Objective Oil-source faults have an important effect on reservoir formation and distribution in shallow formations with non- hydrocarbon generation in oil-rich fault-related basins （Jiang Youlu et al., 2015）. Howev...Objective Oil-source faults have an important effect on reservoir formation and distribution in shallow formations with non- hydrocarbon generation in oil-rich fault-related basins （Jiang Youlu et al., 2015）. However, the fault transporting capacity cannot be evaluated quantitatively at present. Taking the Zhanhua Sag in the Bohai Bay Basin as an example, this work analyzed the factors influencing the transporting capacity of the oil-source faults and proposed a quantitative method for evaluating their transporting capacity.展开更多
Oil and gas exploration near faults in shallow strata is investigated in this study based on an analysis of oil-source faults in reservoire-cap rock combinations without a source rock.The oil-source faults were mapped...Oil and gas exploration near faults in shallow strata is investigated in this study based on an analysis of oil-source faults in reservoire-cap rock combinations without a source rock.The oil-source faults were mapped by superimposition of the distribution area of oil-source faults and the leakage area of cap rocks.This method is applied to the mapping of oil-source faults for two sets of reservoire-cap rock combinations without a source rock in the Banqiao area of the Qikou Sag in the Bohai Bay Basin,eastern China.Combination B is formed by a mudstone cap rock of the middle sub-member of the 1st member of the Shahejie Formation(E3s1 M)with its underlying reservoir,while Combination C is formed by a mudstone cap rock of the 2nd member of the Dongying Formation(E_(3)d_(2))with its underlying reservoir.The results show that the oil-source faults of Combination B are relatively better developed and mainly occur in the northeast and southeast,while those of Combination C are not as well developed and are only distributed at the southeastern edge of the study area with a small proportion in the north.These results are consistent with the fact that oil and gas are mainly distributed near oil-source faults,proving the method proposed is workable in determining the oil-source faults in reservoire-cap rock combinations without a source rock.展开更多
The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nev...The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.展开更多
The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） o...The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） of 0.53 in Well M1 and 0.55 in Wells H1/Hd1/Hd2, respectively. Comparing with vitrinite reflectance （Ro/%）, the OP features a dynamic range and can indicate the oil generation window more precisely. By using OP and other geochemical indices, the oil-source correlation is also conducted. It suggests that the oils in wells M1 and M2 are derived from the source rocks in situ. The mudstone in Huachang uplift is not the main source rocks for oils in this area, The OP is also a useful oil-source correlation parameter in some Tertiary lacustrine basins.展开更多
Series of 2-alkyl-1,3,4-trimethylbenzenes(ATMBs)were detected in most of crude oils and source rocks collected from various strata and locations of the Tarim Basin.They appeared to have heavy carbon isotopic signatur...Series of 2-alkyl-1,3,4-trimethylbenzenes(ATMBs)were detected in most of crude oils and source rocks collected from various strata and locations of the Tarim Basin.They appeared to have heavy carbon isotopic signatures(δ13C,up to~-16‰)compared to those hydrocarbons from oxygenic phototrophic organisms,indicating that the unequivocal source of green sulfur bacteria(GSB)and photic zone euxinia(PZE)existed in the original environment.Considering the high paleoproductivity,the PZE may have enhanced the preservation of organic matter,which triggered the formation of extremely organic-rich source rocks with TOC up to 29.8%for the Lower Cambrian Yuertus Formation(€1y).The coexistence of ATMBs and the diagnostic products from secondary alterations(e.g.,abundant 25-norhopanes,thiadiamondoids,and diamondoids)indicated a stronger ability of anti-second-alterations.Combined with the results of quantitatively de-convoluting mixed oil,the oil-source correlation based on ATMBs from a large number of Lower Paleozoic samples of the Tarim Basin suggested that the abundant deep crude oil resources co ntained a dominant contribution(>50%)from the€1y source rocks.Therefore,the ATMBs,as diagnostic biomarkers indicating unequivocal precursors under special habitat conditions,might provide important insights for the exploration of deep Lower Paleozoic crude oils in the Tarim Basin.展开更多
Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source ...Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source correlation investigation.This objective is achieved through a meticulous analysis of well-log responses,Rock-Eval pyrolysis,and biomarker data.The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen.Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter.Notably,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is observed.Contrarily,the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II kerogen.Through analysis of five oil samples from different wells—SIWA L-1X,SIWA R-3X,SIWA D-1X,PTAH 5X,and PTAH 6X,it is evident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III kerogen.Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments.Noteworthy is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon generation.The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir,suggesting potential links to Paleozoic sources or even originating from the Safa Member itself.These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin.By illuminating the processes of hydrocarbon genesis in the region,this study significantly enriches our knowledge base.展开更多
Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained promine...Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.展开更多
There are abundant bitumens and oil seepages stored in vugs in a Lower-Triassic Daye formation(T_1d)marlite in Ni'erguan village in the Southern Guizhou Depression. However, the source of those oil seepages has no...There are abundant bitumens and oil seepages stored in vugs in a Lower-Triassic Daye formation(T_1d)marlite in Ni'erguan village in the Southern Guizhou Depression. However, the source of those oil seepages has not been determined to date. Multiple suites of source rocks of different ages exist in the depression. Both the oil seepages and potential source rocks have undergone complicated secondary alterations, which have added to the difficulty of an oil-source correlation. For example, the main source rock, a Lower-Cambrian Niutitang Formation"(∈_1n) mudstone, is over mature, and other potential source rocks, both from the Permian and the Triassic, are still in the oil window. In addition, the T_1d oil seepages underwent a large amount of biodegradation. To minimize the influence of biodegradation and thermal maturation, special methods were employed in this oil-source correlation study. These methods included catalytic hydropyrolysis, to release covalently bound biomarkers from the over mature"kerogen of ∈_1n mudstone, sequential extraction, to obtain chloroform bitumen A and chloroform bitumen C from the T_1d marlite, and anhydrous pyrolysis, to release pyrolysates from the kerogen of T_1d marlite. Using the methods above, the biomarkers and n-alkanes releasedfrom the oil samples and source rocks were analysed by GC–MS and GC-C-IRMS. The oil-source correlation indicated that the T_1d oil seepage primarily originated from"the ∈_1n mudstone and was partially mixed with oil generated from the T_1d marlite. Furthermore, the seepage also demonstrated that the above methods were effective for the complicated oil-source correlation in the Southern Guizhou Depression.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
The isolated fracture-vug systems controlled by small-scale strike-slip faults within ultra-deep carbonate rocks of the Tarim Basin exhibit significant exploration potential.The study employs a novel training set inco...The isolated fracture-vug systems controlled by small-scale strike-slip faults within ultra-deep carbonate rocks of the Tarim Basin exhibit significant exploration potential.The study employs a novel training set incorporating innovative fault labels to train a U-Net-structured CNN model,enabling effective identification of small-scale strike-slip faults through seismic data interpretation.Based on the CNN faults,we analyze the distribution patterns of small-scale strike-slip faults.The small-scale strike-slip faults can be categorized into NNW-trending and NE-trending groups with strike lengths ranging 200–5000 m.The development intensity of small-scale strike-slip faults in the Lower Yingshan Member notably exceeds that in the Upper Member.The Lower and Upper Yingshan members are two distinct mechanical layers with contrasting brittleness characteristics,separated by a low-brittleness layer.The superior brittleness of the Lower Yingshan Member enhances the development intensity of small-scale strike-slip faults compared to the upper member,while the low-brittleness layer exerts restrictive effects on vertical fault propagation.Fracture-vug systems formed by interactions of two or more small-scale strike-slip faults demonstrate larger sizes than those controlled by individual faults.All fracture-vug system sizes show positive correlations with the vertical extents of associated small-scale strike-slip faults,particularly intersection and approaching fracture-vug systems exhibit accelerated size increases proportional to the vertical extents.展开更多
