorporating the focal loss function.Comparative validations with five other models,including logistic regression(LR),naive Bayes(NB),gradient boosting decision trees(GBDT),random forest(RF),and support vector machine(SVM),show that this model demonstrates superior identification performance and significantly improves the accuracy of identifying oil-bearing fluids.Mutual information analysis reveals the model's differential dependency on various logging parameters for reservoir fluid identification.This model provides important references and a basis for conducting regional studies and revisiting old wells,demonstrating practical value that can be widely applied.展开更多
Coal mine underground reservoirs help address the severe water imbalance in ecologically fragile mining regions of western China,but evaluating their storage capacity remains challenging due to the coupled effects of ...Coal mine underground reservoirs help address the severe water imbalance in ecologically fragile mining regions of western China,but evaluating their storage capacity remains challenging due to the coupled effects of gangue deformation,saturation,and goaf geometry.This study investigates the deformation and void evolution of fragmented gangue with varying lithologies,particle sizes,and water contents through an independent-developed testing system and theoretical model.A planar micro-unit model and a three-dimensional spatial structure model are proposed to quantify the storage coefficient and total reservoir capacity of underground water storage structures.These models incorporate the effects of stratified lithologies,saturation-induced softening,and spatially distributed stress conditions.The methodology is applied to the underground reservoir in Chahasu coal mine,and the results show that under increasing stress,storage coefficients decline exponentially,with pronounced differences between single-and double-lithology structures.The storage coefficient in the spatial model demonstrate greater resilience to stress concentration compared to planar models,and further analysis identifies critical thresholds in roof fracture distances and stress-recovery times affecting long-term storage performance.This research provides a comprehensive framework for evaluating underground reservoir storage potential,offering theoretical support and engineering guidance for the sustainable utilization of mine water.展开更多
The strong vertical discontinuities pose a fundamental challenge to optimizing stimulated reservoir volume(SRV)in multilayered reservoirs.This research proposes a radial borehole-assisted horizontal well fracturing te...The strong vertical discontinuities pose a fundamental challenge to optimizing stimulated reservoir volume(SRV)in multilayered reservoirs.This research proposes a radial borehole-assisted horizontal well fracturing technology,which is expected to achieve effective vertical stimulation and commingled production across multiple pay zones.Under different geological and engineering conditions,the vertical propagation behavior of hydraulic fractures guided by radial boreholes can be determined by adjusting the interlayered lithologies and radial borehole configurations in experimental samples.Experimental results reveal four fracture network patterns:passivated,cross-layer,skip-layer,and hybrid fractures in the radial borehole fracturing.The radial boreholes perform better fracture guiding performances in the high-brittleness interlayers,which form cross-layer and hybrid fracture networks to improve the growth height.Hydraulic fractures tend to propagate from high-strength to low-strength layers under radial borehole guidance.When radial boreholes interconnect multiple lithology layers,hydraulic fractures initiate preferentially in lower-strength zones rather than remaining confined to borehole root ends.Increased radial borehole length and diameter facilitate fracture skip-layer initiation and cross-layer propagation,while multiple borehole branches enhance fracture penetration across high-strength interlayers.Radial boreholes with inclination angles below 30°enhance fracture height by generating cross-layer and hybrid fracture networks.Furthermore,an inter-borehole phase angle of less than 180°facilitates single-wing fracture cross-layer propagation.Fracture height is primarily governed by radial borehole length,followed by quantity,inclination angle,and diameter.Based on the geometric similarity criteria,the recommended parameters for radial borehole-assisted fracturing in a 5 1/2-inch horizontal well include a length>15 m,an inclination angle<30°,and a diameter>52 mm to ensure effective stimulation across three or more pay zones.Finally,the field-scale numerical model was developed to simulate the optimized radial borehole fracturing and demonstrate the technical superiority.These findings are expected to provide an in-depth understanding of the effective stimulation in multilayered reservoirs.展开更多
