This study proposes a nondestructive optical imaging-based three-dimensional(3D)reconstruction method to analyse electrical tree propagation in polypropylene(PP)cable insulation under mechanical bending.The technique ...This study proposes a nondestructive optical imaging-based three-dimensional(3D)reconstruction method to analyse electrical tree propagation in polypropylene(PP)cable insulation under mechanical bending.The technique combines focus-stacked optical imaging with a feature fusion algorithm to segment in-focus regions across depth layers,enabling 3D reconstruction of electrical trees in PP homopolymer(PPH),block copolymer(PPB)and elastomer-blended(PP/TPE)samples.The results demonstrate that mechanical bending accelerates electrical tree propagation in PPH,and that degradation channels transition from a branch-like to a straight-stick morphology,tending to grow directionally towards stretched regions.With a bending radius of 10 mm,the breakdown time drops from 297.0 min for the undeformed samples to 6.3 min.PPB and PP/TPE delay the time to breakdown by 70.6%and 171.2%,respectively,highlighting their superior resistance under bending stress,which is attributed to maintaining elasticity rather than yield deformation under bending stresses.This study provides a novel tool for evaluating the electrical tree resistance of PP composites under the mechanical stress,guiding the development of recyclable high-voltage direct current cable insulation.展开更多
Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian ne...Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network （PBNN） nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter αk, which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.展开更多
Karst fractures serve as crucial seepage channels and storage spaces for carbonate natural gas reservoirs,and electrical image logs are vital data for visualizing and characterizing such fractures.However,the conventi...Karst fractures serve as crucial seepage channels and storage spaces for carbonate natural gas reservoirs,and electrical image logs are vital data for visualizing and characterizing such fractures.However,the conventional approach of identifying fractures using electrical image logs predominantly relies on manual processes that are not only time-consuming but also highly subjective.In addition,the heterogeneity and strong dissolution tendency of karst carbonate reservoirs lead to complexity and variety in fracture geometry,which makes it difficult to accurately identify fractures.In this paper,the electrical image logs network(EILnet)da deep-learning-based intelligent semantic segmentation model with a selective attention mechanism and selective feature fusion moduledwas created to enable the intelligent identification and segmentation of different types of fractures through electrical logging images.Data from electrical image logs representing structural and induced fractures were first selected using the sliding window technique before image inpainting and data augmentation were implemented for these images to improve the generalizability of the model.Various image-processing tools,including the bilateral filter,Laplace operator,and Gaussian low-pass filter,were also applied to the electrical logging images to generate a multi-attribute dataset to help the model learn the semantic features of the fractures.The results demonstrated that the EILnet model outperforms mainstream deep-learning semantic segmentation models,such as Fully Convolutional Networks(FCN-8s),U-Net,and SegNet,for both the single-channel dataset and the multi-attribute dataset.The EILnet provided significant advantages for the single-channel dataset,and its mean intersection over union(MIoU)and pixel accuracy(PA)were 81.32%and 89.37%,respectively.In the case of the multi-attribute dataset,the identification capability of all models improved to varying degrees,with the EILnet achieving the highest MIoU and PA of 83.43%and 91.11%,respectively.Further,applying the EILnet model to various blind wells demonstrated its ability to provide reliable fracture identification,thereby indicating its promising potential applications.展开更多
Accurately characterizing the storage space of fractured-vuggy carbonate reservoirs is a major technical challenge in the efficient exploration and development of the petroleum industry.Electrical image logs are an ef...Accurately characterizing the storage space of fractured-vuggy carbonate reservoirs is a major technical challenge in the efficient exploration and development of the petroleum industry.Electrical image logs are an effective technique for identifying and evaluating dissolution vugs in carbonate reservoirs.However,due to limitations in the wellbore structure and the design of instruments,the images of electrical image logs often contain numerous blank strips,which affects the accuracy of subsequent vug processing and interpretation.To finely evaluate the pore structu re of karst reservoirs and quantitatively characterize reservoir parameters,this study proposes an automatic identification method for dissolution vugs in electrical image logs,integrating image inpainting and regional segme ntation based on an improved deep image prior(I DIP)framework.Firstly,the I DIP neural network model,leveraging its structural characteristics,uses a random mask and image data as input to iteratively learn low-level features at known pixel points and extend these features to blank areas of the image.This approach allows clear capture of the structure and texture information of vugs in blank strips,even in the absence of sufficient training samples.Subsequently,based on the inpainted images,the Otsu algorithm is used to determine the optimal global threshold,and then the watershed algorithm is applied to segment and label the vug targets,which addresses the problem of over-segmentation when separating the vug information from the stratigraphic background.Finally,the Freeman chain code is used to store and calculate vug parameters,converting the picked vug area into areal porosity to quantitatively assess the develo p ment degree of fractures and vugs in the reservoir.The results show a good correlation with core porosity and are superior to calculations without image inpainting.This study presents a method based on image processing for vug identification and evaluation of karst re servoirs,demonstrating high consistency with actual field data and providing theoretical support and methodological refe rence for the classification and evaluation of similar reservoirs.展开更多