The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly impro...The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly improve our understanding of seismogenesis and our ability to evaluate seismic hazards.Utilising the SKUA GoCAD software,we constructed detailed seismic fault models for the 2021 M_(S)6.4 Yangbi earthquake in Yunnan,China,using two sets of relocated earthquake catalogs and focal mechanism solutions following a convenient 3D fault modeling workflow.Our analysis revealed a NW-striking main fault with a high-angle SW dip,accompanied by two branch faults.Interpretation of one dataset revealed a single NNW-striking branch fault SW of the main fault,whereas the other dataset indicated four steep NNE-striking segments with a left-echelon pattern.Additionally,a third ENE-striking short fault was identified NE of the main fault.In combination with the spatial distribution of pre-existing faults,our 3D fault models indicate that the Yangbi earthquake reactivated pre-existing NW-and NE-striking fault directions rather than the surface-exposed Weixi-Qiaohou-Weishan Fault zone.The occurrence of the Yangbi earthquake demonstrates that the reactivation of pre-existing faults away from active fault zones,through either cascade or conjugate rupture modes,can cause unexpected moderate-large earthquakes and severe disasters,necessitating attention in regions like southeast Xizang,which have complex fault systems.展开更多
To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precis...To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.展开更多
Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator labora...Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator laboratories has revealed that SRF faults are the leading cause of short machine downtime trips.When a cavity fault occurs,system experts analyze the time-series data recorded by low-level RF systems and identify the fault type.However,this requires expertise and intuition,posing a major challenge for control-room operators.Here,we propose an expert feature-based machine learning model for automating SRF cavity fault recognition.The main challenge in converting the"expert reasoning"process for SRF faults into a"model inference"process lies in feature extraction,which is attributed to the associated multidimensional and complex time-series waveforms.Existing autoregression-based feature-extraction methods require the signal to be stable and autocorrelated,resulting in difficulty in capturing the abrupt features that exist in several SRF failure patterns.To address these issues,we introduce expertise into the classification model through reasonable feature engineering.We demonstrate the feasibility of this method using the SRF cavity of the China accelerator facility for superheavy elements(CAFE2).Although specific faults in SRF cavities may vary across different accelerators,similarities exist in the RF signals.Therefore,this study provides valuable guidance for fault analysis of the entire SRF community.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
As coal mining depth increases,the combined effects of high stress,mining stress,and fault structures make dynamic impact hazards more frequent.The reproduction of dynamic impact phenomena is basis for studying their ...As coal mining depth increases,the combined effects of high stress,mining stress,and fault structures make dynamic impact hazards more frequent.The reproduction of dynamic impact phenomena is basis for studying their occurrence patterns and control mechanisms.Physical simulation test represents an efficacious methodology.However,there is currently a lack of simulation devices that can effectively simulate two types of dynamic impact phenomena,including high stress and fault slip dynamic impact.To solve aforementioned issues,the physical simulation test system for dynamic impact in deep roadways developed by authors is employed to carry out comparative tests of high stress and fault slip dynamic impact.The phenomena of high stress and fault slip dynamic impact are reproduced successfully.A comparative analysis is conducted on dynamic phenomena,stress evolution,roadway deformation,and support force.The high stress dynamic impact roadway instability mode,which is characterized by the release of high energy accompanied by symmetric damage,and the fault slip dynamic impact roadway instability mode,which is characterized by the propagation of unilateral stress waves accompanied by asymmetric damage,are clarified.On the basis,the differentiated control concepts for different types of dynamic impact in deep roadways are proposed.展开更多
Knowledge of the seismogenic environment of fault zones is critical for understanding the processes and mechanisms of large earthquakes.We conducted a rock magnetic study of the fault rocks and protoliths to investiga...Knowledge of the seismogenic environment of fault zones is critical for understanding the processes and mechanisms of large earthquakes.We conducted a rock magnetic study of the fault rocks and protoliths to investigate the seismogenic environment of earthquakes in the Motuo fault zone,in the eastern Himalayan syntaxis.The results indicate that magnetite is the principal magnetic carrier in the fault rocks and protolith,while the protolith has a higher content of paramagnetic minerals than the fault rocks.The fault rocks are characterized by a high magnetic susceptibility relative to the protolith in the Motuo fault zone.This is likely due to the thermal alteration of paramagnetic minerals to magnetite caused by coseismic frictional heating with concomitant hydrothermal fluid circulation.The high magnetic susceptibility of the fault rocks and neoformed magnetite indicate that large earthquakes with frictional heating temperatures>500℃have occurred in the Motuo fault zone in the past,and that the fault maintained an oxidizing environment with weak fluid action during these earthquakes.Our results reveal the seismogenic environment of the Motuo fault zone,and they are potentially important for the evaluation of the regional stability in the eastern Himalayan syntaxis.展开更多
