Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hyd...Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hydraulic fracturing process in lab-scale coal samples with DFNs and the induced seismic activities by the discrete element method(DEM).The effects of DFNs on hydraulic fracturing,induced seismicity and elastic property changes have been concluded.Denser DFNs can comprehensively decrease the peak injection pressure and injection duration.The proportion of strong seismic events increases first and then decreases with increasing DFN density.In addition,the relative modulus of the rock mass is derived innovatively from breakdown pressure,breakdown fracture length and the related initiation time.Increasing DFN densities among large(35–60 degrees)and small(0–30 degrees)fracture dip angles show opposite evolution trends in relative modulus.The transitional point(dip angle)for the opposite trends is also proportionally affected by the friction angle of the rock mass.The modelling results have much practical meaning to infer the density and geometry of pre-existing fractures and the elastic property of rock mass in the field,simply based on the hydraulic fracturing and induced seismicity monitoring data.展开更多
Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overa...Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overall direction of hydraulic fractures does not show a delineated shape parallel to the maximum principal stress orientation.A field-scale numerical model based on the distinct element method is set up to carry out a fully coupled hydromechanical simulation,with the explicit representation of natural fractures via the discrete fracture network(DFN)approach.The effects of injection parameters and in situ stress on hydraulic fracture patterns are then quantitatively assessed.The study reveals that shear-induced deformation primarily governs the fracturing morphology in the GR1 well,driven by smaller injection rates and viscosities that promote massive activation of natural fractures,ultimately dominating the direction of hydraulic fracturing.Furthermore,the increase of in situ differential stress may promote shear damage of natural fracture surfaces,with the exact influence pattern depending on the combination of specific discontinuity properties and in situ stress state.Finally,we provide recommendations for EGS fracturing based on the influence characteristics of multiple parameters.This study can serve as an effective basis and reference for the design and optimization of EGS in the Gonghe basin and other sites.展开更多
In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members o...In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members of Triassic Baikouquan Formation(T1b2 and T1b3)in Ma-131 well area,which learned from the successful experience of hydraulic fracturing test sites in North America(HFTS-1).Twelve horizontal wells and a high-angle coring well MaJ02 were drilled.The orientation,connection,propagation law and major controlling factors of hydraulic fractures were analyzed by comparing results of CT scans,imaging logs,direct observation of cores from Well MaJ02,and combined with tracer monitoring data.Results indicate that:(1)Two types of fractures have developed by hydraulic fracturing,i.e.tensile fractures and shear fractures.Tensile fractures are approximately parallel to the direction of the maximum horizontal principal stress,and propagate less than 50 m from perforation clusters.Shear fractures are distributed among tensile fractures and mainly in the strike-slip mode due to the induced stress field among tensile fractures,and some of them are in conjugated pairs.Overall,tensile fractures alternate with shear fractures,with shear fractures dominated and activated after tensile ones.(2)Tracer monitoring results indicate that communication between wells was prevalent in the early stage of production,and the static pressure in the fracture gradually decreased and the connectivity between wells reduced as production progressed.(3)Density of hydraulic fractures is mainly affected by the lithology and fracturing parameters,which is smaller in the mudstone than the conglomerate.Larger fracturing scale and smaller cluster spacing lead to a higher fracture density,which are important directions to improve the well productivity.展开更多
The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise m...The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.展开更多
Through a case analysis,this study examines the spatiotemporal evolution of microseismic(MS)events,energy characteristics,volumetric features,and fracture network development in surface well hydraulic fracturing.A tot...Through a case analysis,this study examines the spatiotemporal evolution of microseismic(MS)events,energy characteristics,volumetric features,and fracture network development in surface well hydraulic fracturing.A total of 349 MS events were analyzed across different fracturing sections,revealing significant heterogeneity in fracture propagation.Energy scanning results showed that cumulative energy values ranged from 240 to 1060 J across the sections,indicating notable differences.Stimulated reservoir volume(SRV)analysis demonstrated well-developed fracture networks in certain sections,with a total SRV exceeding 1540000 m^(3).The hydraulic fracture network analysis revealed that during the midfracturing stage,the density and spatial extent of MS events significantly increased,indicating rapid fracture propagation and the formation of complex networks.In the later stage,the number of secondary fractures near fracture edges decreased,and the fracture network stabilized.By comparing the branching index,fracture length,width,height,and SRV values across different fracturing sections,Sections No.1 and No.8 showed the best performance,with high MS event densities,extensive fracture networks,and significant energy release.However,Sections No.4 and No.5 exhibited sparse MS activity and poor fracture connectivity,indicating suboptimal stimulation effectiveness.展开更多