Borehole-to-surface electrical imaging （BSEI） uses a line source and a point source to generate a stable electric field in the ground. In order to study the surface potential of anomalies, three-dimensional forward ...Borehole-to-surface electrical imaging （BSEI） uses a line source and a point source to generate a stable electric field in the ground. In order to study the surface potential of anomalies, three-dimensional forward modeling of point and line sources was conducted by using the finite-difference method and the incomplete Cholesky conjugate gradient （ICCG） method. Then, the damping least square method was used in the 3D inversion of the formation resistivity data. Several geological models were considered in the forward modeling and inversion. The forward modeling results suggest that the potentials generated by the two sources have different surface signatures. The inversion data suggest that the low- resistivity anomaly is outlined better than the high-resistivity anomaly. Moreover, when the point source is under the anomaly, the resistivity anomaly boundaries are better outlined than when using a line source.展开更多
The electrical contact-high-speed imaging experimental system was developed to investigate the molten bridge phenomena of AgNi10 electrical contact material.The dimension of molten bridges was measured along with the ...The electrical contact-high-speed imaging experimental system was developed to investigate the molten bridge phenomena of AgNi10 electrical contact material.The dimension of molten bridges was measured along with the measurement of waveforms in the contact voltage under the load of direct current(DC) 6 V(8-20 A)and breaking speed of 50.0 mm·s^(-1).A part of the observed results was presented as well as surface morphology of the contacts after electrical contact behavior,which shows some interesting and new phenomena.Molten bridges and arc could exist simultaneously.The stable molten bridge looks like cylindrical shape and then becomes needle tip at its rupture,the diameter and length of molten bridges both increase with the increase in current and the growth gradient of the diameter is larger than that of the length.The morphology and elemental distribution of the contact surface are changed by the behavior of electrical contact.展开更多
Sixty-four multi-electrode Lund imaging system coupled with ABEM SAS 4000 Terrameter was used for the electrical imaging of the study area. Wenner and Gradient arrays with 2 m minimum electrode spacing were employed w...Sixty-four multi-electrode Lund imaging system coupled with ABEM SAS 4000 Terrameter was used for the electrical imaging of the study area. Wenner and Gradient arrays with 2 m minimum electrode spacing were employed which revealed resistivity changes in the vertical and horizontal directions along the survey lines. Earth imager software was employed for?the processing and the iteration of the 2-D resistivity data. The subsurface is characterized with soil material with resistivity ranging from 42 - 15,000 Ohm-m, reflective of varying degree of conductivity associated with changing lithology and fluid type. Correlation with borehole data shows that the first 10 m is composed of laterite. While sand materials occupy 10 to about 60 m beneath the surface, with anomalously high resistivity ≤15,000 Ohm-m in most parts. These high resistivity formations can be attributed to the presence of hydrocarbon within the subsurface, which is an indication that shallow aquifer in the study area has been polluted. The water level in the study area is close to the surface, between 4 - 5 m. As a result of the high resistivity formations in most parts, deep wells of about 45 m are recommended after geophysical investigations.展开更多
To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network(RBFNN) based on information crite...To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network(RBFNN) based on information criterion(IC) and particle swarm optimization(PSO) is presented. In the proposed method, IC is applied to obtain the hidden layer structure by calculating the optimal IC value automatically and PSO algorithm is used to optimize the centers and widths of the radial basis functions in the hidden layer. Meanwhile, impacts of different information criteria to the inversion results are compared, and an implementation of the proposed ICPSO algorithm is given. The optimized neural network has one hidden layer with 261 nodes selected by AKAIKE's information criterion(AIC) and it is trained on 32 data sets and tested on another 8 synthetic data sets. Two complex synthetic examples are used to verify the feasibility and effectiveness of the proposed method with two learning stages. The results show that the proposed method has better performance and higher imaging quality than three-layer and four-layer back propagation neural networks(BPNNs) and traditional least square(LS) inversion.展开更多
Lack of access to potable and adequate water is a major problem for sustainable development in northern Ghana. Developing groundwater resource is the best option for safe, reliable, and cost-efficient water supplies t...Lack of access to potable and adequate water is a major problem for sustainable development in northern Ghana. Developing groundwater resource is the best option for safe, reliable, and cost-efficient water supplies to these dispersed communities. In this study, nine 2D ERI profiles were carried out with the Schlumberger array in eight communities underlain by the crystalline basement rocks in the Bole District of the Savannah Region of Ghana. The aim was to delineate the aquifer zones and select points for groundwater extraction. Nine boreholes were drilled from the selected points. The yield was found to vary from 12 to 180 l/min with a depth range of 50 to 70 m. The weathered and fractured zones together with the bedrock topography were clearly marked. It is evident that the 2D electrical resistivity technique is useful tool in determining the availability of groundwater in weathered and fractured crystalline environment.展开更多