A complex geological environment with faults can be encountered in the process of coal mining.Fault activation can cause instantaneous structure slipping,releasing a significant amount of elastic strain energy during ...A complex geological environment with faults can be encountered in the process of coal mining.Fault activation can cause instantaneous structure slipping,releasing a significant amount of elastic strain energy during underground coal mining.This would trigger strong rockburst disasters.To understand the occurrence of fault-slip induced rockbursts,we developed a physical model test system for fault-slip induced rockbursts in coal mine drifts.The boundary energy storage(BES)loading apparatus and bottom rapid retraction(BRR)apparatus are designed to realize energy compensation and continuous boundary stress transfer of the surrounding rocks for instantaneous fault slip,as well as to provide space for the potential fault slip.Taking the typical fault-slip induced rockburst in the Xinjulong Coal Mine,China,as the background,we conducted a model test using the test system.The deformation and stress in the rock surrounding the drift and the support unit force during fault slip are analyzed.The deformation and failure characteristics and dynamic responses of drifts under fault-slip induced rockbursts are obtained.The test results illustrate the rationality and effectiveness of the test system.Finally,corresponding recommendations and prospects are proposed based on our findings.展开更多
Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from b...Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.展开更多
基金granted by the National Natural Science Foundation of China(grant No.41672131)Fundamental Research Funds for the Central Universities(grant No.16CX06045A)
文摘Objective Oil-source faults have an important effect on reservoir formation and distribution in shallow formations with non- hydrocarbon generation in oil-rich fault-related basins （Jiang Youlu et al., 2015）. However, the fault transporting capacity cannot be evaluated quantitatively at present. Taking the Zhanhua Sag in the Bohai Bay Basin as an example, this work analyzed the factors influencing the transporting capacity of the oil-source faults and proposed a quantitative method for evaluating their transporting capacity.
基金The National Natural Science Foundation of China(grant IDs 41872157,42072157).
文摘Oil and gas exploration near faults in shallow strata is investigated in this study based on an analysis of oil-source faults in reservoire-cap rock combinations without a source rock.The oil-source faults were mapped by superimposition of the distribution area of oil-source faults and the leakage area of cap rocks.This method is applied to the mapping of oil-source faults for two sets of reservoire-cap rock combinations without a source rock in the Banqiao area of the Qikou Sag in the Bohai Bay Basin,eastern China.Combination B is formed by a mudstone cap rock of the middle sub-member of the 1st member of the Shahejie Formation(E3s1 M)with its underlying reservoir,while Combination C is formed by a mudstone cap rock of the 2nd member of the Dongying Formation(E_(3)d_(2))with its underlying reservoir.The results show that the oil-source faults of Combination B are relatively better developed and mainly occur in the northeast and southeast,while those of Combination C are not as well developed and are only distributed at the southeastern edge of the study area with a small proportion in the north.These results are consistent with the fact that oil and gas are mainly distributed near oil-source faults,proving the method proposed is workable in determining the oil-source faults in reservoire-cap rock combinations without a source rock.
基金funded by the South Oil Exploration and Development Company of PetroChina(2021-HNYJ-010).
文摘The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.
基金supported by the Natural Science Foundation of China(Grant No.40672093)CNPC Innovation Fund(07El001)the ESS-China Hydrocarbon Geosciences Collaboration Project under Natural Resources Canada's International Opportunities Program.
文摘The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） of 0.53 in Well M1 and 0.55 in Wells H1/Hd1/Hd2, respectively. Comparing with vitrinite reflectance （Ro/%）, the OP features a dynamic range and can indicate the oil generation window more precisely. By using OP and other geochemical indices, the oil-source correlation is also conducted. It suggests that the oils in wells M1 and M2 are derived from the source rocks in situ. The mudstone in Huachang uplift is not the main source rocks for oils in this area, The OP is also a useful oil-source correlation parameter in some Tertiary lacustrine basins.