For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system ...For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system has settled the problems of recognizing and controlling the unknown, uncertain and nonlinear system successfully, and has been applied to hydraulic roll bending control. The simulation results indicate that the system has good performance and strong robustness, and is better than traditional PID and neural-fuzzy control. The method is an effective tool to control roll bending force with increased dynamic response speed of control system and enhanced tracking accuracy.展开更多
Prepulse combined hydraulic fracturing facilitates the development of fracture networks by integrating prepulse hydraulic loading with conventional hydraulic fracturing.The formation mechanisms of fracture networks be...Prepulse combined hydraulic fracturing facilitates the development of fracture networks by integrating prepulse hydraulic loading with conventional hydraulic fracturing.The formation mechanisms of fracture networks between hydraulic and pre-existing fractures under different prepulse loading parameters remain unclear.This research investigates the impact of prepulse loading parameters,including the prepulse loading number ratio(C),prepulse loading stress ratio(S),and prepulse loading frequency(f),on the formation of fracture networks between hydraulic and pre-existing fractures,using both experimental and numerical methods.The results suggest that low prepulse loading stress ratios and high prepulse loading number ratios are advantageous loading modes.Multiple hydraulic fractures are generated in the specimen under the advantageous loading modes,facilitating the development of a complex fracture network.Fatigue damage occurs in the specimen at the prepulse loading stage.The high water pressure at the secondary conventional hydraulic fracturing promotes the growth of hydraulic fractures along the damage zones.This allows the hydraulic fractures to propagate deeply and interact with pre-existing fractures.Under advantageous loading conditions,multiple hydraulic fractures can extend to pre-existing fractures,and these hydraulic fractures penetrate or propagate along pre-existing fractures.Especially when the approach angle is large,the damage range in the specimen during the prepulse loading stage increases,resulting in the formation of more hydraulic fractures.展开更多
The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydrau...The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.展开更多
With the purpose of making calculation more efficient in practical hydraulic simulations, an improved algorithm was proposed and was applied in the practical water distribution field. This methodology was developed by...With the purpose of making calculation more efficient in practical hydraulic simulations, an improved algorithm was proposed and was applied in the practical water distribution field. This methodology was developed by expanding the traditional loop-equation theory through utilization of the advantages of the graph theory in efficiency. The utilization of the spanning tree technique from graph theory makes the proposed algorithm efficient in calculation and simple to use for computer coding. The algorithms for topological generation and practical implementations are presented in detail in this paper. Through the application to a practical urban system, the consumption of the CPU time and computation memory were decreased while the accuracy was greatly enhanced compared with the present existing methods.展开更多
With an extension of the geological entropy concept in porous media,the approach called directional entrogram is applied to link hydraulic behavior to the anisotropy of the 3D fracture networks.A metric called directi...With an extension of the geological entropy concept in porous media,the approach called directional entrogram is applied to link hydraulic behavior to the anisotropy of the 3D fracture networks.A metric called directional entropic scale is used to measure the anisotropy of spatial order in different directions.Compared with the traditional connectivity indexes based on the statistics of fracture geometry,the directional entropic scale is capable to quantify the anisotropy of connectivity and hydraulic conductivity in heterogeneous 3D fracture networks.According to the numerical analysis of directional entrogram and fluid flow in a number of the 3D fracture networks,the hydraulic conductivities and entropic scales in different directions both increase with spatial order(i.e.,trace length decreasing and spacing increasing)and are independent of the dip angle.As a result,the nonlinear correlation between the hydraulic conductivities and entropic scales from different directions can be unified as quadratic polynomial function,which can shed light on the anisotropic effect of spatial order and global entropy on the heterogeneous hydraulic behaviors.展开更多
The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully ca...The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully carried out for hydraulic axial piston pump based on experiments with the MATLAB and the toolbox of neural networks, The operating pressure, the flow rate of hydraulic axial piston pump, the temperature of hydraulic oil, and bulk modulus of hydraulic oil are the main parameters having influences on the noise of hydraulic axial piston pump. These four parameters are used as inputs of neural networks, and experimental data of the noise are used as outputs of neural networks, Error of noise identification is less than 1% after the neural networks have been trained. The results show that the noise identification of hydraulic axial piston pump is feasible and reliable by using artificial neural networks. The method of noise identification with neural networks is also creative one of noise theoretical research for hydraulic axial piston pump.展开更多