Electrical resistivity imaging surveys have been conducted in order to locate, delineate subsurface water resource and estimate its reserve. The resistivity imaging surveys carried out basically measure and map the re...Electrical resistivity imaging surveys have been conducted in order to locate, delineate subsurface water resource and estimate its reserve. The resistivity imaging surveys carried out basically measure and map the resistivity of subsurface materials. Electrical imaging is an appropriate survey technique for areas with complex geology where the use of resistivity sounding and other techniques are unsuitable to provide detailed subsurface information. The purpose of electrical surveys is to determine the subsurface resistivity distribution by making measurements on the ground surface. The resistivity imaging measurement employing Wenner electrode configuration was carried out using an ABEM SAS 1000 terrameter and electrode selector system ES464. The field survey was conducted along four profiles which provide a continuous coverage of the resistivity imaging below surface. The surface soil material is mainly clayey silt. The results showed that the layers associated with the low resistivities （Ωm） are located at depth ranging from 2 m to 28 m. This low resistivity values are associated with zone of water saturated weathered layer and fractures. The results showed that the thickness of residual soil is about 0.5-2.55 m. Borehole data indicated that the depth of bedrock is about 10 m and the groundwater level is ranging from 8.73 m to 8.54 m.展开更多
We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs bas...We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs based on electric imaging logging data. We automatically identify and extract fracture–vug information from the electric imaging images by adopting a path morphological operator that remains flexible enough to fit rectilinear and slightly curved structures because they are independent of the structuring element shape. The Otsu method was used to extract fracture–vug information from the background noise caused by the matrix. To accommodate the differences in scale and form of the different target regions,including fracture and vug path, operators with different lengths were selected for their recognition and extraction at the corresponding scale. Polynomial and elliptic functions are used to fit the extracted fractures and vugs, respectively, and the fracture–vug parameters are deduced from the fitted edge. Finally, test examples of numerical simulation data and several measured well data have been provided for the verification of the effectiveness and adaptability of the path morphology method in the application of electric imaging logging data processing. This also provides algorithm support for the fine evaluation of fracture–vug reservoirs.展开更多
Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on t...Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on the tool design and borehole size,and the null data in these gaps negatively aff ect the quantitative evaluation of reservoirs.Images with linear and texture features obtained from microresistivity image logs have distinct dual fabric features because of logging principles and various geological phenomena.Linear image features usually include phenomena such as fractures,bedding,and unconformities.Contrarily,texture-based image features usually indicate phenomena such as vugs and rock matrices.According to the characteristics of this fabric-based binary image structure and guided by the practice of geological interpretation,an adaptive inpainting method for the blank gaps in microresistivity image logs is proposed.For images with linear features,a sinusoidal tracking inpainting algorithm based on an evaluation of the validity and continuity of pixel sets is used.Contrarily,the most similar target transplantation algorithm is applied to texture-based images.The results obtained for measured electrical imaging data showed that the full borehole image obtained by the proposed method,whether it was a linear structural image refl ecting fracture and bedding or texture-based image refl ecting the matrix and pore of rock,had substantially good inpainting quality with enhanced visual connectivity.The proposed method was eff ective for inpainting electrical image logs with large gaps and high angle fractures with high heterogeneity.Moreover,ladder and block artifacts were rare,and the inpainting marks were not obvious.In addition,detailed full borehole images obtained by the proposed method will provide an essential basis for interpreting geological phenomena and reservoir parameters.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
Electrical capacitance tomography(ECT)has been applied to two-phase flow measurement in recent years.Image reconstruction algorithms play an important role in the successful applications of ECT.To solve the ill-posed ...Electrical capacitance tomography(ECT)has been applied to two-phase flow measurement in recent years.Image reconstruction algorithms play an important role in the successful applications of ECT.To solve the ill-posed and nonlinear inverse problem of ECT image reconstruction,a new ECT image reconstruction method based on fast linearized alternating direction method of multipliers(FLADMM)is proposed in this paper.On the basis of theoretical analysis of compressed sensing(CS),the data acquisition of ECT is regarded as a linear measurement process of permittivity distribution signal of pipe section.A new measurement matrix is designed and L1 regularization method is used to convert ECT inverse problem to a convex relaxation problem which contains prior knowledge.A new fast alternating direction method of multipliers which contained linearized idea is employed to minimize the objective function.Simulation data and experimental results indicate that compared with other methods,the quality and speed of reconstructed images are markedly improved.Also,the dynamic experimental results indicate that the proposed algorithm can ful fill the real-time requirement of ECT systems in the application.展开更多
Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using im...Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using image segmentation technique of electric imaging logging data. Firstly, based on Hagen-Poiseuille's law of incompressible fluid flow and the different cross-sectional areas in single fractures and vugs in carbonate reservoirs, a multi-scale conduit flow model for fracture-vug carbonate reservoir was established, and a multi-scale conduit radial fluid flow equation was deduced. Then, conduit flow production index was introduced. The conduit flow production index was calculated using fracture-vug area extracted from the result of electrical image segmentation. Finally, production prediction of fracture-vug carbonate reservoir was realized by using electric imaging logging data. The method has been applied to Ordovician fracture-vug carbonate reservoirs in the Tabei area, and the predicted results are in good agreement with the oil testing data.展开更多