Landslide susceptibility mapping(LSM)is an essential tool for mitigating the escalating global risk of landslides.However,challenges such as the heterogeneity of different landslide triggers,extensive engineering acti...Landslide susceptibility mapping(LSM)is an essential tool for mitigating the escalating global risk of landslides.However,challenges such as the heterogeneity of different landslide triggers,extensive engineering activities exacerbated reactivation,and the interpretability of data-driven models have hindered the practical application of LSM.This work proposes a novel framework for enhancing LSM considering different triggers for accumulation and rock landslides,leveraging interpretable machine learning and Multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR)technology.Initially,a refined fieldinvestigation was conducted to delineate the accumulation and rock area according to landslide types,leading to the identificationof relevant contributing factors.Deformation along the slope was then combined with time-series analysis to derive a landslide activity level(AL)index to recognize the likelihood of reactivation or dormancy.The SHapley Additive exPlanation(SHAP)technique facilitated the interpretation of factors and the identificationof determinants in high susceptibility areas.The results indicate that random forest(RF)outperformed other models in both accumulation and rock areas.Key factors including thickness and weak intercalation were identifiedfor accumulation and rock landslides.The introduction of AL substantially enhanced the predictive capability of the LSM and outperformed models that neglect movement trends or deformation rates with an average ratio of 81.23%in high susceptibility zones.Besides,the fieldvalidation confirmedthat 83.8%of newly identifiedlandslides were correctly upgraded.Given its efficiencyand operational simplicity,the proposed hybrid model opens new avenues for the feasibility of enhancement in LSM at urban settlements worldwide.展开更多
Carbonate gas reservoirs are often characterized by strong heterogeneity,complex inter-well connectivity,extensive edge or bottom water,and unbalanced production,challenges that are also common in many heterogeneous g...Carbonate gas reservoirs are often characterized by strong heterogeneity,complex inter-well connectivity,extensive edge or bottom water,and unbalanced production,challenges that are also common in many heterogeneous gas reservoirs with intricate storage and flow behavior.To address these issues within a unified,data-driven framework,this study develops a multi-block material balance model that accounts for inter-block flow and aquifer influx,and is applicable to a wide range of reservoir types.The model incorporates inter-well and well-group conductive connectivity together with pseudo–steady-state aquifer support.The governing equations are solved using a Newton–Raphson scheme,while particle swarm optimization is employed to estimate formation pressures,inter-well connectivity,and effective aquifer volumes.An unbalanced exploitation factor,UEF,is introduced to quantify production imbalance and to guide development optimization.Validation using a synthetic reservoir model demonstrates that the approach accurately reproduces pressure evolution,crossflow behavior,and water influx.Application to a representative case(the Longwangmiao)field further confirms its robustness under highly heterogeneous conditions,achieving a 12.9%reduction in UEF through optimized production allocation.展开更多
This paper discusses the characteristics and formation mechanism of thin dolomite reservoirs in the lower submember of the second member of the Permian Maokou Formation(lower Mao 2 Member)in the Wusheng-Tongnan area o...This paper discusses the characteristics and formation mechanism of thin dolomite reservoirs in the lower submember of the second member of the Permian Maokou Formation(lower Mao 2 Member)in the Wusheng-Tongnan area of the Sichuan Basin,SW China,through comprehensive analysis of geological,geophysical and geochemical data.The reservoir rocks of the lower Mao 2 Member are dominated by porphyritic vuggy dolomite and calcareous dolomite or dolomitic limestone,which have typical karst characteristics of early diagenetic stage.The dolomites at the edge of the karst system and in the fillings have dissolved estuaries,and the dolomite breccia has micrite envelope and rim cement at the edge,indicating that dolomitization is earlier than the early diagenetic karstification.The shoal facies laminated dolomite is primarily formed by the seepage reflux dolomitization of moderate-salinity seawater.The key factors of reservoir formation are the bioclastic shoal deposition superimposed with seepgae reflux dolomitization and the karstification of early diagenetic stage,which are locally reformed by fractures and hydrothermal processes.The development of dolomite vuggy reservoir is closely related to the upward-shallowing sequence,and mainly occurs in the late highstand of the fourth-order cycle.Moreover,the size of dolomite is closely related to formation thickness,and it is concentrated in the formation thickness conversion area,followed by the thinner area.According to the understanding of insufficient accommodation space in the geomorphic highland and the migration of granular shoal to geomorphic lowland in the late highstand of the third-order cycle,it is proposed that the large-scale shoal-controlled dolomite reservoirs are distributed along structural highs and slopes,and the reservoir-forming model with shoal,dolomitization and karstification jointly controlled by the microgeomorphy and sea-level fluctuation in the sedimentary period is established.On this basis,the paleogeomorphology in the lower Mao 2 Member is restored using well-seismic data,and the reservoir distribution is predicted.The prediction results have been verified by the latest results of exploration wells and tests,which provide an important reference for the prediction of thin dolomite reservoirs under similar geological setting.展开更多