By integrating laboratory physical modeling experiments with machine learning-based analysis of dominant factors,this study explored the feasibility of pulse hydraulic fracturing(PHF)in deep coal rocks and revealed th...By integrating laboratory physical modeling experiments with machine learning-based analysis of dominant factors,this study explored the feasibility of pulse hydraulic fracturing(PHF)in deep coal rocks and revealed the fracture propagation patterns and the mechanisms of pulsating loading in the process.The results show that PHF induces fatigue damage in coal matrix,significantly reducing breakdown pressure and increasing fracture network volume.Lower vertical stress differential coefficient(less than 0.31),lower peak pressure ratio(less than 0.9),higher horizontal stress differential coefficient(greater than 0.13),higher pulse amplitude ratio(greater than or equal to 0.5)and higher pulse frequency(greater than or equal to 3 Hz)effectively decrease the breakdown pressure.Conversely,higher vertical stress differential coefficient(greater than or equal to 0.31),higher pulse amplitude ratio(greater than or equal to 0.5),lower horizontal stress differential coefficient(less than or equal to 0.13),lower peak pressure ratio(less than 0.9),and lower pulse frequency(less than 3 Hz)promote the formation of a complex fracture network.Vertical stress and peak pressure are the most critical geological and engineering parameters affecting the stimulation effectiveness of PHF.The dominant mechanism varies with coal rank due to differences in geomechanical characteristics and natural fracture development.Low-rank coal primarily exhibits matrix strength degradation.High-rank coal mainly involves the activation of natural fractures and bedding planes.Medium-rank coal shows a coexistence of matrix strength degradation and micro-fracture connectivity.The PHF forms complex fracture networks through the dual mechanism of matrix strength degradation and fracture network connectivity enhancement.展开更多
Artificial neural networks （ANNs） and genetic programming （GP） have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the characteristics of hy...Artificial neural networks （ANNs） and genetic programming （GP） have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the characteristics of hydraulic jumps, such as the free surface location and energy dissipation. The dimensionless hydraulic parameters, including jump depth, jump length, and energy dissipation, were determined as functions of the Froude number and the height and length of corrugations. The estimations of the ANN and GP models were found to be in good agreement with the measured data. The results of the ANN model were compared with those of the GP model, showing that the proposed ANN models are much more accurate than the GP models.展开更多
To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power syst...To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power system are given for the precision requirement,and a control strategy for dual relative control parameters in the dual loop PID is put forward,a load and throttle rotation-speed response model for variable pump and gasoline engine is provided according to a physical process,a simplified neural network structure PID is introduced,and formed mixed neural network PID(MNN PID)to control rotation speed of engine and pressure of variable pump,calculation using the back propagation(BP)algorithm and a self-adapted learning step is made,including a mathematic principle and a calculation flow scheme,the BP algorithm of neural network PID is trained and the control effect of system is simulated in Matlab environment,real control effects of engine rotation speed and variable pump pressure are verified in the experimental bench.Results show that algorithm effect of MNN PID is stable and MNN PID can meet the adjusting requirement of control parameters.展开更多
To make a large area of dredger fill silt surface layer form working face and subsequent construction problems, the project conducts the bamboo network reinforcement in the silt surface layer. It makes the surface lay...To make a large area of dredger fill silt surface layer form working face and subsequent construction problems, the project conducts the bamboo network reinforcement in the silt surface layer. It makes the surface layer bearing capacity to meet the construction requirement of deep processing. Based on Shantou Municipal Road Embankment Treatment Engineering and the project, the bamboo network reinforcement technology to reinforce the dredger fill super soft soil surface layer is used. The results show that the bearing capacity of hydraulic fill super soft soil surface layer is 32.6 kPa after 3 months treatment. The surface layer bearing capacity after 3 months treatment improved 323% than the early treatment and increased 695% than no processing. The results indicate that the reinforcement effect is outstanding and provide the basis for drafting the dredger fill super soft soil surface layer treatment plan.展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;">The reliability and ease of applying metaheuristic methods in solving large and complex equation systems make it int...<div style="text-align:justify;"> <span style="font-family:Verdana;">The reliability and ease of applying metaheuristic methods in solving large and complex equation systems make it interesting to be applied as an alternative solution to solving problems in various fields. This article proves the effectiveness of an optimization model based on the <span style="font-family:Verdana;">m<span style="font-family:Verdana;">etaheuristic method for the analysis of hydraulic parameters of drinking water distribution pipes. The metaheuristic methods explored are Differential Evolution (DE) algorithm, Particle Swam Optimization (PSO) algorithm and CODEQ algorithm. The effectiveness of the three methods is measured relative by comparing the results of the analysis of the three models with the results from Newton Raphson method and Monte Carlo simulation method. The analysis shows that the optimization model based on the DE, PSO and CODEQ algorithms is very effective for solving problems on a simple network that has 6 pipe elements and 5 service nodes. The results obtained have a level of accuracy as good as Newton Raphson method. In the case of complex networks that have 32 pipe elements and 21 service nodes, there is an indication of performance degradation which is indicated by a decrease in fitness value. In this case, Newton Raphson method still shows its consistency. The optimization model based on the metaheuristic method is still far more effective than the Monte Carlo simulation method, although it is not as effective as Newton Raphson method. The Monte Carlo simulation method is not recommended for hydraulic pipe network analysis, even for simple networks.展开更多