Electrical impedance tomography(EIT)is a non-invasive imaging modality that generates real-time images by measuring tissue bioimpedance.It works by applying current and collecting voltage data to reconstruct images of...Electrical impedance tomography(EIT)is a non-invasive imaging modality that generates real-time images by measuring tissue bioimpedance.It works by applying current and collecting voltage data to reconstruct images of electrical conductivity,refl ecting tissue properties.[1]We aim to off er a comprehensive guide to the fundamental technology behind EIT and to explore its clinical applications across both pulmonary and extrapulmonary domains.展开更多
Gradient coil is an essential component of a magnetic resonance imaging(MRI)scanner.To achieve high spatial resolution and imaging speed,a high-efficiency gradient coil with high slew rate is required.In consideration...Gradient coil is an essential component of a magnetic resonance imaging(MRI)scanner.To achieve high spatial resolution and imaging speed,a high-efficiency gradient coil with high slew rate is required.In consideration of the safety and comfort of the patient,the mechanical stability,acoustic noise and peripheral nerve stimulation(PNS)are also need to be concerned for practical use.In our previous work,a high-efficiency whole-body gradient coil set with a hybrid cylindrical-planar structure has been presented,which offers significantly improved coil performances.In this work,we propose to design this transverse gradient coil system with transformed magnetic gradient fields.By shifting up the zero point of gradient fields,the designed new Y-gradient coil could provide enhanced electromagnetic performances.With more uniform coil winding arrangement,the net torque of the new coil is significantly reduced and the generated sound pressure level(SPL)is lower at most tested frequency bands.On the other hand,the new transverse gradient coil designed with rotated magnetic gradient fields produces considerably reduced electric field in the human body,which is important for the use of rapid MR sequences.It's demonstrated that a safer and patient-friendly design could be obtained by using transformed magnetic gradient fields,which is critical for practical use.展开更多
In electrical impedance tomography (EIT) an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. Several...In electrical impedance tomography (EIT) an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. Several difficulties have been identified in EIT, where the main problem is the low spatial resolution. This paper presents a fining mesh method based on finite element method (FEM), by fining the sensitive element, the most actual signal is obtained in certain electrode number. Newton-Raphson reconstruction algorithm improves the spatial solution of image. The advantages of this method are the improvement of spatial resolution and ease of implementation.展开更多
Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combine...Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combined electrical-thermal-mechanical stress over long operating times.In this paper,the chemical characteristics of oil-pressboard insulation samples subjected to electrical-thermal-mechanical ageing for different times are studied.An image processing algorithm is used to analyse the discharge propagation characteristics of the samples under combined alternating current(AC)-direct current(DC)voltage,and the current pulse curves and phase resolved partial discharge spectrogram corresponding to the discharge images are analysed.An improved wavelet packet algorithm is used to denoise the discharge current pulse.Finally,the influence of electrical-thermal-mechanical ageing on discharge characteristics is analysed using radar charts.The condition of oil-pressboard insulation is one of the main factors determining the life expectancy of converter transformers.The results obtained here therefore have practical significance for understanding the process of insulation failure caused by accelerated ageing of oil-pressboard insulation.展开更多
Because of the illposedness of soft field, the quality of EIT images is not satisfied as expected. This paper puts forward a threshold strategy to decrease the artifacts in the reconstructed images by modifying the so...Because of the illposedness of soft field, the quality of EIT images is not satisfied as expected. This paper puts forward a threshold strategy to decrease the artifacts in the reconstructed images by modifying the solutions of inverse problem. Threshold strategy is a kind of post processing method with merits of easy, direct and efficient. Reconstructed by Gauss-Newton algorithm, the simulation image’s quality is improved evidently. We take two performance targets, image reconstruction error and correlation coefficient, to evaluate the improvement. The images and the data show that threshold strategy is effective and achievable.展开更多
基金supported by National Natural Science Foundation of China(Grants 52477151 and 52522702).
文摘This study proposes a nondestructive optical imaging-based three-dimensional(3D)reconstruction method to analyse electrical tree propagation in polypropylene(PP)cable insulation under mechanical bending.The technique combines focus-stacked optical imaging with a feature fusion algorithm to segment in-focus regions across depth layers,enabling 3D reconstruction of electrical trees in PP homopolymer(PPH),block copolymer(PPB)and elastomer-blended(PP/TPE)samples.The results demonstrate that mechanical bending accelerates electrical tree propagation in PPH,and that degradation channels transition from a branch-like to a straight-stick morphology,tending to grow directionally towards stretched regions.With a bending radius of 10 mm,the breakdown time drops from 297.0 min for the undeformed samples to 6.3 min.PPB and PP/TPE delay the time to breakdown by 70.6%and 171.2%,respectively,highlighting their superior resistance under bending stress,which is attributed to maintaining elasticity rather than yield deformation under bending stresses.This study provides a novel tool for evaluating the electrical tree resistance of PP composites under the mechanical stress,guiding the development of recyclable high-voltage direct current cable insulation.