The physical properties of hydrocarbon reservoirs are important factors affecting the percolation ability of the reservoirs.Tight-sand reservoirs exhibit complex pore throat connectivity due to the extensive developme...The physical properties of hydrocarbon reservoirs are important factors affecting the percolation ability of the reservoirs.Tight-sand reservoirs exhibit complex pore throat connectivity due to the extensive development of micro-and nano-scale pore and throat systems.Characterizing the microscopic properties of these reservoirs using nondestructive,quantitative methods serves as an important means to determine the characteristics of microscopic pores and throats in tight-sand reservoirs and the mechanism behind the influence of these characteristics on reservoir porosity and permeability.In this study,a low-permeability sandstone sample and two tight sandstone samples collected from the Ordos Basin were nondestructively tested using high-resolution nano-CT technology to quantitively characterize their microscopic pore throat structures and model them three-dimensionally(in 3D)based on CT threshold differences and gray models.A thorough analysis and comparison reveal that the three samples exhibit a certain positive correlation between their porosity and permeability but the most important factor affecting both porosity and permeability is the microscopic pore throat structure.Although the number of pores in tight sandstones shows a minor impact on their porosity,large pores(more than 20μm)contribute predominantly to porosity,suggesting that the permeability of tight sandstones is controlled primarily by large pore throats.For these samples,higher permeability corresponds to larger average throat sizes.Therefore,throats with average radii greater than 2μm can significantly improve the permeability of tight sandstones.展开更多
The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers.However,little information is av...The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers.However,little information is available on how the rainfall affect nutrient dynamics in subtropicalmontane rivers with complex land use.This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu,a montane reservoir of southeast China.The results showed that riverine total nitrogen(TN)and total phosphorus(TP)concentrations increased continuously with increasing rainfall intensity,while TN:TP decreased.The heavy rainfall and rainstorm drove more than 30%of the annual N and P loading in only 5.20%of the total rainfall period,indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs.NO_(3)^(−)-N is the primary nitrogen form lost,while particulate phosphorus(PP)dominated phosphorus loss.Themain source of N is cropland,and themain source of P is residential area.Spatially,forestedwatersheds have better drainage quality,while it is still a potential source of nonpoint pollution during rainfall events.TN and TP concentrations were significantly higher at sites dominated by cropland and residential area,indicating their substantial contributions to deteriorating river water quality.Temporally,TN and TP concentrations reached high values in May-August when rainfall was most intense,while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities.The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads,providing guidance for nutrient load reduction planning for Lake Qiandaohu.展开更多
Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic ...Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.展开更多
The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion...The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion system analysis and in situ U-Pb dating,the sequence of tight sandstone reservoir densification and oil charging was determined.Through petrological observations,fluid inclusion analysis and physical property analysis,it is concluded that compaction and cementation are the primary causes of reservoir densification.When the content of calcite cement is less than or equal to 7%,compaction dominates densification;otherwise,cementation becomes more significant.However,determining the exact timing of compaction densification proved challenging.Microscopic observations revealed that oil charging likely occurred either before or during the densification of the reservoir.According to in situ U-Pb dating and the porosity evolution curve,cementation densification occurred between 167.0±20.0 Ma and 151.8 Ma.Temperature measurements of the aqueous inclusions indicate that oil charging occurred between 125.0 and 96.0 Ma,suggesting that densification preceded oil charging.This study provides valuable insights for the future exploration of tight oil reservoirs in the Ordos Basin.展开更多
Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While suc...Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.展开更多
Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based ...Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.展开更多
基金supported by the State Key Research Development Program of China(Grant No.2021YFC2800905-02)the National Natural Science Foundation of China(Grant No.52304208)。
文摘Identifying geohazards such as landslides and methane leakage is crucial during gas extraction from natural gas hydrate(NGH)reservoirs,and understanding reservoir settlement behavior is central to this assessment.Horizontal wells can enlarge the pressure relief zone within the formation,improving single-well productivity,and are therefore considered a promising approach for NGH development.This study examines the settlement response of hydrate-bearing sediments during depressurization using horizontal wells.A fully coupled thermal,hydraulic,mechanical,and chemical(THMC)model with representative reservoir properties(Shenhu region in the South China Sea)is presented accordingly.The simulations show that lower production pressures,while increasing gas output,also intensify formation settlement.The maximum difference in settlement between the lowest and highest production pressures reaches 0.016 m,contributing to more pronounced differential subsidence.Optimal well placement,specifically targeting a low-saturation hydrate zone containing free gas and situated adjacent to a high-saturation hydrate layer,markedly improves both gas production rate and cumulative yield,while reducing overall settlement and limiting changes in effective stress.