Hydraulic systems have the characteristics of strong fault concealment,powerful nonlinear time-varying signals,and a complex vibration transmission mechanism;hence,diagnosis of these systems is a challenge.To provide ...Hydraulic systems have the characteristics of strong fault concealment,powerful nonlinear time-varying signals,and a complex vibration transmission mechanism;hence,diagnosis of these systems is a challenge.To provide accurate diagnosis results automatically,numerous studies have been carried out.Among them,signal-based methods are commonly used,which employ signal processing techniques based on the state signal used for extracting features,and further input the features into the classifier for fault recognition.However,their main deficiencies include the following:(1)The features are manually designed and thus may have a lack of objectivity.(2)For signal processing,feature extraction and pattern recognition are conducted using independent models,which cannot be jointly optimized globally.(3)The machine learning algorithms adopted by these methods have a shallow architecture,which limits their capacity to deeply mine the essential features of a fault.As a breakthrough in artificial intelligence,deep learning holds the potential to overcome such deficiencies.Based on deep learning,deep neural networks(DNNs)can automatically learn the complex nonlinear relations implied in a signal,can be globally optimized,and can obtain the high-level features of multi-dimensional data.In this paper,the main technology used in an intelligent fault diagnosis and the current research status of hydraulic system fault diagnosis are summarized and analyzed.The significant prospect of applying deep learning in the field of intelligent fault diagnosis is presented,and the main ideas,methods,and principles of several typical DNNs are described and summarized.The commonality between a fault diagnosis and other issues regarding typical pattern recognition are analyzed,and research ideas for applying DNNs for hydraulic fault diagnosis are proposed.Meanwhile,the research advantages and development trend of DNNs(both domestically and overseas)as applied to an intelligent fault diagnosis are reviewed.Furthermore,the fault characteristics of a complex hydraulic system are summarized and discussed,and the key problems and possible research ideas of applying DNNs to an intelligent hydraulic fault diagnosis are presented and comprehensively analyzed.展开更多
The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor valve.Essentially,the Valvistor valve is a proportional throttl...The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor valve.Essentially,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load pressure.The flow fluctuation severely restricts the application of the Valvistor valve.In this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow valve.The mathematical model of this valve is established and linearized.Fuzzy proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control system.The feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main orifice.The results show that inference with BPNN can obtain the flow data fast and accurately.With the flow control method,the flow can keep at the set point when the pressure differential across the main orifice changes.The flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow valve.For the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes abruptly.The performances of hysteresis,linearity and bandwidth are in a high range.The linear mathematical model can be verified and the assumptions in the system modeling is reasonable.展开更多
In this context, recent developments in the coupled three-dimensional(3 D) hydro-mechanical(HM)simulation tool TOUGH-RBSN are presented. This tool is used to model hydraulic fracture in geological media, as observed i...In this context, recent developments in the coupled three-dimensional(3 D) hydro-mechanical(HM)simulation tool TOUGH-RBSN are presented. This tool is used to model hydraulic fracture in geological media, as observed in laboratory-scale tests. The TOUGH-RBSN simulator is based on the effective linking of two numerical methods: TOUGH2, a finite volume method for simulating mass transport within a permeable medium; and a lattice model based on the rigid-body-spring network(RBSN) concept. The method relies on a Voronoi-based discretization technique that can represent fracture development within a permeable rock matrix. The simulator provides two-way coupling of HM processes, including fluid pressure-induced fracture and fracture-assisted flow. We first present the basic capabilities of the modeling approach using two example applications, i.e. permeability evolution under compression deformation, and analyses of a static fracturing simulation. Thereafter, the model is used to simulate laboratory tests of hydraulic fracturing in granite. In most respects, the simulation results meet expectations with respect to permeability evolution and fracturing patterns. It can be seen that the evolution of injection pressure associated with the simulated fracture developments is strongly affected by fluid viscosity.展开更多
基金Australian Research Council Linkage Program(LP200301404)for sponsoring this researchthe financial support provided by the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology,SKLGP2021K002)National Natural Science Foundation of China(52374101,32111530138).