基金supported by the National Natural Science Foundation of China(Grant No.41374118)the Research Fund for the Higher Education Doctoral Program of China(Grant No.20120162110015)+3 种基金the China Postdoctoral Science Foundation(Grant No.2015M580700)the Hunan Provincial Natural Science Foundation,the China(Grant No.2016JJ3086)the Hunan Provincial Science and Technology Program,China(Grant No.2015JC3067)the Scientific Research Fund of Hunan Provincial Education Department,China(Grant No.15B138)
文摘Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network （PBNN） nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter αk, which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.
基金the National Natural Science Foundation of China(42472194,42302153,and 42002144)the Fundamental Research Funds for the Central Univer-sities(22CX06002A).
文摘Karst fractures serve as crucial seepage channels and storage spaces for carbonate natural gas reservoirs,and electrical image logs are vital data for visualizing and characterizing such fractures.However,the conventional approach of identifying fractures using electrical image logs predominantly relies on manual processes that are not only time-consuming but also highly subjective.In addition,the heterogeneity and strong dissolution tendency of karst carbonate reservoirs lead to complexity and variety in fracture geometry,which makes it difficult to accurately identify fractures.In this paper,the electrical image logs network(EILnet)da deep-learning-based intelligent semantic segmentation model with a selective attention mechanism and selective feature fusion moduledwas created to enable the intelligent identification and segmentation of different types of fractures through electrical logging images.Data from electrical image logs representing structural and induced fractures were first selected using the sliding window technique before image inpainting and data augmentation were implemented for these images to improve the generalizability of the model.Various image-processing tools,including the bilateral filter,Laplace operator,and Gaussian low-pass filter,were also applied to the electrical logging images to generate a multi-attribute dataset to help the model learn the semantic features of the fractures.The results demonstrated that the EILnet model outperforms mainstream deep-learning semantic segmentation models,such as Fully Convolutional Networks(FCN-8s),U-Net,and SegNet,for both the single-channel dataset and the multi-attribute dataset.The EILnet provided significant advantages for the single-channel dataset,and its mean intersection over union(MIoU)and pixel accuracy(PA)were 81.32%and 89.37%,respectively.In the case of the multi-attribute dataset,the identification capability of all models improved to varying degrees,with the EILnet achieving the highest MIoU and PA of 83.43%and 91.11%,respectively.Further,applying the EILnet model to various blind wells demonstrated its ability to provide reliable fracture identification,thereby indicating its promising potential applications.
基金supported by the National Natural Science Foundation of China(Grant No.42272180)。
文摘Accurately characterizing the storage space of fractured-vuggy carbonate reservoirs is a major technical challenge in the efficient exploration and development of the petroleum industry.Electrical image logs are an effective technique for identifying and evaluating dissolution vugs in carbonate reservoirs.However,due to limitations in the wellbore structure and the design of instruments,the images of electrical image logs often contain numerous blank strips,which affects the accuracy of subsequent vug processing and interpretation.To finely evaluate the pore structu re of karst reservoirs and quantitatively characterize reservoir parameters,this study proposes an automatic identification method for dissolution vugs in electrical image logs,integrating image inpainting and regional segme ntation based on an improved deep image prior(I DIP)framework.Firstly,the I DIP neural network model,leveraging its structural characteristics,uses a random mask and image data as input to iteratively learn low-level features at known pixel points and extend these features to blank areas of the image.This approach allows clear capture of the structure and texture information of vugs in blank strips,even in the absence of sufficient training samples.Subsequently,based on the inpainted images,the Otsu algorithm is used to determine the optimal global threshold,and then the watershed algorithm is applied to segment and label the vug targets,which addresses the problem of over-segmentation when separating the vug information from the stratigraphic background.Finally,the Freeman chain code is used to store and calculate vug parameters,converting the picked vug area into areal porosity to quantitatively assess the develo p ment degree of fractures and vugs in the reservoir.The results show a good correlation with core porosity and are superior to calculations without image inpainting.This study presents a method based on image processing for vug identification and evaluation of karst re servoirs,demonstrating high consistency with actual field data and providing theoretical support and methodological refe rence for the classification and evaluation of similar reservoirs.