基金supported by the National Key Research and Development Program of China under Grant 2022YFB3608300in part by the National Nature Science Foundation of China(NSFC)under Grants 62404050,U2341218,62574056,62204052。
文摘Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal scale tasks.In this study,we report an OECT-based neuromorphic device with tunable relaxation time(τ)by introducing an additional vertical back-gate electrode into a planar structure.The dual-gate design enablesτreconfiguration from 93 to 541 ms.The tunable relaxation behaviors can be attributed to the combined effects of planar-gate induced electrochemical doping and back-gateinduced electrostatic coupling,as verified by electrochemical impedance spectroscopy analysis.Furthermore,we used theτ-tunable OECT devices as physical reservoirs in the RC system for intelligent driving trajectory prediction,achieving a significant improvement in prediction accuracy from below 69%to 99%.The results demonstrate that theτ-tunable OECT shows a promising candidate for multi-temporal scale neuromorphic computing applications.
基金supported in part by the Chinese Academy of Sciences(No.XDA0330302)NSFC program(No.22127901)。
文摘Neuromorphic devices have garnered significant attention as potential building blocks for energy-efficient hardware systems owing to their capacity to emulate the computational efficiency of the brain.In this regard,reservoir computing(RC)framework,which leverages straightforward training methods and efficient temporal signal processing,has emerged as a promising scheme.While various physical reservoir devices,including ferroelectric,optoelectronic,and memristor-based systems,have been demonstrated,many still face challenges related to compatibility with mainstream complementary metal oxide semiconductor(CMOS)integration processes.This study introduced a silicon-based schottky barrier metal-oxide-semiconductor field effect transistor(SB-MOSFET),which was fabricated under low thermal budget and compatible with back-end-of-line(BEOL).The device demonstrated short-term memory characteristics,facilitated by the modulation of schottky barriers and charge trapping.Utilizing these characteristics,a RC system for temporal data processing was constructed,and its performance was validated in a 5×4 digital classification task,achieving an accuracy exceeding 98%after 50 training epochs.Furthermore,the system successfully processed temporal signal in waveform classification and prediction tasks using time-division multiplexing.Overall,the SB-MOSFET's high compatibility with CMOS technology provides substantial advantages for large-scale integration,enabling the development of energy-efficient reservoir computing hardware.
基金supported by Guangdong Basic and Applied Basic Research Foundation(Nos.2023A1515110824 and 2025A1515011839)Shenzhen Science and Technology Program(No.RCBS20231211090638066).
文摘Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China(No.LD21C030001)the Key Research and Development Program of National Natural Science Foundation of China(No.2021YFE0112000)+1 种基金the National Natural Science Foundation of China(Nos.32371634,31970219)the Scientific Research Project of the Shanghai Municipal Bureau of Ecology and Environment(No.202409)。
文摘Microbial communities play indispensable roles in the biogeochemical cycling of river ecosystems.However,the response patterns of microbial community diversity,niche breadth,and assembly to rainfall disturbances in complex mountainous riverine reservoirs remain inadequately understood.We employed high-throughput sequencing of 16S and 18S ribosomal RNA genes,along with multivariate statistical methods to systematically investigate prokaryotic and eukaryotic microorganisms in the riverine Zhaoshandu Reservoir,Wenzhou,Zhejiang,East China.Results show significant temporal heterogeneity in both prokaryotic and eukaryotic microbial communities,with eukaryotic microbes showing more pronounced temporal variation.Canonical correspondence analysis revealed that rainfall and water temperature were the key drivers shaping microbial communities.Additionally,eukaryotic microorganisms exhibited a more pronounced response to rainfall and water temperature compared to prokaryotes.Modified stochasticity ratio model indicated that deterministic processes predominantly governed microbial community assembly,with stronger deterministic processes in eukaryotic compared to prokaryotic microorganisms.Rainfall has significantly altered water quality,notably increasing phosphorus concentration in the water column.Total phosphorus and total nitrogen showed significant correlations with the niche breadth of prokaryotic and eukaryotic microorganisms,and phosphorus nutrients served as keystones and playing indispensable roles in their co-occurrence networks.A structural equation model confirmed the notable impacts of rainfall and water temperature on microbial community diversity,further revealing that rainfall indirectly influenced the niche breadth and co-occurrence relationships of microbial communities by altering phosphorus concentrations.The findings underscore the influence of rainfall and water temperature on microbial distribution,highlighting the sensitivity of riverine reservoir ecosystems to climate change.