文摘Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hydraulic fracturing process in lab-scale coal samples with DFNs and the induced seismic activities by the discrete element method(DEM).The effects of DFNs on hydraulic fracturing,induced seismicity and elastic property changes have been concluded.Denser DFNs can comprehensively decrease the peak injection pressure and injection duration.The proportion of strong seismic events increases first and then decreases with increasing DFN density.In addition,the relative modulus of the rock mass is derived innovatively from breakdown pressure,breakdown fracture length and the related initiation time.Increasing DFN densities among large(35–60 degrees)and small(0–30 degrees)fracture dip angles show opposite evolution trends in relative modulus.The transitional point(dip angle)for the opposite trends is also proportionally affected by the friction angle of the rock mass.The modelling results have much practical meaning to infer the density and geometry of pre-existing fractures and the elastic property of rock mass in the field,simply based on the hydraulic fracturing and induced seismicity monitoring data.
基金support from the National Natural Science Foundation of China(Grant Nos.42320104003,42177175,and 42077247)the Fundamental Research Funds for the Central Universities.
文摘Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overall direction of hydraulic fractures does not show a delineated shape parallel to the maximum principal stress orientation.A field-scale numerical model based on the distinct element method is set up to carry out a fully coupled hydromechanical simulation,with the explicit representation of natural fractures via the discrete fracture network(DFN)approach.The effects of injection parameters and in situ stress on hydraulic fracture patterns are then quantitatively assessed.The study reveals that shear-induced deformation primarily governs the fracturing morphology in the GR1 well,driven by smaller injection rates and viscosities that promote massive activation of natural fractures,ultimately dominating the direction of hydraulic fracturing.Furthermore,the increase of in situ differential stress may promote shear damage of natural fracture surfaces,with the exact influence pattern depending on the combination of specific discontinuity properties and in situ stress state.Finally,we provide recommendations for EGS fracturing based on the influence characteristics of multiple parameters.This study can serve as an effective basis and reference for the design and optimization of EGS in the Gonghe basin and other sites.
基金Supported by the National Natural Science Foundation of China(52274051)CNPC-China University of Petroleum(Beijing)Strategic Cooperative Project(ZLZX2020-01).
文摘In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members of Triassic Baikouquan Formation(T1b2 and T1b3)in Ma-131 well area,which learned from the successful experience of hydraulic fracturing test sites in North America(HFTS-1).Twelve horizontal wells and a high-angle coring well MaJ02 were drilled.The orientation,connection,propagation law and major controlling factors of hydraulic fractures were analyzed by comparing results of CT scans,imaging logs,direct observation of cores from Well MaJ02,and combined with tracer monitoring data.Results indicate that:(1)Two types of fractures have developed by hydraulic fracturing,i.e.tensile fractures and shear fractures.Tensile fractures are approximately parallel to the direction of the maximum horizontal principal stress,and propagate less than 50 m from perforation clusters.Shear fractures are distributed among tensile fractures and mainly in the strike-slip mode due to the induced stress field among tensile fractures,and some of them are in conjugated pairs.Overall,tensile fractures alternate with shear fractures,with shear fractures dominated and activated after tensile ones.(2)Tracer monitoring results indicate that communication between wells was prevalent in the early stage of production,and the static pressure in the fracture gradually decreased and the connectivity between wells reduced as production progressed.(3)Density of hydraulic fractures is mainly affected by the lithology and fracturing parameters,which is smaller in the mudstone than the conglomerate.Larger fracturing scale and smaller cluster spacing lead to a higher fracture density,which are important directions to improve the well productivity.
基金Item Sponsored by National High-Tech Research and Development Program(863Program)of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Hebei Provincial Science and Technology Project of China(10212101D)
文摘The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.
基金supported by Yunlong Lake Laboratory of Deep Underground Science and Engineering Project(No.104024008)the National Natural Science Foundation of China(Nos.52274241 and 52474261)the Natural Science Foundation of Jiangsu Province(No.BK20240207).