基金sponsored by the National Major Project(No.2016ZX05014-001)the National Natural Science Foundation of China(No.41172130 and U1403191)the Fundamental Research Funds for the Central Universities(No.2-9-2015-209)
文摘Borehole-to-surface electrical imaging （BSEI） uses a line source and a point source to generate a stable electric field in the ground. In order to study the surface potential of anomalies, three-dimensional forward modeling of point and line sources was conducted by using the finite-difference method and the incomplete Cholesky conjugate gradient （ICCG） method. Then, the damping least square method was used in the 3D inversion of the formation resistivity data. Several geological models were considered in the forward modeling and inversion. The forward modeling results suggest that the potentials generated by the two sources have different surface signatures. The inversion data suggest that the low- resistivity anomaly is outlined better than the high-resistivity anomaly. Moreover, when the point source is under the anomaly, the resistivity anomaly boundaries are better outlined than when using a line source.
基金financially supported by the National Natural Science Foundation of China (Nos.51461023, 51267007,51164015,U1302272,515070575 and U1602275)the Natural Science Foundation of Yunnan Province (Nos.2010CD126, 2012FB195 and 2015FA042)+3 种基金the Yunnan Applied Basic Research Projects (No.2014FB164)the Innovation Team of Yunnan Province (No.2012HC027)the Technology innovation talents of Yunnan Province (No.2015HB024)the Fund of the State Key Laboratory of Advanced Technologies for Comprehensive Utilization of Platinum Metals (No.SKL-SPM-201526)。
文摘The electrical contact-high-speed imaging experimental system was developed to investigate the molten bridge phenomena of AgNi10 electrical contact material.The dimension of molten bridges was measured along with the measurement of waveforms in the contact voltage under the load of direct current(DC) 6 V(8-20 A)and breaking speed of 50.0 mm·s^(-1).A part of the observed results was presented as well as surface morphology of the contacts after electrical contact behavior,which shows some interesting and new phenomena.Molten bridges and arc could exist simultaneously.The stable molten bridge looks like cylindrical shape and then becomes needle tip at its rupture,the diameter and length of molten bridges both increase with the increase in current and the growth gradient of the diameter is larger than that of the length.The morphology and elemental distribution of the contact surface are changed by the behavior of electrical contact.
文摘Sixty-four multi-electrode Lund imaging system coupled with ABEM SAS 4000 Terrameter was used for the electrical imaging of the study area. Wenner and Gradient arrays with 2 m minimum electrode spacing were employed which revealed resistivity changes in the vertical and horizontal directions along the survey lines. Earth imager software was employed for?the processing and the iteration of the 2-D resistivity data. The subsurface is characterized with soil material with resistivity ranging from 42 - 15,000 Ohm-m, reflective of varying degree of conductivity associated with changing lithology and fluid type. Correlation with borehole data shows that the first 10 m is composed of laterite. While sand materials occupy 10 to about 60 m beneath the surface, with anomalously high resistivity ≤15,000 Ohm-m in most parts. These high resistivity formations can be attributed to the presence of hydrocarbon within the subsurface, which is an indication that shallow aquifer in the study area has been polluted. The water level in the study area is close to the surface, between 4 - 5 m. As a result of the high resistivity formations in most parts, deep wells of about 45 m are recommended after geophysical investigations.
基金Project(41374118)supported by the National Natural Science Foundation,ChinaProject(20120162110015)supported by Research Fund for the Doctoral Program of Higher Education,China+3 种基金Project(2015M580700)supported by the China Postdoctoral Science Foundation,ChinaProject(2016JJ3086)supported by the Hunan Provincial Natural Science Foundation,ChinaProject(2015JC3067)supported by the Hunan Provincial Science and Technology Program,ChinaProject(15B138)supported by the Scientific Research Fund of Hunan Provincial Education Department,China
文摘To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network(RBFNN) based on information criterion(IC) and particle swarm optimization(PSO) is presented. In the proposed method, IC is applied to obtain the hidden layer structure by calculating the optimal IC value automatically and PSO algorithm is used to optimize the centers and widths of the radial basis functions in the hidden layer. Meanwhile, impacts of different information criteria to the inversion results are compared, and an implementation of the proposed ICPSO algorithm is given. The optimized neural network has one hidden layer with 261 nodes selected by AKAIKE's information criterion(AIC) and it is trained on 32 data sets and tested on another 8 synthetic data sets. Two complex synthetic examples are used to verify the feasibility and effectiveness of the proposed method with two learning stages. The results show that the proposed method has better performance and higher imaging quality than three-layer and four-layer back propagation neural networks(BPNNs) and traditional least square(LS) inversion.
文摘Lack of access to potable and adequate water is a major problem for sustainable development in northern Ghana. Developing groundwater resource is the best option for safe, reliable, and cost-efficient water supplies to these dispersed communities. In this study, nine 2D ERI profiles were carried out with the Schlumberger array in eight communities underlain by the crystalline basement rocks in the Bole District of the Savannah Region of Ghana. The aim was to delineate the aquifer zones and select points for groundwater extraction. Nine boreholes were drilled from the selected points. The yield was found to vary from 12 to 180 l/min with a depth range of 50 to 70 m. The weathered and fractured zones together with the bedrock topography were clearly marked. It is evident that the 2D electrical resistivity technique is useful tool in determining the availability of groundwater in weathered and fractured crystalline environment.