文摘In recent years,significant breakthroughs have been achieved in the exploration of deep volcanic rocks in the Junggar Basin,highlighting their substantial exploration potential.The complex distribution of volcanic reservoirs is attributed to the multi-phase tectonic evolution within the basin,with their superior reservoir properties playing a crucial role in natural gas formation.However,due to the combined effects of multi-cyclic volcanic eruptions and tectonic activities,predicting volcanic facies distribution and favorable reservoirs remains highly challenging.This study focuses on the third member of the Jiamuhe Formation in the Zhongguai Uplift.By integrating drilling and petrophysical data with well-seismic analysis techniques,a seismic identification model for volcanic reservoirs has been established.The findings reveal that different facies exhibit distinct seismic response characteristics.Andesite,rhyolite,volcanic breccia,and volcanic clastic rocks show variability in amplitude,frequency,and continuity.Using structural-guided filtering,high-resolution coherence analysis,and 3D body carving techniques,the locations of volcanic craters and eruption centers were successfully identified,further clarifying the distribution patterns of volcanic facies.By combining multi-attribute clustering analysis and seismic attribute extraction,a volcanic facies zone distribution map was generated,and favorable exploration directions for volcanic reservoirs were proposed.The study provides technical guidance for the exploration of deep volcanic oil and gas reservoirs in the Junggar Basin and holds significant application value.
基金funded by the Major National Science and Technology Project for Deep Earth of China(Grant No.2024ZD1003805)the National Natural Science Foundation of China(Grant Nos.52311530070 and 52004015).
文摘Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(THMD)coupled model was developed to describe the coupling between rock damage and mechanical,fluid flow and heat transfer fields.The model considers rock heterogeneity,and incorporates the Mohr-Coulomb failure criterion and the maximum tensile stress criterion to evaluate shear and tensile damage.This numerical modeling methodology was first verified against analytical solutions and experimental results,and was then used to simulate the THMD coupling behavior in deep geothermal exploitation.A coupled numerical model was set up to simulate the geothermal fluids extraction and re-injection process in a reservoir at 1 km depth over a 7-year period.Rock damage was found to accelerate the propagation of cold fronts away from the injection well,and have a distinct effect on the performance of geothermal exploitation.When the rock damage was considered,the field injectivity increases by 8.4 times,the range of cooled regions increases by 18.6 times,and the vertical deformation changes by 1.2 times after 7 years of geothermal operations,compared to the scenario where it was not considered.Parametric studies have suggested that thermal contraction dominates the rock damage evolution,and that thermal-induced rock damage only occurs at a sufficiently large temperature difference between fluids injected and the reservoir.This work underscores the importance of accurately accounting for the damage effect on reservoir response during fluid injection activities that cause significant cooling of reservoir rocks.
基金supported by the Major Program of National Natural Science Foundation of China(Grant No.42090055)the National Key ScientificInstruments and Equipment Development Projects of China(Grant No.41827808)the National Nature Science Foundation of China(Grant No.42207216).
文摘Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the tensile stress in the area has exceeded the tensile strength of the soil,leading to local instability.To explore the impact of tensile failure behavior on the stability and failure modes of reservoir landslides,the Huangtupo Riverside Slump#1 is taken as a case study.By considering local tensile failure,potential tensile cracks are incorporated into the analysis via the limit equilibrium method and reliability theory.The reliability of landslides under different tensile failure scenarios is quantified.Strain-softening characteristics of the soil are combined to further analyze the failure transmission path of the landslide.Finally,these potential failure modes were validated through physical model tests.The results show that cracks developing at rear positions reduce the stability of the slope and increase the probability of instability.During the destruction process,retrogressive failures with multiple sliding surfaces are likely to occur.However,tensile failure at the forefront reduces the likelihood of an individual slide mass descending.Progressive failure results in both regular and skip transmission patterns.Additionally,cracks and water level changes can also lead to shifts in the positions of the most dangerous blocks.Therefore,in practical landslide analysis and prevention,it is necessary to consider local tensile damage and identify potential tensile crack locations in advance to optimize prevention measures and accurately evaluate landslide risk.
基金supported by a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918 and 202103)。
文摘With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has broad potential for improving production efficiency.Currently,the Jiyuan Oilfield in the Ordos Basin relies mainly on manual reprocessing and interpretation of old well logging data to identify different fluid types in low-contrast reservoirs,guiding subsequent production work.This study uses well logging data from the Chang 1 reservoir,partitioning the dataset based on individual wells for model training and testing.A deep learning model for intelligent reservoir fluid identification was constructed by incorporating the focal loss function.Comparative validations with five other models,including logistic regression(LR),naive Bayes(NB),gradient boosting decision trees(GBDT),random forest(RF),and support vector machine(SVM),show that this model demonstrates superior identification performance and significantly improves the accuracy of identifying oil-bearing fluids.Mutual information analysis reveals the model's differential dependency on various logging parameters for reservoir fluid identification.This model provides important references and a basis for conducting regional studies and revisiting old wells,demonstrating practical value that can be widely applied.