文摘Through a case analysis,this study examines the spatiotemporal evolution of microseismic(MS)events,energy characteristics,volumetric features,and fracture network development in surface well hydraulic fracturing.A total of 349 MS events were analyzed across different fracturing sections,revealing significant heterogeneity in fracture propagation.Energy scanning results showed that cumulative energy values ranged from 240 to 1060 J across the sections,indicating notable differences.Stimulated reservoir volume(SRV)analysis demonstrated well-developed fracture networks in certain sections,with a total SRV exceeding 1540000 m^(3).The hydraulic fracture network analysis revealed that during the midfracturing stage,the density and spatial extent of MS events significantly increased,indicating rapid fracture propagation and the formation of complex networks.In the later stage,the number of secondary fractures near fracture edges decreased,and the fracture network stabilized.By comparing the branching index,fracture length,width,height,and SRV values across different fracturing sections,Sections No.1 and No.8 showed the best performance,with high MS event densities,extensive fracture networks,and significant energy release.However,Sections No.4 and No.5 exhibited sparse MS activity and poor fracture connectivity,indicating suboptimal stimulation effectiveness.
文摘For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system has settled the problems of recognizing and controlling the unknown, uncertain and nonlinear system successfully, and has been applied to hydraulic roll bending control. The simulation results indicate that the system has good performance and strong robustness, and is better than traditional PID and neural-fuzzy control. The method is an effective tool to control roll bending force with increased dynamic response speed of control system and enhanced tracking accuracy.
基金financially supported by,the Fundamental Research Funds for the Central Universities(Grant No.2023QN1064)the China Postdoctoral Science Foundation(Grant No.2023M733772)Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant No.2023ZB847)。
文摘Prepulse combined hydraulic fracturing facilitates the development of fracture networks by integrating prepulse hydraulic loading with conventional hydraulic fracturing.The formation mechanisms of fracture networks between hydraulic and pre-existing fractures under different prepulse loading parameters remain unclear.This research investigates the impact of prepulse loading parameters,including the prepulse loading number ratio(C),prepulse loading stress ratio(S),and prepulse loading frequency(f),on the formation of fracture networks between hydraulic and pre-existing fractures,using both experimental and numerical methods.The results suggest that low prepulse loading stress ratios and high prepulse loading number ratios are advantageous loading modes.Multiple hydraulic fractures are generated in the specimen under the advantageous loading modes,facilitating the development of a complex fracture network.Fatigue damage occurs in the specimen at the prepulse loading stage.The high water pressure at the secondary conventional hydraulic fracturing promotes the growth of hydraulic fractures along the damage zones.This allows the hydraulic fractures to propagate deeply and interact with pre-existing fractures.Under advantageous loading conditions,multiple hydraulic fractures can extend to pre-existing fractures,and these hydraulic fractures penetrate or propagate along pre-existing fractures.Especially when the approach angle is large,the damage range in the specimen during the prepulse loading stage increases,resulting in the formation of more hydraulic fractures.
文摘The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.
文摘With the purpose of making calculation more efficient in practical hydraulic simulations, an improved algorithm was proposed and was applied in the practical water distribution field. This methodology was developed by expanding the traditional loop-equation theory through utilization of the advantages of the graph theory in efficiency. The utilization of the spanning tree technique from graph theory makes the proposed algorithm efficient in calculation and simple to use for computer coding. The algorithms for topological generation and practical implementations are presented in detail in this paper. Through the application to a practical urban system, the consumption of the CPU time and computation memory were decreased while the accuracy was greatly enhanced compared with the present existing methods.
基金supported by the National Natural Science Foundation of China(Nos.42077243,52209148,and 52079062).
文摘With an extension of the geological entropy concept in porous media,the approach called directional entrogram is applied to link hydraulic behavior to the anisotropy of the 3D fracture networks.A metric called directional entropic scale is used to measure the anisotropy of spatial order in different directions.Compared with the traditional connectivity indexes based on the statistics of fracture geometry,the directional entropic scale is capable to quantify the anisotropy of connectivity and hydraulic conductivity in heterogeneous 3D fracture networks.According to the numerical analysis of directional entrogram and fluid flow in a number of the 3D fracture networks,the hydraulic conductivities and entropic scales in different directions both increase with spatial order(i.e.,trace length decreasing and spacing increasing)and are independent of the dip angle.As a result,the nonlinear correlation between the hydraulic conductivities and entropic scales from different directions can be unified as quadratic polynomial function,which can shed light on the anisotropic effect of spatial order and global entropy on the heterogeneous hydraulic behaviors.
基金This project is supported by National Natural Science Foundation of China (No.50175097).
文摘The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully carried out for hydraulic axial piston pump based on experiments with the MATLAB and the toolbox of neural networks, The operating pressure, the flow rate of hydraulic axial piston pump, the temperature of hydraulic oil, and bulk modulus of hydraulic oil are the main parameters having influences on the noise of hydraulic axial piston pump. These four parameters are used as inputs of neural networks, and experimental data of the noise are used as outputs of neural networks, Error of noise identification is less than 1% after the neural networks have been trained. The results show that the noise identification of hydraulic axial piston pump is feasible and reliable by using artificial neural networks. The method of noise identification with neural networks is also creative one of noise theoretical research for hydraulic axial piston pump.