文摘Electrical resistivity imaging surveys have been conducted in order to locate, delineate subsurface water resource and estimate its reserve. The resistivity imaging surveys carried out basically measure and map the resistivity of subsurface materials. Electrical imaging is an appropriate survey technique for areas with complex geology where the use of resistivity sounding and other techniques are unsuitable to provide detailed subsurface information. The purpose of electrical surveys is to determine the subsurface resistivity distribution by making measurements on the ground surface. The resistivity imaging measurement employing Wenner electrode configuration was carried out using an ABEM SAS 1000 terrameter and electrode selector system ES464. The field survey was conducted along four profiles which provide a continuous coverage of the resistivity imaging below surface. The surface soil material is mainly clayey silt. The results showed that the layers associated with the low resistivities （Ωm） are located at depth ranging from 2 m to 28 m. This low resistivity values are associated with zone of water saturated weathered layer and fractures. The results showed that the thickness of residual soil is about 0.5-2.55 m. Borehole data indicated that the depth of bedrock is about 10 m and the groundwater level is ranging from 8.73 m to 8.54 m.
基金granted access to projects supported by the National Major Fundamental Research Program of China ‘‘On basic research problems in applied geophysics for deep oil and gas fields’’(Grant Number 2013CB228605)CNPC Science and Technology Project(Grant Number 2016A-3303)and CNPC Logging Project(Grant Number 2017E-15)
文摘We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs based on electric imaging logging data. We automatically identify and extract fracture–vug information from the electric imaging images by adopting a path morphological operator that remains flexible enough to fit rectilinear and slightly curved structures because they are independent of the structuring element shape. The Otsu method was used to extract fracture–vug information from the background noise caused by the matrix. To accommodate the differences in scale and form of the different target regions,including fracture and vug path, operators with different lengths were selected for their recognition and extraction at the corresponding scale. Polynomial and elliptic functions are used to fit the extracted fractures and vugs, respectively, and the fracture–vug parameters are deduced from the fitted edge. Finally, test examples of numerical simulation data and several measured well data have been provided for the verification of the effectiveness and adaptability of the path morphology method in the application of electric imaging logging data processing. This also provides algorithm support for the fine evaluation of fracture–vug reservoirs.
基金This work was supported by Initial Scientifi c Research Fund for Doctor of Xinjiang University(No.620321016)Gansu Provincial Natural Science Foundation of China(No.17JR5RA313)Key Laboratory of Petroleum Resource Research of Chinese Academy of Science Foundation(No.KFJJ2016-02).
文摘Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on the tool design and borehole size,and the null data in these gaps negatively aff ect the quantitative evaluation of reservoirs.Images with linear and texture features obtained from microresistivity image logs have distinct dual fabric features because of logging principles and various geological phenomena.Linear image features usually include phenomena such as fractures,bedding,and unconformities.Contrarily,texture-based image features usually indicate phenomena such as vugs and rock matrices.According to the characteristics of this fabric-based binary image structure and guided by the practice of geological interpretation,an adaptive inpainting method for the blank gaps in microresistivity image logs is proposed.For images with linear features,a sinusoidal tracking inpainting algorithm based on an evaluation of the validity and continuity of pixel sets is used.Contrarily,the most similar target transplantation algorithm is applied to texture-based images.The results obtained for measured electrical imaging data showed that the full borehole image obtained by the proposed method,whether it was a linear structural image refl ecting fracture and bedding or texture-based image refl ecting the matrix and pore of rock,had substantially good inpainting quality with enhanced visual connectivity.The proposed method was eff ective for inpainting electrical image logs with large gaps and high angle fractures with high heterogeneity.Moreover,ladder and block artifacts were rare,and the inpainting marks were not obvious.In addition,detailed full borehole images obtained by the proposed method will provide an essential basis for interpreting geological phenomena and reservoir parameters.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
基金Supported by the National Natural Science Foundation of China(61203021)the Key Science and Technology Program of Liaoning Province(2011216011)+1 种基金the Natural Science Foundation of Liaoning Province(2013020024)the Program for Liaoning Excellent Talents in Universities(LJQ2015061)
文摘Electrical capacitance tomography(ECT)has been applied to two-phase flow measurement in recent years.Image reconstruction algorithms play an important role in the successful applications of ECT.To solve the ill-posed and nonlinear inverse problem of ECT image reconstruction,a new ECT image reconstruction method based on fast linearized alternating direction method of multipliers(FLADMM)is proposed in this paper.On the basis of theoretical analysis of compressed sensing(CS),the data acquisition of ECT is regarded as a linear measurement process of permittivity distribution signal of pipe section.A new measurement matrix is designed and L1 regularization method is used to convert ECT inverse problem to a convex relaxation problem which contains prior knowledge.A new fast alternating direction method of multipliers which contained linearized idea is employed to minimize the objective function.Simulation data and experimental results indicate that compared with other methods,the quality and speed of reconstructed images are markedly improved.Also,the dynamic experimental results indicate that the proposed algorithm can ful fill the real-time requirement of ECT systems in the application.