基金supported by the National Natural Science Foundation of China(Nos.52404153,52504157 and 52504156)the Natural Science Foundation of Jiangsu Province(No.BK20241649).
文摘Coal mine underground reservoirs help address the severe water imbalance in ecologically fragile mining regions of western China,but evaluating their storage capacity remains challenging due to the coupled effects of gangue deformation,saturation,and goaf geometry.This study investigates the deformation and void evolution of fragmented gangue with varying lithologies,particle sizes,and water contents through an independent-developed testing system and theoretical model.A planar micro-unit model and a three-dimensional spatial structure model are proposed to quantify the storage coefficient and total reservoir capacity of underground water storage structures.These models incorporate the effects of stratified lithologies,saturation-induced softening,and spatially distributed stress conditions.The methodology is applied to the underground reservoir in Chahasu coal mine,and the results show that under increasing stress,storage coefficients decline exponentially,with pronounced differences between single-and double-lithology structures.The storage coefficient in the spatial model demonstrate greater resilience to stress concentration compared to planar models,and further analysis identifies critical thresholds in roof fracture distances and stress-recovery times affecting long-term storage performance.This research provides a comprehensive framework for evaluating underground reservoir storage potential,offering theoretical support and engineering guidance for the sustainable utilization of mine water.
基金supported by the National Natural Science Foundation of China(Nos.U24B6001,52421002,52474016,and 52020105001)Research on Key Technologies for Exploration and Development of Dry Geothermal Resources(No.2022DJ5503)Deep-land National Science and Technology Major Project of China(No.2024ZD1003504).
文摘The strong vertical discontinuities pose a fundamental challenge to optimizing stimulated reservoir volume(SRV)in multilayered reservoirs.This research proposes a radial borehole-assisted horizontal well fracturing technology,which is expected to achieve effective vertical stimulation and commingled production across multiple pay zones.Under different geological and engineering conditions,the vertical propagation behavior of hydraulic fractures guided by radial boreholes can be determined by adjusting the interlayered lithologies and radial borehole configurations in experimental samples.Experimental results reveal four fracture network patterns:passivated,cross-layer,skip-layer,and hybrid fractures in the radial borehole fracturing.The radial boreholes perform better fracture guiding performances in the high-brittleness interlayers,which form cross-layer and hybrid fracture networks to improve the growth height.Hydraulic fractures tend to propagate from high-strength to low-strength layers under radial borehole guidance.When radial boreholes interconnect multiple lithology layers,hydraulic fractures initiate preferentially in lower-strength zones rather than remaining confined to borehole root ends.Increased radial borehole length and diameter facilitate fracture skip-layer initiation and cross-layer propagation,while multiple borehole branches enhance fracture penetration across high-strength interlayers.Radial boreholes with inclination angles below 30°enhance fracture height by generating cross-layer and hybrid fracture networks.Furthermore,an inter-borehole phase angle of less than 180°facilitates single-wing fracture cross-layer propagation.Fracture height is primarily governed by radial borehole length,followed by quantity,inclination angle,and diameter.Based on the geometric similarity criteria,the recommended parameters for radial borehole-assisted fracturing in a 5 1/2-inch horizontal well include a length>15 m,an inclination angle<30°,and a diameter>52 mm to ensure effective stimulation across three or more pay zones.Finally,the field-scale numerical model was developed to simulate the optimized radial borehole fracturing and demonstrate the technical superiority.These findings are expected to provide an in-depth understanding of the effective stimulation in multilayered reservoirs.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3007201)the National Natural Science Foundation of China(Grant No.42377161)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB 2024ZR03).