基金financial support provided by the National Science and Technology Major Project of the Ministry of Science and Technology of China (2016ZX04004-004)National Natural Science Foundation of China (41672125)
文摘Series of 2-alkyl-1,3,4-trimethylbenzenes(ATMBs)were detected in most of crude oils and source rocks collected from various strata and locations of the Tarim Basin.They appeared to have heavy carbon isotopic signatures(δ13C,up to~-16‰)compared to those hydrocarbons from oxygenic phototrophic organisms,indicating that the unequivocal source of green sulfur bacteria(GSB)and photic zone euxinia(PZE)existed in the original environment.Considering the high paleoproductivity,the PZE may have enhanced the preservation of organic matter,which triggered the formation of extremely organic-rich source rocks with TOC up to 29.8%for the Lower Cambrian Yuertus Formation(€1y).The coexistence of ATMBs and the diagnostic products from secondary alterations(e.g.,abundant 25-norhopanes,thiadiamondoids,and diamondoids)indicated a stronger ability of anti-second-alterations.Combined with the results of quantitatively de-convoluting mixed oil,the oil-source correlation based on ATMBs from a large number of Lower Paleozoic samples of the Tarim Basin suggested that the abundant deep crude oil resources co ntained a dominant contribution(>50%)from the€1y source rocks.Therefore,the ATMBs,as diagnostic biomarkers indicating unequivocal precursors under special habitat conditions,might provide important insights for the exploration of deep Lower Paleozoic crude oils in the Tarim Basin.
基金the research project is funded by Abdullah Alrushaid Chair for Earth Science Remote Sensing Research at King Saud University,Riyadh,Saudi Arabia.。
文摘Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source correlation investigation.This objective is achieved through a meticulous analysis of well-log responses,Rock-Eval pyrolysis,and biomarker data.The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen.Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter.Notably,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is observed.Contrarily,the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II kerogen.Through analysis of five oil samples from different wells—SIWA L-1X,SIWA R-3X,SIWA D-1X,PTAH 5X,and PTAH 6X,it is evident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III kerogen.Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments.Noteworthy is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon generation.The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir,suggesting potential links to Paleozoic sources or even originating from the Safa Member itself.These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin.By illuminating the processes of hydrocarbon genesis in the region,this study significantly enriches our knowledge base.
基金supported by the National Natural Science Foundation of China(No.52277055).
文摘Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.
基金supported jointly by the National Science and Technology Major Project of China (Grant Nos: 2011ZX05008002 and 2011ZX05005-001)
文摘There are abundant bitumens and oil seepages stored in vugs in a Lower-Triassic Daye formation(T_1d)marlite in Ni'erguan village in the Southern Guizhou Depression. However, the source of those oil seepages has not been determined to date. Multiple suites of source rocks of different ages exist in the depression. Both the oil seepages and potential source rocks have undergone complicated secondary alterations, which have added to the difficulty of an oil-source correlation. For example, the main source rock, a Lower-Cambrian Niutitang Formation"(∈_1n) mudstone, is over mature, and other potential source rocks, both from the Permian and the Triassic, are still in the oil window. In addition, the T_1d oil seepages underwent a large amount of biodegradation. To minimize the influence of biodegradation and thermal maturation, special methods were employed in this oil-source correlation study. These methods included catalytic hydropyrolysis, to release covalently bound biomarkers from the over mature"kerogen of ∈_1n mudstone, sequential extraction, to obtain chloroform bitumen A and chloroform bitumen C from the T_1d marlite, and anhydrous pyrolysis, to release pyrolysates from the kerogen of T_1d marlite. Using the methods above, the biomarkers and n-alkanes releasedfrom the oil samples and source rocks were analysed by GC–MS and GC-C-IRMS. The oil-source correlation indicated that the T_1d oil seepage primarily originated from"the ∈_1n mudstone and was partially mixed with oil generated from the T_1d marlite. Furthermore, the seepage also demonstrated that the above methods were effective for the complicated oil-source correlation in the Southern Guizhou Depression.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported by the National Natural Science Foundation of China(No.U21B2062).