基金Supported by the National Natural Science Foundation of China(52274014,52421002).
文摘By integrating laboratory physical modeling experiments with machine learning-based analysis of dominant factors,this study explored the feasibility of pulse hydraulic fracturing(PHF)in deep coal rocks and revealed the fracture propagation patterns and the mechanisms of pulsating loading in the process.The results show that PHF induces fatigue damage in coal matrix,significantly reducing breakdown pressure and increasing fracture network volume.Lower vertical stress differential coefficient(less than 0.31),lower peak pressure ratio(less than 0.9),higher horizontal stress differential coefficient(greater than 0.13),higher pulse amplitude ratio(greater than or equal to 0.5)and higher pulse frequency(greater than or equal to 3 Hz)effectively decrease the breakdown pressure.Conversely,higher vertical stress differential coefficient(greater than or equal to 0.31),higher pulse amplitude ratio(greater than or equal to 0.5),lower horizontal stress differential coefficient(less than or equal to 0.13),lower peak pressure ratio(less than 0.9),and lower pulse frequency(less than 3 Hz)promote the formation of a complex fracture network.Vertical stress and peak pressure are the most critical geological and engineering parameters affecting the stimulation effectiveness of PHF.The dominant mechanism varies with coal rank due to differences in geomechanical characteristics and natural fracture development.Low-rank coal primarily exhibits matrix strength degradation.High-rank coal mainly involves the activation of natural fractures and bedding planes.Medium-rank coal shows a coexistence of matrix strength degradation and micro-fracture connectivity.The PHF forms complex fracture networks through the dual mechanism of matrix strength degradation and fracture network connectivity enhancement.
文摘Artificial neural networks （ANNs） and genetic programming （GP） have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the characteristics of hydraulic jumps, such as the free surface location and energy dissipation. The dimensionless hydraulic parameters, including jump depth, jump length, and energy dissipation, were determined as functions of the Froude number and the height and length of corrugations. The estimations of the ANN and GP models were found to be in good agreement with the measured data. The results of the ANN model were compared with those of the GP model, showing that the proposed ANN models are much more accurate than the GP models.
基金Supported by the National Natural Science Foundation of China(51305457)。
文摘To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power system are given for the precision requirement,and a control strategy for dual relative control parameters in the dual loop PID is put forward,a load and throttle rotation-speed response model for variable pump and gasoline engine is provided according to a physical process,a simplified neural network structure PID is introduced,and formed mixed neural network PID(MNN PID)to control rotation speed of engine and pressure of variable pump,calculation using the back propagation(BP)algorithm and a self-adapted learning step is made,including a mathematic principle and a calculation flow scheme,the BP algorithm of neural network PID is trained and the control effect of system is simulated in Matlab environment,real control effects of engine rotation speed and variable pump pressure are verified in the experimental bench.Results show that algorithm effect of MNN PID is stable and MNN PID can meet the adjusting requirement of control parameters.
文摘To make a large area of dredger fill silt surface layer form working face and subsequent construction problems, the project conducts the bamboo network reinforcement in the silt surface layer. It makes the surface layer bearing capacity to meet the construction requirement of deep processing. Based on Shantou Municipal Road Embankment Treatment Engineering and the project, the bamboo network reinforcement technology to reinforce the dredger fill super soft soil surface layer is used. The results show that the bearing capacity of hydraulic fill super soft soil surface layer is 32.6 kPa after 3 months treatment. The surface layer bearing capacity after 3 months treatment improved 323% than the early treatment and increased 695% than no processing. The results indicate that the reinforcement effect is outstanding and provide the basis for drafting the dredger fill super soft soil surface layer treatment plan.
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;">The reliability and ease of applying metaheuristic methods in solving large and complex equation systems make it interesting to be applied as an alternative solution to solving problems in various fields. This article proves the effectiveness of an optimization model based on the <span style="font-family:Verdana;">m<span style="font-family:Verdana;">etaheuristic method for the analysis of hydraulic parameters of drinking water distribution pipes. The metaheuristic methods explored are Differential Evolution (DE) algorithm, Particle Swam Optimization (PSO) algorithm and CODEQ algorithm. The effectiveness of the three methods is measured relative by comparing the results of the analysis of the three models with the results from Newton Raphson method and Monte Carlo simulation method. The analysis shows that the optimization model based on the DE, PSO and CODEQ algorithms is very effective for solving problems on a simple network that has 6 pipe elements and 5 service nodes. The results obtained have a level of accuracy as good as Newton Raphson method. In the case of complex networks that have 32 pipe elements and 21 service nodes, there is an indication of performance degradation which is indicated by a decrease in fitness value. In this case, Newton Raphson method still shows its consistency. The optimization model based on the metaheuristic method is still far more effective than the Monte Carlo simulation method, although it is not as effective as Newton Raphson method. The Monte Carlo simulation method is not recommended for hydraulic pipe network analysis, even for simple networks.