文摘Landslide susceptibility mapping(LSM)is an essential tool for mitigating the escalating global risk of landslides.However,challenges such as the heterogeneity of different landslide triggers,extensive engineering activities exacerbated reactivation,and the interpretability of data-driven models have hindered the practical application of LSM.This work proposes a novel framework for enhancing LSM considering different triggers for accumulation and rock landslides,leveraging interpretable machine learning and Multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR)technology.Initially,a refined fieldinvestigation was conducted to delineate the accumulation and rock area according to landslide types,leading to the identificationof relevant contributing factors.Deformation along the slope was then combined with time-series analysis to derive a landslide activity level(AL)index to recognize the likelihood of reactivation or dormancy.The SHapley Additive exPlanation(SHAP)technique facilitated the interpretation of factors and the identificationof determinants in high susceptibility areas.The results indicate that random forest(RF)outperformed other models in both accumulation and rock areas.Key factors including thickness and weak intercalation were identifiedfor accumulation and rock landslides.The introduction of AL substantially enhanced the predictive capability of the LSM and outperformed models that neglect movement trends or deformation rates with an average ratio of 81.23%in high susceptibility zones.Besides,the fieldvalidation confirmedthat 83.8%of newly identifiedlandslides were correctly upgraded.Given its efficiencyand operational simplicity,the proposed hybrid model opens new avenues for the feasibility of enhancement in LSM at urban settlements worldwide.
基金supported by the National Natural Science Foundation of China(No.52104018,52274030)China National Petroleum Corporation(CNPC)Innovation Foundation(No.2024DQ02-0303)China National Petroleum Corporation(CNPC)14th Five-Year Plan Major Strategic Scientific and Technological Project for Prospective and Fundamental Research(2024DJ86).
文摘Carbonate gas reservoirs are often characterized by strong heterogeneity,complex inter-well connectivity,extensive edge or bottom water,and unbalanced production,challenges that are also common in many heterogeneous gas reservoirs with intricate storage and flow behavior.To address these issues within a unified,data-driven framework,this study develops a multi-block material balance model that accounts for inter-block flow and aquifer influx,and is applicable to a wide range of reservoir types.The model incorporates inter-well and well-group conductive connectivity together with pseudo–steady-state aquifer support.The governing equations are solved using a Newton–Raphson scheme,while particle swarm optimization is employed to estimate formation pressures,inter-well connectivity,and effective aquifer volumes.An unbalanced exploitation factor,UEF,is introduced to quantify production imbalance and to guide development optimization.Validation using a synthetic reservoir model demonstrates that the approach accurately reproduces pressure evolution,crossflow behavior,and water influx.Application to a representative case(the Longwangmiao)field further confirms its robustness under highly heterogeneous conditions,achieving a 12.9%reduction in UEF through optimized production allocation.
基金Supported by the National Natural Science Foundation of China(42172166)National Natural Science Foundation and CNPC Joint Fund Project(U23B20154)CNPC-Southwest Petroleum University Science and Technology Cooperation Project(2020CX010000).
文摘This paper discusses the characteristics and formation mechanism of thin dolomite reservoirs in the lower submember of the second member of the Permian Maokou Formation(lower Mao 2 Member)in the Wusheng-Tongnan area of the Sichuan Basin,SW China,through comprehensive analysis of geological,geophysical and geochemical data.The reservoir rocks of the lower Mao 2 Member are dominated by porphyritic vuggy dolomite and calcareous dolomite or dolomitic limestone,which have typical karst characteristics of early diagenetic stage.The dolomites at the edge of the karst system and in the fillings have dissolved estuaries,and the dolomite breccia has micrite envelope and rim cement at the edge,indicating that dolomitization is earlier than the early diagenetic karstification.The shoal facies laminated dolomite is primarily formed by the seepage reflux dolomitization of moderate-salinity seawater.The key factors of reservoir formation are the bioclastic shoal deposition superimposed with seepgae reflux dolomitization and the karstification of early diagenetic stage,which are locally reformed by fractures and hydrothermal processes.The development of dolomite vuggy reservoir is closely related to the upward-shallowing sequence,and mainly occurs in the late highstand of the fourth-order cycle.Moreover,the size of dolomite is closely related to formation thickness,and it is concentrated in the formation thickness conversion area,followed by the thinner area.According to the understanding of insufficient accommodation space in the geomorphic highland and the migration of granular shoal to geomorphic lowland in the late highstand of the third-order cycle,it is proposed that the large-scale shoal-controlled dolomite reservoirs are distributed along structural highs and slopes,and the reservoir-forming model with shoal,dolomitization and karstification jointly controlled by the microgeomorphy and sea-level fluctuation in the sedimentary period is established.On this basis,the paleogeomorphology in the lower Mao 2 Member is restored using well-seismic data,and the reservoir distribution is predicted.The prediction results have been verified by the latest results of exploration wells and tests,which provide an important reference for the prediction of thin dolomite reservoirs under similar geological setting.