文摘The isolated fracture-vug systems controlled by small-scale strike-slip faults within ultra-deep carbonate rocks of the Tarim Basin exhibit significant exploration potential.The study employs a novel training set incorporating innovative fault labels to train a U-Net-structured CNN model,enabling effective identification of small-scale strike-slip faults through seismic data interpretation.Based on the CNN faults,we analyze the distribution patterns of small-scale strike-slip faults.The small-scale strike-slip faults can be categorized into NNW-trending and NE-trending groups with strike lengths ranging 200–5000 m.The development intensity of small-scale strike-slip faults in the Lower Yingshan Member notably exceeds that in the Upper Member.The Lower and Upper Yingshan members are two distinct mechanical layers with contrasting brittleness characteristics,separated by a low-brittleness layer.The superior brittleness of the Lower Yingshan Member enhances the development intensity of small-scale strike-slip faults compared to the upper member,while the low-brittleness layer exerts restrictive effects on vertical fault propagation.Fracture-vug systems formed by interactions of two or more small-scale strike-slip faults demonstrate larger sizes than those controlled by individual faults.All fracture-vug system sizes show positive correlations with the vertical extents of associated small-scale strike-slip faults,particularly intersection and approaching fracture-vug systems exhibit accelerated size increases proportional to the vertical extents.
基金financial support from the National Key R&D Program of China (No. 2021YFC3000600)National Natural Science Foundation of China (No. 41872206)National Nonprofit Fundamental Research Grant of China, Institute of Geology, China, Earthquake Administration (No. IGCEA2010)
文摘The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly improve our understanding of seismogenesis and our ability to evaluate seismic hazards.Utilising the SKUA GoCAD software,we constructed detailed seismic fault models for the 2021 M_(S)6.4 Yangbi earthquake in Yunnan,China,using two sets of relocated earthquake catalogs and focal mechanism solutions following a convenient 3D fault modeling workflow.Our analysis revealed a NW-striking main fault with a high-angle SW dip,accompanied by two branch faults.Interpretation of one dataset revealed a single NNW-striking branch fault SW of the main fault,whereas the other dataset indicated four steep NNE-striking segments with a left-echelon pattern.Additionally,a third ENE-striking short fault was identified NE of the main fault.In combination with the spatial distribution of pre-existing faults,our 3D fault models indicate that the Yangbi earthquake reactivated pre-existing NW-and NE-striking fault directions rather than the surface-exposed Weixi-Qiaohou-Weishan Fault zone.The occurrence of the Yangbi earthquake demonstrates that the reactivation of pre-existing faults away from active fault zones,through either cascade or conjugate rupture modes,can cause unexpected moderate-large earthquakes and severe disasters,necessitating attention in regions like southeast Xizang,which have complex fault systems.
基金Yongxian Huang supported by Projects of Guangzhou Science and Technology Plan(2023A04J0409)。
文摘To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.
基金supported by the studies of intelligent LLRF control algorithms for superconducting RF cavities(No.E129851YR0)the National Natural Science Foundation of China(No.U22A20261)Applications of Artificial Intelligence in the Stability Study of Superconducting Linear Accelerators(No.E429851YR0)。
文摘Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator laboratories has revealed that SRF faults are the leading cause of short machine downtime trips.When a cavity fault occurs,system experts analyze the time-series data recorded by low-level RF systems and identify the fault type.However,this requires expertise and intuition,posing a major challenge for control-room operators.Here,we propose an expert feature-based machine learning model for automating SRF cavity fault recognition.The main challenge in converting the"expert reasoning"process for SRF faults into a"model inference"process lies in feature extraction,which is attributed to the associated multidimensional and complex time-series waveforms.Existing autoregression-based feature-extraction methods require the signal to be stable and autocorrelated,resulting in difficulty in capturing the abrupt features that exist in several SRF failure patterns.To address these issues,we introduce expertise into the classification model through reasonable feature engineering.We demonstrate the feasibility of this method using the SRF cavity of the China accelerator facility for superheavy elements(CAFE2).Although specific faults in SRF cavities may vary across different accelerators,similarities exist in the RF signals.Therefore,this study provides valuable guidance for fault analysis of the entire SRF community.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
基金supported by the National Natural Science Foundation of China(Nos.U24A2088,42177130,42277174,and 42477166).