基金Supported by National Natural Science Foundation of China(Grant No.51705531)Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20150724)
文摘Hydraulic systems have the characteristics of strong fault concealment,powerful nonlinear time-varying signals,and a complex vibration transmission mechanism;hence,diagnosis of these systems is a challenge.To provide accurate diagnosis results automatically,numerous studies have been carried out.Among them,signal-based methods are commonly used,which employ signal processing techniques based on the state signal used for extracting features,and further input the features into the classifier for fault recognition.However,their main deficiencies include the following:(1)The features are manually designed and thus may have a lack of objectivity.(2)For signal processing,feature extraction and pattern recognition are conducted using independent models,which cannot be jointly optimized globally.(3)The machine learning algorithms adopted by these methods have a shallow architecture,which limits their capacity to deeply mine the essential features of a fault.As a breakthrough in artificial intelligence,deep learning holds the potential to overcome such deficiencies.Based on deep learning,deep neural networks(DNNs)can automatically learn the complex nonlinear relations implied in a signal,can be globally optimized,and can obtain the high-level features of multi-dimensional data.In this paper,the main technology used in an intelligent fault diagnosis and the current research status of hydraulic system fault diagnosis are summarized and analyzed.The significant prospect of applying deep learning in the field of intelligent fault diagnosis is presented,and the main ideas,methods,and principles of several typical DNNs are described and summarized.The commonality between a fault diagnosis and other issues regarding typical pattern recognition are analyzed,and research ideas for applying DNNs for hydraulic fault diagnosis are proposed.Meanwhile,the research advantages and development trend of DNNs(both domestically and overseas)as applied to an intelligent fault diagnosis are reviewed.Furthermore,the fault characteristics of a complex hydraulic system are summarized and discussed,and the key problems and possible research ideas of applying DNNs to an intelligent hydraulic fault diagnosis are presented and comprehensively analyzed.
基金Supported by National Natural Science Foundation of China(Grant No.51805350)Key Technologies Research and Development Program of China(Grant No.2018YFB2001202)+1 种基金Natural Science Foundation of Shanxi Province of China(Grant No.201801D221226)Postdoctoral Science Foundation of China(Grant No.2019M651073).
文摘The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor valve.Essentially,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load pressure.The flow fluctuation severely restricts the application of the Valvistor valve.In this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow valve.The mathematical model of this valve is established and linearized.Fuzzy proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control system.The feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main orifice.The results show that inference with BPNN can obtain the flow data fast and accurately.With the flow control method,the flow can keep at the set point when the pressure differential across the main orifice changes.The flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow valve.For the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes abruptly.The performances of hysteresis,linearity and bandwidth are in a high range.The linear mathematical model can be verified and the assumptions in the system modeling is reasonable.
基金partially supported by the National Key Research&Development Plan of China(Grant No.2017YFC0804203)International Cooperation Project of Chinese Academy of Sciences(Grant No.115242KYSB20160024)the Open Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(Grant No.Z016003)
文摘In this context, recent developments in the coupled three-dimensional(3 D) hydro-mechanical(HM)simulation tool TOUGH-RBSN are presented. This tool is used to model hydraulic fracture in geological media, as observed in laboratory-scale tests. The TOUGH-RBSN simulator is based on the effective linking of two numerical methods: TOUGH2, a finite volume method for simulating mass transport within a permeable medium; and a lattice model based on the rigid-body-spring network(RBSN) concept. The method relies on a Voronoi-based discretization technique that can represent fracture development within a permeable rock matrix. The simulator provides two-way coupling of HM processes, including fluid pressure-induced fracture and fracture-assisted flow. We first present the basic capabilities of the modeling approach using two example applications, i.e. permeability evolution under compression deformation, and analyses of a static fracturing simulation. Thereafter, the model is used to simulate laboratory tests of hydraulic fracturing in granite. In most respects, the simulation results meet expectations with respect to permeability evolution and fracturing patterns. It can be seen that the evolution of injection pressure associated with the simulated fracture developments is strongly affected by fluid viscosity.