文摘The physical properties of hydrocarbon reservoirs are important factors affecting the percolation ability of the reservoirs.Tight-sand reservoirs exhibit complex pore throat connectivity due to the extensive development of micro-and nano-scale pore and throat systems.Characterizing the microscopic properties of these reservoirs using nondestructive,quantitative methods serves as an important means to determine the characteristics of microscopic pores and throats in tight-sand reservoirs and the mechanism behind the influence of these characteristics on reservoir porosity and permeability.In this study,a low-permeability sandstone sample and two tight sandstone samples collected from the Ordos Basin were nondestructively tested using high-resolution nano-CT technology to quantitively characterize their microscopic pore throat structures and model them three-dimensionally(in 3D)based on CT threshold differences and gray models.A thorough analysis and comparison reveal that the three samples exhibit a certain positive correlation between their porosity and permeability but the most important factor affecting both porosity and permeability is the microscopic pore throat structure.Although the number of pores in tight sandstones shows a minor impact on their porosity,large pores(more than 20μm)contribute predominantly to porosity,suggesting that the permeability of tight sandstones is controlled primarily by large pore throats.For these samples,higher permeability corresponds to larger average throat sizes.Therefore,throats with average radii greater than 2μm can significantly improve the permeability of tight sandstones.
基金supported by the National Natural Science Foundation of China(Nos.U2340209,and 42271126)the NIGLAS Foundation(No.NIGLAS2022GS03)+1 种基金the Natural Science Foundation of Jiangsu Province(No.BK20220041)the US National Science Foundation Projects(Nos.1831096,1803697,and 2108917).
文摘The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers.However,little information is available on how the rainfall affect nutrient dynamics in subtropicalmontane rivers with complex land use.This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu,a montane reservoir of southeast China.The results showed that riverine total nitrogen(TN)and total phosphorus(TP)concentrations increased continuously with increasing rainfall intensity,while TN:TP decreased.The heavy rainfall and rainstorm drove more than 30%of the annual N and P loading in only 5.20%of the total rainfall period,indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs.NO_(3)^(−)-N is the primary nitrogen form lost,while particulate phosphorus(PP)dominated phosphorus loss.Themain source of N is cropland,and themain source of P is residential area.Spatially,forestedwatersheds have better drainage quality,while it is still a potential source of nonpoint pollution during rainfall events.TN and TP concentrations were significantly higher at sites dominated by cropland and residential area,indicating their substantial contributions to deteriorating river water quality.Temporally,TN and TP concentrations reached high values in May-August when rainfall was most intense,while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities.The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads,providing guidance for nutrient load reduction planning for Lake Qiandaohu.
基金supported by the"Science and Technology Development Plan Project of Jilin Province,China"(Grant No.20240101018JJ)the Fundamental Research Funds for the Central Universities(Grant No.2412023YQ004)the National Natural Science Foundation of China(Grant Nos.52072065,52272140,52372137,and U23A20568).
文摘Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.
基金supported by the project of the Exploration Department of the Huabei Oilfield Company of Sinopec(No.34550008-20-ZC0609-0031).
文摘The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion system analysis and in situ U-Pb dating,the sequence of tight sandstone reservoir densification and oil charging was determined.Through petrological observations,fluid inclusion analysis and physical property analysis,it is concluded that compaction and cementation are the primary causes of reservoir densification.When the content of calcite cement is less than or equal to 7%,compaction dominates densification;otherwise,cementation becomes more significant.However,determining the exact timing of compaction densification proved challenging.Microscopic observations revealed that oil charging likely occurred either before or during the densification of the reservoir.According to in situ U-Pb dating and the porosity evolution curve,cementation densification occurred between 167.0±20.0 Ma and 151.8 Ma.Temperature measurements of the aqueous inclusions indicate that oil charging occurred between 125.0 and 96.0 Ma,suggesting that densification preceded oil charging.This study provides valuable insights for the future exploration of tight oil reservoirs in the Ordos Basin.
基金National Natural Science Foundation of China(62171305,62405206,62004135,62001317,62111530301)Natural Science Foundation of Jiangsu Province(BK20240778,BK20241917)+3 种基金State Key Laboratory of Advanced Optical Communication Systems and Networks,China(2023GZKF08)China Postdoctoral Science Foundation(2024M752314)Postdoctoral Fellowship Program of CPSF(GZC20231883)Innovative and Entrepreneurial Talent Program of Jiangsu Province(JSSCRC2021527).
文摘Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.
基金supported by the National Key R&D Program of China(Grant No.2022YFC3005401)the National Natural Science Foundation of China(Grant No.52239009)。
文摘Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.