文摘As coal mining depth increases,the combined effects of high stress,mining stress,and fault structures make dynamic impact hazards more frequent.The reproduction of dynamic impact phenomena is basis for studying their occurrence patterns and control mechanisms.Physical simulation test represents an efficacious methodology.However,there is currently a lack of simulation devices that can effectively simulate two types of dynamic impact phenomena,including high stress and fault slip dynamic impact.To solve aforementioned issues,the physical simulation test system for dynamic impact in deep roadways developed by authors is employed to carry out comparative tests of high stress and fault slip dynamic impact.The phenomena of high stress and fault slip dynamic impact are reproduced successfully.A comparative analysis is conducted on dynamic phenomena,stress evolution,roadway deformation,and support force.The high stress dynamic impact roadway instability mode,which is characterized by the release of high energy accompanied by symmetric damage,and the fault slip dynamic impact roadway instability mode,which is characterized by the propagation of unilateral stress waves accompanied by asymmetric damage,are clarified.On the basis,the differentiated control concepts for different types of dynamic impact in deep roadways are proposed.
基金supported by the Fundamental Research Funds of the Institute of Geomechanics(DZLXJK202401)the National Natural Science Foundation of China(42177172,U2244226,42172255)+1 种基金the China Geological Survey Project(DD20230538)Deep Earth Probe and Mineral Resources ExplorationNational Science and Technology Major Project(2024ZD1000500)。
文摘Knowledge of the seismogenic environment of fault zones is critical for understanding the processes and mechanisms of large earthquakes.We conducted a rock magnetic study of the fault rocks and protoliths to investigate the seismogenic environment of earthquakes in the Motuo fault zone,in the eastern Himalayan syntaxis.The results indicate that magnetite is the principal magnetic carrier in the fault rocks and protolith,while the protolith has a higher content of paramagnetic minerals than the fault rocks.The fault rocks are characterized by a high magnetic susceptibility relative to the protolith in the Motuo fault zone.This is likely due to the thermal alteration of paramagnetic minerals to magnetite caused by coseismic frictional heating with concomitant hydrothermal fluid circulation.The high magnetic susceptibility of the fault rocks and neoformed magnetite indicate that large earthquakes with frictional heating temperatures>500℃have occurred in the Motuo fault zone in the past,and that the fault maintained an oxidizing environment with weak fluid action during these earthquakes.Our results reveal the seismogenic environment of the Motuo fault zone,and they are potentially important for the evaluation of the regional stability in the eastern Himalayan syntaxis.
基金support from the National Natural Science Foundation of China (Grant Nos.51927807,42077267 and 42277174).
文摘A complex geological environment with faults can be encountered in the process of coal mining.Fault activation can cause instantaneous structure slipping,releasing a significant amount of elastic strain energy during underground coal mining.This would trigger strong rockburst disasters.To understand the occurrence of fault-slip induced rockbursts,we developed a physical model test system for fault-slip induced rockbursts in coal mine drifts.The boundary energy storage(BES)loading apparatus and bottom rapid retraction(BRR)apparatus are designed to realize energy compensation and continuous boundary stress transfer of the surrounding rocks for instantaneous fault slip,as well as to provide space for the potential fault slip.Taking the typical fault-slip induced rockburst in the Xinjulong Coal Mine,China,as the background,we conducted a model test using the test system.The deformation and stress in the rock surrounding the drift and the support unit force during fault slip are analyzed.The deformation and failure characteristics and dynamic responses of drifts under fault-slip induced rockbursts are obtained.The test results illustrate the rationality and effectiveness of the test system.Finally,corresponding recommendations and prospects are proposed based on our findings.
基金support by the National Natural Science Foundation of China(Grant No.52402520)。
文摘Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.