基金Supported by the China National Science and Technology Major Project(2011ZX05020-008)
文摘Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using image segmentation technique of electric imaging logging data. Firstly, based on Hagen-Poiseuille's law of incompressible fluid flow and the different cross-sectional areas in single fractures and vugs in carbonate reservoirs, a multi-scale conduit flow model for fracture-vug carbonate reservoir was established, and a multi-scale conduit radial fluid flow equation was deduced. Then, conduit flow production index was introduced. The conduit flow production index was calculated using fracture-vug area extracted from the result of electrical image segmentation. Finally, production prediction of fracture-vug carbonate reservoir was realized by using electric imaging logging data. The method has been applied to Ordovician fracture-vug carbonate reservoirs in the Tabei area, and the predicted results are in good agreement with the oil testing data.
基金supported partially by grants from the National Natural Science Foundation of China(82470068,82270086,GS Zhang82372185,BP Tian)+2 种基金the Natural Science Foundation of Zhejiang Province(Key Project)(LZ25H150001,GS Zhang)the National Health Commission Scientifi c Research Fund Zhejiang Provincial Health Major Science and Technology Plan Project(co-construction project of National Health Commission Committee and Zhejiang Province)(WKJ-ZJ-2526,GS Zhang)the Medical and Health Research Program of Zhejiang Province(2023572679).
文摘Electrical impedance tomography(EIT)is a non-invasive imaging modality that generates real-time images by measuring tissue bioimpedance.It works by applying current and collecting voltage data to reconstruct images of electrical conductivity,refl ecting tissue properties.[1]We aim to off er a comprehensive guide to the fundamental technology behind EIT and to explore its clinical applications across both pulmonary and extrapulmonary domains.
基金supported by the Instrument Developing Project of Magnetic Resonance Union of Chinese Academy of Sciences,Grant No.2022GZL002.
文摘Gradient coil is an essential component of a magnetic resonance imaging(MRI)scanner.To achieve high spatial resolution and imaging speed,a high-efficiency gradient coil with high slew rate is required.In consideration of the safety and comfort of the patient,the mechanical stability,acoustic noise and peripheral nerve stimulation(PNS)are also need to be concerned for practical use.In our previous work,a high-efficiency whole-body gradient coil set with a hybrid cylindrical-planar structure has been presented,which offers significantly improved coil performances.In this work,we propose to design this transverse gradient coil system with transformed magnetic gradient fields.By shifting up the zero point of gradient fields,the designed new Y-gradient coil could provide enhanced electromagnetic performances.With more uniform coil winding arrangement,the net torque of the new coil is significantly reduced and the generated sound pressure level(SPL)is lower at most tested frequency bands.On the other hand,the new transverse gradient coil designed with rotated magnetic gradient fields produces considerably reduced electric field in the human body,which is important for the use of rapid MR sequences.It's demonstrated that a safer and patient-friendly design could be obtained by using transformed magnetic gradient fields,which is critical for practical use.
文摘In electrical impedance tomography (EIT) an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. Several difficulties have been identified in EIT, where the main problem is the low spatial resolution. This paper presents a fining mesh method based on finite element method (FEM), by fining the sensitive element, the most actual signal is obtained in certain electrode number. Newton-Raphson reconstruction algorithm improves the spatial solution of image. The advantages of this method are the improvement of spatial resolution and ease of implementation.
基金supported by the Central Guided Local Science and Technology Development Project(Grant YDZX2022001).
文摘Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combined electrical-thermal-mechanical stress over long operating times.In this paper,the chemical characteristics of oil-pressboard insulation samples subjected to electrical-thermal-mechanical ageing for different times are studied.An image processing algorithm is used to analyse the discharge propagation characteristics of the samples under combined alternating current(AC)-direct current(DC)voltage,and the current pulse curves and phase resolved partial discharge spectrogram corresponding to the discharge images are analysed.An improved wavelet packet algorithm is used to denoise the discharge current pulse.Finally,the influence of electrical-thermal-mechanical ageing on discharge characteristics is analysed using radar charts.The condition of oil-pressboard insulation is one of the main factors determining the life expectancy of converter transformers.The results obtained here therefore have practical significance for understanding the process of insulation failure caused by accelerated ageing of oil-pressboard insulation.
文摘Because of the illposedness of soft field, the quality of EIT images is not satisfied as expected. This paper puts forward a threshold strategy to decrease the artifacts in the reconstructed images by modifying the solutions of inverse problem. Threshold strategy is a kind of post processing method with merits of easy, direct and efficient. Reconstructed by Gauss-Newton algorithm, the simulation image’s quality is improved evidently. We take two performance targets, image reconstruction error and correlation coefficient, to evaluate the improvement. The images and the data show that threshold strategy is effective and achievable.
